diff --git a/.DS_Store b/.DS_Store index 8f2c4bd..320b978 100644 Binary files a/.DS_Store and b/.DS_Store differ diff --git a/.gitignore b/.gitignore index 3af0ccb..1a1cd77 100644 --- a/.gitignore +++ b/.gitignore @@ -1 +1,3 @@ /data +/notebooks/mlruns/ +/models/* \ No newline at end of file diff --git a/README.md b/README.md index 495224a..bc5bf27 100644 --- a/README.md +++ b/README.md @@ -6,25 +6,9 @@

Our responsibility was to build a deep learning model that is capable of transcribing a speech to text in the Amharic language. The model we produce will be accurate and is robust against background noise.

+## Code +The code of our analysis can be found in the **notebooks** folder. The data preprocessing and visualization, and model training parts can be found in the **Amharic_STT_preprocessing.ipynb** jupyter notebook. This notebook can be run in google colab. The **Amharic_Speech_To_Text.ipynb** contains a modularized version of the first notebook. The **scripts** folder contains the data loading and preprocessing functions. The trained models will be stored in the **models** folder. -Structure -├── logs -├── modules -├── notebooks -├── tests -└── Dockerfile - -# Contributors - -* [Azaria Tamrat](https://github.com/Azariagmt) -* [Bethelhem Sisay](https://github.com/Bethelsis) -* [Daniel Zelalem](https://github.com/daniEL2371) -* [Dorothy Cheruiyot](https://github.com/Doro97) -* [Eliphaz Niyodusenga]() -* [Elizabeth Nanjala]() -* [Natneal Teshome](https://github.com/Natty-star) -* [UWASE Rachel](https://github.com/ntabanarachel) -* [Yosef Alemneh](https://github.com/mozartofmath) - - - +## Dependencies +To install the necessary dependencies, execute the command +```$ pip install -r requirements.txt"``` diff --git a/app.py b/app.py index e69de29..45d81aa 100644 --- a/app.py +++ b/app.py @@ -0,0 +1,35 @@ +import streamlit as st +import awesome_streamlit as ast +import scripts.pages.recorded_audio +import scripts.pages.record_audio +import scripts.pages.home +import scripts.pages.model_summary + +# create the pages +PAGES = { + "Home" : scripts.pages.home, + "Model Summary" : scripts.pages.model_summary, + "Choose Audio": scripts.pages.recorded_audio, + "Record your own voice": scripts.pages.record_audio, + +} + + +# render the pages +def main(): + + st.sidebar.title("Navigation") + selection = st.sidebar.radio("Go to", list(PAGES.keys())) + + page = PAGES[selection] + with st.spinner(f"Loading {selection} ..."): + ast.shared.components.write_page(page) + st.sidebar.title("About") + st.sidebar.info( + """ + This app is an end-to-end solution that is capable of transcribing a speech to text in the Amharic language. + """ + ) + +if __name__ == "__main__": + main() \ No newline at end of file diff --git a/char_to_int.pkl b/char_to_int.pkl new file mode 100644 index 0000000..cd643c2 Binary files /dev/null and b/char_to_int.pkl differ diff --git a/int_to_char.pkl b/int_to_char.pkl new file mode 100644 index 0000000..3904672 Binary files /dev/null and b/int_to_char.pkl differ diff --git a/models/amharic_stt_mfcc.h5 b/models/amharic_stt_mfcc.h5 new file mode 100644 index 0000000..a54e4ca Binary files /dev/null and b/models/amharic_stt_mfcc.h5 differ diff --git a/models/encoder.pkl b/models/encoder.pkl new file mode 100644 index 0000000..3787480 Binary files /dev/null and b/models/encoder.pkl differ diff --git a/models/new_model_v1_2000.h5 b/models/new_model_v1_2000.h5 new file mode 100644 index 0000000..59e6dab Binary files /dev/null and b/models/new_model_v1_2000.h5 differ diff --git a/models/new_model_v1_6000.h5 b/models/new_model_v1_6000.h5 new file mode 100644 index 0000000..4b2f3f8 Binary files /dev/null and b/models/new_model_v1_6000.h5 differ diff --git a/notebooks/.DS_Store b/notebooks/.DS_Store index 5478ff9..afbcdeb 100644 Binary files a/notebooks/.DS_Store and b/notebooks/.DS_Store differ diff --git a/notebooks/.ipynb_checkpoints/Amharic_Speech_To_Text-checkpoint.ipynb b/notebooks/.ipynb_checkpoints/Amharic_Speech_To_Text-checkpoint.ipynb new file mode 100644 index 0000000..f4adb87 --- /dev/null +++ b/notebooks/.ipynb_checkpoints/Amharic_Speech_To_Text-checkpoint.ipynb @@ -0,0 +1,1229 @@ +{ + "cells": [ + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## **Imports**" + ] + }, + { + "cell_type": "code", + "execution_count": 1, + "metadata": {}, + "outputs": [ + { + "name": "stderr", + "output_type": "stream", + "text": [ + "\n", + "Bad key \"text.kerning_factor\" on line 4 in\n", + "C:\\Users\\HP\\Anaconda3\\lib\\site-packages\\matplotlib\\mpl-data\\stylelib\\_classic_test_patch.mplstyle.\n", + "You probably need to get an updated matplotlibrc file from\n", + "http://github.com/matplotlib/matplotlib/blob/master/matplotlibrc.template\n", + "or from the matplotlib source distribution\n" + ] + } + ], + "source": [ + "# setting path\n", + "\n", + "import sys\n", + "sys.path.append('../scripts')\n", + "from dataset_loader import load_audio_files, load_transcripts, load_spectrograms_with_transcripts, load_spectrograms_with_transcripts_in_batches\n", + "from resize_and_augment import resize_audios_mono, augment_audio, equalize_transcript_dimension\n", + "from FeatureExtraction import FeatureExtraction\n", + "from transcript_encoder import fit_label_encoder, encode_transcripts, decode_predicted\n", + "from models import model_1\n", + "sys.path.append('../notebooks')" + ] + }, + { + "cell_type": "code", + "execution_count": 2, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "9" + ] + }, + "execution_count": 2, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "import librosa #for audio processing\n", + "import librosa.display\n", + "import IPython.display as ipd\n", + "import matplotlib.pyplot as plt\n", + "import numpy as np\n", + "import warnings\n", + "import os\n", + "import mlflow\n", + "import mlflow.keras\n", + "import logging\n", + "len(os.listdir('../data/train/wav/'))" + ] + }, + { + "cell_type": "code", + "execution_count": 3, + "metadata": {}, + "outputs": [], + "source": [ + "sample_rate = 22050" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## **Load Audio Files**" + ] + }, + { + "cell_type": "code", + "execution_count": 4, + "metadata": {}, + "outputs": [], + "source": [ + "audio_files, maximum_length = load_audio_files('../data/train/wav/', sample_rate, True)\n", + "logging.info('loaded audio files')" + ] + }, + { + "cell_type": "code", + "execution_count": 5, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "The longest audio is 9.088027210884354 seconds long\n" + ] + } + ], + "source": [ + "print(\"The longest audio is\",maximum_length/sample_rate, 'seconds long')" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## **Load Transcripts**" + ] + }, + { + "cell_type": "code", + "execution_count": 6, + "metadata": {}, + "outputs": [], + "source": [ + "transcripts = load_transcripts(\"../data/train/trsTrain.txt\")\n", + "logging.info('loaded transcripts')" + ] + }, + { + "cell_type": "code", + "execution_count": 7, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "200391" + ] + }, + "execution_count": 7, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "maximum_length" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "**Sample audio along with transcript**" + ] + }, + { + "cell_type": "code", + "execution_count": 8, + "metadata": {}, + "outputs": [], + "source": [ + "demo_audio = list(audio_files.keys())[0]" + ] + }, + { + "cell_type": "code", + "execution_count": 9, + "metadata": {}, + "outputs": [ + { + "data": { + "text/html": [ + "\n", + " \n", + " " + ], + "text/plain": [ + "" + ] + }, + "execution_count": 9, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "ipd.Audio(audio_files[demo_audio], rate=sample_rate)" + ] + }, + { + "cell_type": "code", + "execution_count": 10, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "" + ] + }, + "execution_count": 10, + "metadata": {}, + "output_type": "execute_result" + }, + { + "data": { + "image/png": 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d9srPeGFq1d42L3nxhzWBIFfrIvPur5twKEyNNKOYSJrYJhwrFz+jFSkOHy/FZP8F2omk/kj9EWaG82sz1uGntcapxXrH4pVvzzM10UZJznY7V6xI52ZeOXduKyhG28emYu3uItz36RJMmJtvextidWjsP3ICN7y/AKX+WYmhvb/Ho8h1NYPBVhwYN3UNPl0Qflae4uEvlmKPf4hIsy5HyNG9LaS2V96W6Hpz7v1kcdg7NrsWwdW6qPy+0RcUWv0Qqz98A/9WWYf36yU78KFOd7tb/ucPQg8fL6vSm2M0UUG93JIW71wSqzKTdD1hnrfeJ6DyWFe/tv+nke+2eGshnpuyGg9/uTTi57LjwvVTID1Af2clZeV4+ce12F6oH2T3HVd1wk+sLNh8AOv3RNZr9OqM9XhztvHyaA/9T/s9mrvpAFbvOoyVBr3QAHD6Sz8B8PZEAgA4GBL4/7TWWyWZ5m48YKkUTbOsGijzDyeHloJwojahGoMtl8zbdMCx7tOJedsxZ71+L1TrR6fi36pu/WjXS1Qox+p3y3Zh5mr3Jp3u8/fiWH11X5upnYuR5MEpev8zmOG2Q6OXSfkTlEDUTlaG7l6bsR69QmY7mZ0YUu5ynZxo/bJuX2DYKi+/oMqM3Iv/9TsA4IeV2ouLG9mwtwj//mkDZugsTG7GaeNnYtyUVSjx3+GXlFYgd8wUfDQvX+P5juCNWRuw5YB+Eebjpaq/L0ZR/K5Dx5A7Zgouf2sebvkwz7HnMSos++yU1Rj5+hxT+3nYRLkdN70VxahKOMrlz8qhMX/TAYz9pnJCxtrd1pauapZdGWwpN9fKsKJdxYL1MNhyyei35+HLxTvw6vS1juxfAthqcCKcttJ6roKZ5zRLOa6HvvxTlZ8dLy0PuluZtmIXVu00/6FSf2hKysqxbLu5khR61fvd7upXqM8FCyKcafmrQRAORJY/sTC/0PR7n7elAAdUdXz2HD6OLiG5ZKGUIRu9e4KHJi7FDVGu+ekk5X37WJVIPmP1Xs1h3EgNe+UX/G3aWmyIonzL8dIKLMyv7NUu8gfBY7+pmgto9jCJJA8sGv1fqFzJQt1Gu29sjW7ASsIMRz38ReQ9l06bErJ25ORlwbXW7HwVlRUMQt+b/UdKggIqtc8Wbguq9agcX3qlU0KVllcEerSUhHllgepyKdF33Az84MC1EWCw5ap3ftmE12Yad1dHY/BLs/UvyqoD3MwJ0UwBuA/nbsEbM9cbbpM7Zgr2HykJ9LRodaMfDpmlc8dHizHqzTk4cKRqLVyt4Ujlz/n3TxsxYe4WXPDP8At0A/oXEPWH2wtCT05BPQhRimRFgEguZNsLfYFtseokqTVrtuDoCVzk7/HR69matmKXauiLAO/US1POG2/9sgmHjpW6khC+etdhXP7WXFv3GU0vyMS84F7p3DFTAr3xblNyX5VaZFqMZkV/tXh7oKconHNf/xUAsKWgOKh3e/GWQt1zbujLrnz/+izj646ivELidv9EL6VnS8nVWrylEHuLSgxHhaLBYCtBKRfAvTofYnUdHq2LpZIgqhzb780xNwPnQ4Ocmdn+fe7XCJrCKS2X6PXcDMNhsF2HjqGkrDzoRPjcFF/ZCr0cihU7Dnm6V0RNCSwPhFR4vum/+qUDAr9r8towbupqzcfXGqyjZyXWUoIrJSdOadb6PUWas2aTVQ0v0FlmpboV/96470jYz5Be4nM4EsCXESzjs0ln6a3Zqhyf+z9bgmGv/BJRuyKhJHmf89qvQT12pn43zDFltK6k0c/0gqo+Lua3WXX+P+egTKeb+cGJS3WvOXqGvvwznvimcgJSskG3oV6ur9nk9rIKGchJVoItpQj0G7M2+Lfx/W3bCooxK4ph+VAMtlyQH4PKtcq5wkz1ai1KV+pK//Cd1WFH5Rq5raA4cFArdbk2R5EUGjpT68O5+YGv+78wCy//uE4zsFqmczd23htz4qZX5KUffUPOoaUVtHK0Qj36VXSFJ/cW6VfXLyqpmqSvZ5HO5AutEiehJ1D10lBqWrNODx8vNT204JSi46XYV1Ri63AhADzw+VLdGcOK6yK8gSg4WoLpq8JfYEKDkSEv/xy2R0M5l3y1OLJzUiK48yNvlc/p1aqupe1nrfHfhBvcvUXS6Wc2VaNqz5a1J1PnJyszZENHBk6U+R5/Y9Z63PSBfXl/DLZccMbff3L+SaK821dGbJRyD3sOW7tbUe5ABr04Gy/+sAa5Y6YEEhPv/Hgx3vnVeFacnk9CZmX+GHJhmLF6D96cXTWp82hJGVbsOGRYoiDc3Ww0xWHtEM1Qg9aCxlYYvTb3fboEV71jrR4UAJz/xq/4zd9TOXFh1RIfHZ+YFvh5cFtkyPdV993v+Zm4bYJzCdJmdH3qR/QZN8O2panUol1aS8+2Av3Px+KthYH8Oq1SDrvCLHel9Hg8ODE2OUvRVEN3KtXsqMENwB0xDMS2HihGh7HfB9beDKVVsFhNKzgKTf+wQq80yNXvzguaJR7aWuV75ddPf3E2njKoN6gubKrsN3QlAaUth4/ZW7OPwZaL1kY4NdmMaGedVUgZUd2RIxo9FG/97Aus1NPy1XkLVmo0hUvw3qTTa/bclNU47405QUNuoflsEr6A6nedemJ25kbFGydG6pbvOByoIK13Zxt6bMxesxetH50a3DaNxhWfKDecKRfvmtTJwOy1ey1VIV+0pTBQMiQSy7cfCuTWaB0P0SxcbYfQxeiLXe7Z1GLU+zdthTOJ2VrW7SlCSVkFCiO8gXxX42a521M/AogsX1D9sqg/z79t8JXSUIQLgrcUFOO/v+dj8rKdmq91uUawFdoDPmf9fqzZfbjKaM7C/AJ8rropvOqdeYY9/qEYbHmAE7PdtIp8hrr8rbk4VFyqeeIslxKvTre+LIV6EWSzw6WnjZ8VfNA6mIOzZncRHvj8DwCokjQrpcR7czbrLo/S74WZzjUsDLNJ6NEsoaTQShC1mgS/fPsh5I6ZYjqQDj2JKkPBK0NmoSqz7ZQT6dGSMpTrtE0ZXrz+vQV4XicXLV4JAdz4/kJ09V/gzHhm8ir8JYpSA0a5NADQoHa66X050dunlM5Q0woK7LS36Lilz4ZXirsq7VgXwYSYsCKItoyC0Acn/qHatW/nC/3LCSnnjdD34J5PlqDNY1OrTKoqVw0jKsFWaKrNviMlmnmwL05bg0e+9H1+XpuxHr9vPGCp6jyDLQ94LMp8mkgt2FyAjfu1P2xfLd6Bt8IUwDSytaDY0nBp33EzMXGhb4jQTA+S2RkvWr5esgOTl1UNRtfsLsLrs5ybHRoNs7l3kebqqGktEWP1GrHGX/9GveqAUW5Z6OwupU7R10uCk7Vf+sGXt9bmsak4dqIcnf/6g+46gEqbf163D1OWudvrYrdIeg+iHRlTz0jWCjD0SqdoueJte2cH6tVqUybIOOG7pTvRd9xM3PD+QnR76gdTK314J9iKfh95+QWan70VO6Jbw/WzhcGpIuqXTFlR5LL/m4tvluzA/iJfz9zP6/Zp3mie/0ZwvbMy1c7KpUTR8dKgkiyKnQcrb/4nLtyGCXPzA5MsXp+5Huv8o1K7LIzKMNiKMXWXqGKKi93vxx3qao+kkvfDXy7H8dJyDH5ptuF2L05bgzaPTY1qeQWjKuvRKDx6AlOXR7aGWEWF1LyIlZSVR9UjEYncMVOCpnhbXfqocrHfyt8zes0zUpMBhF9A+YTqzvTeTxebbs/OQ8cwdflOx5fkiBlV5KRXlFg5lnYfOo7FWwujykMqLa/AO79WzkjWepf0ZiRqWbL1IIpPlGGGKudy8rLK90dKGVgFI5TWxAe7Jx0tzC/Ee3M244tFvou71hJKyrJLP6/bh8PHyzAuZKmoKzTKTZitGL9qZ/gq9EaklNhWUBzIo6qa5+j7vob/c2fVZwu34dL/m4tf11cNcP7yv+Bz1fHSchQeNR6uVG7KpJSY4S+IrbRx/d4j+Hzh1iq9Tfd//kdg0kz+gWLNG82dh4KPofLyytehokKGnTnZtmEtPPzlMjzxbWUe2CvT1yHVv4i1lbp2ng22pAS+WbIdUkocKi4NrDclpcTzU1djr/+DeLD4RGCG0x0fLcJbP2/EtoJiLNpSiNwxUwLj+JOX7sTnC7dCSok56/djy4GjQQegcjAUHS8N6uJWPsRSShw7UY7Vuw7jro8X40RZBQ4Vl2LTviP4df0+3D4hD9sKirHj4DGUlVdg5c5DeH7Kajw7eRX2FZVg0ZYC/Lhyty09D8avm7WL4lXvzsd8hxfgtKLjE9PCbqMsamtmWz2h+R1WfLFom2bQDACvzVyPuz5eErhorNl9GNsKirH/SAny8guwef9R3PzBQizeWogvF21H7pgpuOCfc1BRIdH3+Rm4+5PKdfMu+7/fsWrnYdd6Zc7/Z+VdoeXi7f7DUD3EN27KKt3NlUTdcMGWevbUDAurFEgJ3PXxEnR8YhqeU7WjrLwCZeUVgec9dKwUq3Yexo6DvjIiJWXl+M1/Ifhp7V5s3n8UpeUVkFLiaEkZflq7F+v2FAVyp6SUuPOjRY7XTVLfeevlpnX+6w8oOHoC/V6YGTTEplWvLpzQ04rWeWbVrqLAa2VGpyd/wC0f5uE/v25CRYXEPZ8swT9nbUDB0RO4bcIinPr8TBw74StwnDtmCp7+biV2HjyGk5+chlPHzcCiLYWYunwXvlq8PSjx2S7PTF6FP/sDhyMRLHA+f3NBoKK9WbljpmDuxgM49/VfMfL1OXhz9nrkjpmCd37ZCCklBoyfhZGv/wopJb5e4jt/FB49gddmrMOgv83CxIVbUVZegdaPTsWgF2fjyW9WYPZaX57jV4t919Pf1u8PBEnpKZGFAAX+66XWLOLQ0jSPfb0cPZ6tWtYl1E9r9wZN5FEfYo98uTwwEzIa5RUSufVrIlkIlFXIsCk86vNRZkZK4Gvlb1yzuyjohjK5dr3GevsSsVpx26qTu3WXx84dF/TYRT1y0LhORmBdsUaZ6YHI9OIeOfhqifX6MInmtdHd8afP/gi/IUXkweEn4ZXp65AkgE0vjAz62fo9RRj+avR1hDo2yUTt9JSo16i0w4LHhqJRnQxMX7UHt1pY/uTpCzrjr5NW4rr+rfDMqC4A9IskAsDlvZtjYt52jL+4K0b3bam7bccmmYZ1jAAgf/xI5I6ZguZ1a2DOI0NMX+xuH9wmqqHz1GSB0vLYn0/TU5JMzTbt1jwLy7Yfwg2n5eLhER3Q6Unjyv1qMx86HUNf/hkA8P2fBuGFqavxi0PFH3OyawSGnHu1qqtbLiRWzurUGI+PPDmwnmEkJt7eHxmpSaYLLIfz1Pmd8NR3+jcvinO6NEHt9BTd5b2yaqRGnTOcP34k3puzGc9MrmzP8qfOQmZGKgBfbuyCzQXIHx98vtT6XE6+dyDO8w/9bRh3Dto9/n1UbauTkaIZECYJoGtOFi7onoNnJ+u/ji3q1sA2//qfmekpgVUVuuTUwYodhwOf+TYNa2HTvqPY9cH9KNm1XrMPOUXrQS8o0zhpheZvqLsAGWj5eKUScaJ6xT9poEL61gSsmVb5EbIj0AKMiyLGWt/nZ2Lj8+da/j1lcsWHc7egS04WvltqPLSqzE4d89VytG5QS3c7K6+NlMCXFurMRRNoAXAl0ALMl/VQas1JKS3NAAaABz+vvIF74PM/HD1G1bl9bgdagK+8zMMjOka1D7sr2JsJtADg+zAzHO3obFm67WBQoAUAhUdL0fWpHzHnkTM1h2D1nKfKsbLj06Q3I1XCV9h76fZDqJGa7F/Gp+ozqh8rUuUFbvPnJyqfeb1Z8GqeHUaMdLaKElIq+QleWbaCEo/SM5A7ZgpmrdmDDo0zXW6RM/41e4Plk/JB1d3yw18sC1uyQ+2KMAU7w1HaerD4BB76n3fXoXPLB3O3WK5BpV5xwks3A7E6vw975ecYPZNztCaT2jH6OurNqr11Sq7YwL/NDpQ4uvTfVWeLGrFjMkG4yTO+r6VuPqPejcyhCGpweTbYUkeU4T5QyUJV3Ez5X1Z+H2bGsubPhc7XXhfrhV+ruxH/8PVm3fTfPFN108wcV3qFBmMl9NlnrNnrZDUO2ymffaMCklqqFExUPaD3lsTrpy3agPpSvb4AACAASURBVNYNoe+BgKNVYuKG2WOwQoa/FtpFa9JX3pZClJVX4MeVuwM510bC5W+aYWYPJ8ordGdbHy8tR1pyUpXXWCvXTQCGXYWeHUZUtzncCxau9z7ce6b1c6nzNZGa1bt8M8eVE8m+VggRfOe3dNtBy6Uf4lHon6j+m/XekmrwsjhOCAQSlo2E/pivvY/R65Akgl+3Kq+hQx9svYkS8zcX4LYJ5irl21HBPSXJ3HGlF4SWlFYgLSUJofdtWr1u4V5Jz/ZsUWSMkv2IzNA6N5lZL88reBGOL1K6f4ORqMK9rE696npr0Vp5n//02ZKo2xGuEG845TpDjJH0ujHYIqKwvqzGiwcTJapYF1ktt1BDxo4F3M0GW8a9g1X3Ecm9AYMtilu10z07Ck4uiqaGGlF1EusORb0Zu06lkmkFSpoMXge7CiEz2KK45dUaceSub1gGhsiUaJY9i4ReOoJTrTAbxBmtkGHXEDeDLYpbDLWIvCXaHBmKnWQhbJnxZ4XZNV5tY8PhaNchzWCL4hZ7tkiLmYXMyRmMteJHarLgDasJdsWjDLYosKhmvOGJgrRs2OudopvVjVtV9Mm6pOoQGXvocGSwRRBxWpqRHVukhYV9icKrDp8Ss7MtY3EpYbBF8FT4b0Gspy1TfIh0qS+iaqUaRFteKt/GYIviFmMt0rJq12G3m0DkefE6omGF0SzDkA0dx2CL4rRfi8EWERHp89I1gsEWxW1Sa7mXPklERHGkOszm9tKfyGCLiIiomvFSPpNTzA4jMkGeiIiIHJD40RZ7toiIiMg1HopDHOOloVIGW0RERNVMdVhpwUtDpQy2iIiIKOF4KNZisEVERETkJAZbRERERA5isEVERETkIAZbRERERA5isEVERETkIAZbRERERA5isEVERETkIFuCLSHECCHEWiHEBiHEGI2fpwshPvf/fL4QIteO5yUiIiLyuqiDLSFEMoA3AZwDoBOAK4UQnUI2uxlAoZSyHYBXAfwt2uclIiIiigd29Gz1BbBBSrlJSnkCwGcARoVsMwrAB/6vvwAwVAghbHhuIiIiIk+zI9jKAbBN9f12/2Oa20gpywAcAlDfhucmIiIi8jQ7gi2tHqrQJYnMbAMhxG1CiDwhRF7x4UIbmkZERETkLjuCre0AWqi+bw5gp942QogUAFkACkJ3JKV8W0rZW0rZu2adujY0jYiIiMhddgRbCwG0F0K0FkKkARgNYFLINpMAXO//+lIAs6SUXlqQm4iIiMgRKdHuQEpZJoS4B8APAJIBvCelXCmEeAZAnpRyEoD/AJgghNgAX4/W6Gifl4iIiCgeRB1sAYCUciqAqSGPPan6+jiAy+x4LiIiIqJ4wgryRERERA5isEVERETkIAZbRERERA5isEVERETkIAZbRERERA5isEVERETkIAZbRERERA5isEVERETkIAZbRERElHCShNstqMRgi4iIqJrJSE38y78Q3om2Ev/VJiIioiAC3glEnOKlv5DBFhERUTXjoU4fx3jpb2SwRUREVM14KRBxitlhxFi8FAy2CKnJ8fmpS/ZS9iMRURzhMGJsMdiiuP3QMdYiIiI9Xuq9Y7BFcctDnyPykO4tst1uApHnSUi3m+C4JLPRVgwuJgy2KG55aVoveUfiX0KIoierwQfFS5cIBluEE+UVbjchIl76IJGHVIerCFGUqsPHJMlklxUT5IkMmO4ipmqlc06W202otmqkJrvdBDKpojpEWzZcIuzKDWawRXGLoRZp4XHhnmOl5W43gUwqLa/gJCMTKmyKSRlsUfziiYKIKCIVMvblc8ac0zGmz+elBE4GW0SUUO48o63bTSCKC7FOxWjbsHZMn6/CZLRlNNnKrqFxBlsUt46WcMiCqmqaVcPtJhDFhVgHWykx7kmrsGHuV7JNURKDrQTTuVkdt5tACeiBYSe53QQislms5xhZGba8sm+LqJ/P7CQAEfJ/8D4qv1aaH8miK3EVbDFFJ7yLezZ3uwkU57TOhx2aZMa+IRHieSK+JInY93iQj1PB1shuTTUfr52RYnoffz6rQ9TtKLOY3R66dUqSCArYlN0lJ1kPnTwbbCndm0mi8uSv97KlJPkWnAkXbQoR+Yk4mmOSp5HE9crlp1ja3sxFxe0LT+j5qXuL7LiqaeZUW7V2q/UY4wZrKqT1i6KaXcM8XhLuEAp3jJs9Bp1aqq2rTvmVHi2yMfvPZyB//Miw+6iVbj4w01Nu4rgyihvSU5JQVi5NvZ7hNvHsYZrifwUqZPipl2UVvoUHysNsJ2XkkxOimdQQywkRsjrUTvGQi3s2R7829fDHk8ORaeKuzcxFJZoLjxP+NLS9202IiJn3wwqtd0XrMY+9fZpmPHi6202wTZzWZDakdwgFOh78G+hd4M0eg07dmAxu3xAAUEf1GbxlUGsIIdC6QS1T+7CjbXpBkvrh1JQk3efKSE1GWYWs8npqFQKXgGGmvWeDrbREvF2hhKLcnX12W39k10xD0fEyl1tkvz65dXFGh4aWE2lPP6lh4OvJ9w7Es6M6G27fpmHlCXjWQ9EFAsr5rk5GKn58YHBU+0pE1/dvZfmm7MwOle/nKdVw7cnZfz4j6n3kZEc/cSP0oh9tXG9HrLXgsaFVHqtbKxXtG9XGwrHD0LOl73gZO7JT2H1lpFZe9+1I3tfLEVN2nZachIoK/R6w4PZUPt6gdrrltng2okn1B1v1aqUFHht/SVf85D/oT2pcG9f1bxX42YSb++ruq0mdjMDXSsQNAB0aZ6Jv63qB728b3Cbw9fWqfQ9s1yCCv8CaWmn2TC/t2IQJ8k765u4BAICTm1Z9ndc+N8L0CbVJnQzdO7xXLj8Fz11oHJzEyrvX9YEQ1gcbzurcGADwxHmd0CUnC9f2zzXcvlfLugCAd67rjTYG08NPbmo+d0wI4KTG2tv3zq2LM05qiLaqIO/jW04N2mbYyY0CJ+sr+hgn63ZqWgfjLuyCe85sZ7p9djn/lGamtjuluW9oJ6tGquFrrOWVy7sHvv7kllNtr5fUv019AL5p9oNVgfqT5wVfoOvWTLX1ec145fJTkBzlhX/6A4Pxvzv629Qi4AuT+zq7c2M8e2GXwPddcuqgUWZloBDt+rKZ6SloVCcDX991WtDjWTVSMf3B05GekowUkx0njTLTg4JaO4KtVJ3nFgAu7N4Mf7/8FJwor9DtCVTnZtVKq+yla17Xd55vUNsXn9x5etuw5357+9ltVCMtGV/eP0gzeHj72l44vUNDpKck44nzOuHQsVI0qJ2Od6/rjdYNayEnuwYOFpdizFfL8H/X9EJGajKWbC2ElBI9W9XDkZIy1EhN1ox6Hzv35MDXT4/qgvIKGbRdSVk5pi3fjVE9cgAAxSfKcPhYGZZuP4izOjUOFIrbe/g4/th2EPVqpaFXq7rYV1SCCgl8Mn8LXp+1ocrzrnxmBHLHTIn6dRvY3npg+P4NfXDjfxdG/dx2OLNDQ8xeu8/x57mwezN888dOy7/XvUU2vv/ToKAAXpGekoxr+rXC36atCfR6KcdakgAKjp5AvVppeP+3fAw9uRH2HC7B5W/NxXMXdsE1/Vrh3k8WY2D7BoFJDukpybiwRw4WbSnE6LfnRfcHRyjLf3Gzet5TTnLqGjVX9m2JTxds1dxeObEO6djIcL+Z6dFdbM/u3BhX9m2JMzpoP0/++JEoK69AkhBIShKQUuJ4aQVqpCXj3iHt0LhORtAJfPeh46idkRJ0PunTuh5OP6mhLZ9nM8aOPBnfLa16LF9wSlO8fHl3tH/8ewBAkr99dw9pZ7mYZc30yvexVnoK+uTWq7LNoPYN8OoV3dH7uRmW9v3lnaehZ8tstH50Kh49pyOuPLUlZq7egzs+Wozr+rfChHlbkJmRgpsGtMbgkxqi57PTcf/Q9rh1cBvsP1KCouNlKKuQuPDN3yw9r1kX92yOXYeORfS7y546C49/tRztdYL+UC3q1sBXdw1An3G+1/Cjm0/FNf+Zj2/uHoDuLbLx10krkF0jDb1z62HNsyNw/XsL8OHNfbF4SyE27y9Gt+ZZ6JKTFTj2WtariR4tstGhSSY+vbUf6tVKw+b9RzF91W48P3VN1EN1r13pC8J7+G+WAKBpVgZqqgKTfm3qY3tBcdh9fXHHaahfqzIQtCP3sfhEcHmgEZ2bYOXOQ9hx8Bi6t8hGq3o1DX8/6HOi+lIJ+lvWq4m8scMBAI+c0xFJT+1cq7cvzwZbgH4vzVmdmwS+Tk1OCnTpDevUOPB4k6xk/PfGyt4u9cFQ20LiXehJKT0lORBoAUDNtBTUTEtBkyxfm5Rku0Z1MoLa2ch/cb6sdwvNYMstX955GrJduFvU89a1vXHS2O8Nt/nwpr647r0FyB8/MuILWr1a1ruBFVq9WoqbB7bGmR0r78zVx1p9/3F608DWAIBW9WsFJYq+cVXPoH1d1tvXm6J1YYuFZU+dFfg60pOy+sZyUPsGusGWkgMR7mkW5BcEvr5tcBu8/csm3W3Vbc6qkYrJ9w5EizAnVwBBd+JCCNTw9zo3r1v1d5tkVQ261UOoTmmWnYGdB48DABrqDGm8NroHhBBY99w5KD5RFrihSk+x3ose2sugdTzkZNewNLyy6flzsaWgONDDu+CxoWiYmQ4hBEZ0aRr4bIQO4ak/M0oS9aqdh00/rxkt69XEv6/pGfi762RYP0c+c0Fn1MlIDfpcC2G8APSvjwwBACwaOwwpSUnIqpka9Pc+fUFlL1VGajI+v93Xw9W/bQP0V9XyzR8/EsdLy5GanITkJIEf7q8cTm/doBZa+j8HB4tLLf9dgO+maNaavcjUeF1SQjLOHxx+Eh4cHr50TMv6NYOGt5Vet7TkJEx/cDDW7i7CbRMWRdReRXKSwLbCY4Gvw1371O1Rp4ko5/IuIRMBZEnxEb19eXYYMVFpnexvOC039g3xS9KZoZmZkRJVjsH9w6wlVdevlYbJ9w5EWkqSZg6A2uCTGpqazWJEb2pytNJSkmwfyk1OEnj/xj627jOc/PEjgy4wVocbAnVrVL83yKDX9USZL9hKCnM7O6Bt/cDXY0aYH8qqnZ5iKtCKR3qvWeBilZKE7Jpphhf5cFKTk/CMKu9O6xlzTSY+A74aSklJwcnSjepkRDys1b6xvZXJG9dJR+dmWYEbK62ZcTMe9AUwT57XCbcOah1IMVBcp3Feb2PyNapfOz3QqxypDJ3RG5/ouo06NsnEorHDNG8E3762t+X9Kak6Qgj85ezgkg8t69dEq/q1cFbnJqjvTyvq0TIbvz58Jp7zD5GO6t5M87ox7OTGQd+rX4/kpCQ01hihAHyzEAEg/0AxJt0zAJPuqXxvP721H3b4A7Z2jcwfdwy2PGDsyJPDb+SAcRd1Qedm2lN0z+rUJKogsFZaCjY+f66pbTs2ycRvY4ZUuUtwyouXdkOvVnWrPN6paR3X3otwztQZ9gqlvoON1LxHq560rJ6a+/lzcM7vVplPpHUXrJAhqb4rnz4bQNWld5R8nvzxI5GUJJA/fiRSw9R8MXtnHU8iCZyinXSkDoS0gqLGdcz3ar1wcbeo2hJKLzfHzjypUO0aZSJ//EjcNLA1Hh/ZCd1NTByIdcV2PXYM0dXX6cWsXztN83GzOoQMuWbXqDxvKMHTS5d2Q4t6NQM9rHVrpgVGjxRNszLw6hXBpXmCgy1fQPrCxV2rtKGjqq5gt+bZ6NY8G8P9z92/bX3cOtg3OqHOKQ+HwZYHmE0gtMJM0HD1qa2QlqL93EnCN1XXKvVUX7N5IV/ddRoy1OtPOXg+GtKxES73D8/ljR1W5efX9m+FOY+cqfm7Cx437nHzAjuKj2oNjVntcWhRrybyx48MDMGFE7qshtKTEDpENqBdg0Cid6BtOgeM8vh9Q9vjkl6JVez3aEkZVjx9NjaZvKEBgH9e3SOqYLw8TI0FpXfSLYufGF7lsUiH4J2qoOOdYMvXjp4tq950mmFYnDSC186oR/v1K3uodu3bebtGvvOc3vs048HTMffRoVVu8NQ1DJXXoFNIWkiPFtl49/qqIwmPjTwZX97pmwgwpGNjvHhJtyo9Z0YYbLmoo4NVuevUiK4LOkmIiLr00zUW7XxtdHfUyUgJ6in7+2WVdxzqZMpw7h1iPNtLL19m3EVdkDd2GN5QfXC18kvSU5I1c3OstjPRGB0JDTPTI6ppdd+QdnjvBt+Qg7r0Q+A5BdAxZPZhl5wsfHvPwCrbhTqleRYGn+T8LGIjmRkpaKoRuNrh8PEy1E5PCTvsqtYoMyOqYHxIx8a42J+vqvW0ZntfnRLay9CinvfWyDR6v167orvuz+zWq1VdXNIzR/dmO1xv8U0Dqt6IK6kdkcSpei/L66O7B32GQoOr0Oe6tFcOnruwi+7wnjqfTOkMyAi5ZuU2qIWGmekYocq5Bny5buoRkcv7tKjyu0YYbLlg/bhzHH+OaO+flJPCVae2BOCbBm+Fcgey8flzMap7DpY9dXbgovj5bf2q9E6YFXoX8uezgoeHBrVvoFnTKUkINKidbliVOFxsaWVihRPOiyLP7AKT5QH0GN2RP3dhF3x086m6P9fz4Fkd0KaB76Q4vFPVO8TNL4xE56bhjxOtpn17z0A8d2HV4YFYWv7U2Zj95zOCykvYJZpjwYjR5I+W9WviFX9AoNWbGDqMU+Xn/pIDv48ZEkULzXOqOno0jHK21BOvnFa3Vhpevrw79h8p0fx5uKVy9IZtI6V3frmge07QTb9eiQZlk79f1h3X9GulvRFChxGVYCv4b1F6v+wO1hlsucDuA1WLcoDq5V2FHmChbhrg+71Mf4DR1kIioJr64B7dxxe4ZdVMNbz7MTpJtqwf3OuknmW66flzcfPA1kEzDZW7ojM6aPd4LXliOP59dU/Nn3mNUiPuvpDevSt6h1+wVe/vNyu3gX5yud7dsRa9JHm9C7V6XbLQmksKrwzNaMlITUbTLHtP2p/ccipeDrNMVGjdI7PSUpJwy8Dw6QOhL/kGEzeQ53b1BYjNbCju6TSnDqlw71usbdirO3lOU7jSLEBkn8f2quuL0a+H5nZaHe9NUdXNUtoZ2julpPXcM6Q9ZkZZYFmNwVaC05ttEZqEGEqpC6McyvcNCT+7MC0lCc9fpN+b0KFJJvq3qa87TGekS04d5I8fWSWhX/1ZS0ryDX2qP5AP+e/Q9C54dWul4ZyuzvQS2E35u0KHam9VFePV/V2T56R/6AxlGL1nkVyXQocccrJraM4wVQ+76A1teDnYckLtjJSIyjeYIeAr+GqVXt7ppapcubEjT8ZyVTkRpymHxZInhuPuM9sab2yR0fnTqHdQa9ipb+t6Uc+utpsQ+vmfy586Szcf98cHBqNhprmJEsqEjRVPn42HVTOLDdcz1BlGNDtzPiVJ4H7/8mOhw4jKuS/Nf57JqpGKthaL/xphsOWi8Zd0c2y2jICvp0e34rbFC5SZRUFH92kRGA7Su7h/elu/oOE4rcrcdWumBnJDAN/yLRNuMj9MpXxW7zi9LS7pmYMlGomzWvRekttNBDOxpu6ZtHNpq7oWZtcooumpDVcRPKtGKpY+6btAq6s5qz04/KTACdSL3IgFI83vtrutymf99sFtkJKcZDgj1Q5aM+Hq1krDX862t+J9hcHdS7ilkN6/ITj5euLtzs2YtOqxcytfJ73JFEbvod6KDVp+f9Q3nBxaYPz0Dg11S92EvrLKS62VQ6YlNTkpUJJDGS5Uyjxk10zFFX1a4NJe4UcKIsFgyyV5Y4ehe4tsRwtW6iVjntI8C3efYe+dHmCth0P5kPztkqpTwFOSkwK5IQDQpmFt3SCgSrcyKk92QviGU80GEP1a19d83Gq1baeoz+HdmldOM9d6DfQoOXh26t+mvukWXNqrOUaqehKza6aFvatX6g2l6LwPNw1sjfs9XNpBed/GXVRZkHJ4p8aGdcesWv3MCHx112m4uGfkeT+D2zcIGpJuUDsdN56Wi6n3DaqyreUAO0YfoV/+UjmTuG7N6EoQGDEKtpSlXPScaWIozi2tGwT35DwSUsvOzrexns77k56SrDvZ4i9nd8Db1/YKfK+c681OFElJFoHzuZIsrwRbyUkCf7ukG7pGmE8cDoMtl0SykKVZ793Q27Bo57f3DAyqbm934vcbV3YP5Gc5Teuc194/LdhqjDS6b2Wb1Xf4Ds0Cj8ojI/QTWLXW8lT+hj4RDBGFY2VG3KjuOXgzwhw5M0Gv3nqTXtCgdjrO7er73F2skQz9x5O+Htgr+1q/s66RloyeLesG0gYiKV3wj9E9MLpvy6BhoL9e0BmdmlUdFjupcW18cUd/9Gujf7PYrXlW5Y1PjKKtWukpyB8/EnMfHYL/OlgI2KikyQPDTwq8l+F8ems/u5rkCCfXBVbOsVaOjGbZNYKuXQPaNQha3zicvPzCQDqC0lOu5DcbDl/agMFWHPjm7gG4sq/54GVIx8aBcWgzh09ocrJWkTcrzj8lJ+rqx9FQLg5WT/DqAGvNsyMCpTnuOL2toyfuSPRq5TvBNK9bA9khd4hGr/1FPYzrTUV6SXT6UtqlWR3NQrShLorhjC6rBCrLh2jlCWbXTMM3dw/AOJdnUSrHlhEhBHrn1jPMl5sUUqIjlppmVf1cKMINlX5+W7+ghbe1vH9DX83HX7q0Gzo2qaP73Aql4HNairu95qH3L6GtaZodfG243oHVTqIZum7fONPSMOxJjWsHkuRDe8qdqq2mYLAVB8xUJtbTIoJk9Et1CkCqx/OjZXboy8xMO8CeJY/UH7b0lGR8c/cALHhsKLJqpOouXBxLWq9YWnISsmqkYuLt/Q3vkrVqumlNZrB64pt8r++C2q5RbYzq3syx/LbJ9w0KuxzMyqfPxj1nGtdhc4P6WP/r+Z0w40HfDCetnrruLbLD9hQaXRQql0my3MyI1AxTtPa2033pCuFy82LpFP8QvN5EgFPb1A+7tJNeEvhlvVuY6oFVtmli80xVq7J06jEqN6oNaqcjf/xI3DKoNb6667TACg7xaETnJnjqgs6qnq3g98lsYn+kogq2hBD1hBDThRDr/f9XOXqFEN2FEHOFECuFEMuEEFdE85zVTbR5He0a1Y5qpot6BthVp+rXL7HKrrsIZTdaSanRXnAyUpPD1g6KJaNjoW/reujfVjvnDPAVAw09Ds7p0qTKdlbfF2WJpVrpKXhtdA88eu7Jrg2N1LJY5DPWJHzJxUrBxdP875dRjs+0+6vmSxlRjvlIPl/hEru1hCv0m5NdA7+NGRJYfN0LlEPkvRv6YNyFXYw31hC6dl+k8sePjGr9WTv8WedvCa17N3Zkp4irzYcT6XqYVg1s3wBCp1j3iqfPdny5uGh7tsYAmCmlbA9gpv/7UMUArpNSdgYwAsA/hBCRd9VUM0P9yZRuzW6/+8x2gUU400PqKcXiLsfs3611mbD6knm9gkAkJTOMRDLzUHFRjxx8oTOT1ijoo0o3DWiNBY8Pxf9d00t3m7o10/DTn88IeszoOFV6JCKp6F9lXyY+D4+c0xFvXavffsAXcMWitmA4Ss+FcrEVAK42KIAZKn/8SKx4+mzccbr9k4vcopeTZWVR8UgJIfD9n6zdTEQjdNiwVLX8VCwKVkf7DKMAnOH/+gMAPwF4RL2BlHKd6uudQoi9ABoCOBjlcyecUac0w7dLdwY9FquoX0/NtJTAzDc7T5h29Wwpd4ah+7v61JY4L8qq6XHBpcPj1RguLZIoQt+qlOQkNMrMQKPMDN3e5/IKidwGtTC8U2NMX7UHgHFdsVsGtUZug1qWpuArQmfvmfmM5mTX0OydsbIodaxkZqRgX1EJBHwV+CNZfsvtVSScZlS82AlGNcnsFjpsWOZwQnyoaK+ejaWUuwDA/79hYosQoi+ANAAbo3zehPR3l6sLd4tyyquV4qB2JdC3a1Qb/7q6B+4Jqao+7qKuli44T53fCa3C5Gl4Rbj4u2UUf4cXZ17Gu/uHRV6WQpkhdeugylw4o/c/u2aabs6lkVXPnB00BDv1vkFR1QD0clAiBPDPq3oGXXxD11WsLkInEbVrlOm5Aqt2Ua+LOKp7s0DuXqyEDbaEEDOEECs0/o2y8kRCiKYAJgC4UUqpuTy8EOI2IUSeECJv3759VnafENzsap/10Ol49/reYbe7pp+qPAJ86+Ip+rUxP3yUk10D654zXuLj41tO1c0pUDu3azPdSvlm3TCgtW4V7HjzUBQ1p4zydpRg/NJe3p3x50W9Tcyi1KN19+1ExfzQXp5OzepEVUbD7R55Tf6X0pNtI8epPzevje4R8wA77NVFSjlMStlF49+3APb4gyglmNqrtQ8hRB0AUwCMlVLOM3iut6WUvaWUvRs2jN9ZD9F4LiRhM1bnhTYNa6NRprWARcJ4YdVwwq2pN6BdA0frkSWqlOQkR4+bv1/GIUQrhBB48rxOGBBBzaI6GrlXdg3B3+lAYWOFl8OZU0J68NOSk9BAo/I8JRa38waj7eudBOB6AOP9/38buoEQIg3A1wA+lFL+L8rnS3ih3e9O1/6wKrTb+bR2DbD2uRGOrdVGVZmpH+bEcfPCxV2xraDY/h1XA5HMxuvYJBP1/Tcb7VQL9dpVfNHJcgxe7DxS1hR97NyTgx6fM+ZMpCYlocez091oFsWI2yuBRBtsjQcwUQhxM4CtAC4DACFEbwB3SClvAXA5gMEA6gshbvD/3g1Syj+ifO5qJdxh8vCIDjh8rCzsfh4POdFEQxkCZ6AVWx1V613qHRedmtbBql2HbX3ezs2yqiwETrGhHvKwY6ah02JVMd6KD27sg6KSsirDiFZ79BOJF4Nip+gtZB8rUX1qpZQHAAzVeDwPwC3+rz8C8FE0z0PhF4Ie0bkJ2phYofyWQdHVu+nZKhsT5m3xfe1Q3RXSF5q8qtfH8eKl3XDeG3Ms799jHamkIRbT8qPlxYt4ozoZxjO4qqFw6zgmIDDmiQAAC1pJREFUEr2F7GMlMTKCE5iSsPxAmBlNZi+S0SaHqpd7ya6mM3i84rt7BuKDG7WXDbH6Nv9LWa+Q0RZRtVGdJgvEdc8WxY7Rwqdm9G9TH3M3HbCpNT5XWVivkexntDq9Uc7WzIdOx7ET5Q60iMgn3OQXolhzO0GenwiPiXS5kXC/1aKeue7i+4a0q1JpV4/bCYcUmbYNa1dZmkJU+YIoMtPuH4S3rw1fRsZrxo60L5+VvMftYIs9Wx5zUuPweVdawo3+mE1YffAse9b9IndFOhtxcPvqWXKF7NOxSeyqghOZZbYTwSns2fKYjk3qVFkLzQ52Ds2/cHFX+3ZGjpARJl+xt9K77E6v8eKMQSKnuH1uY7DlQeqT6pCOjfU3tKCFjUvRnNmhkWaxRfIOs6WYpt43CPMfG+rJ2WMU7F9X9bR1f5EG5ETxyO2eLV4xPUg9BNSyvj1B0rX9W9m2XlmTrAwse+psW/ZFzjBadketUzNlyIfRlte5fWee6KrTzLzqKNJ8aLsw2EoQTbOMC/PVyUjF9aflxqYx5LquOdaKj57cNNPRiuJkzae3noqGIcU27Q4GOIxIANC2YS1s3HfU7WY4LtnlYJrDiAkidCFZqt6sLqrdqn4tLHnyLIdaQ1b1b9sgaIkecl51DT0fryazMFNcrrPFYIsowVWnKtFkXrS1+ygx9G1d3+0mOO7SXs2Rk+3ueZDBFlGCe3C48eoDFB/svi8f3aeFzXukeGRXLq+Xnda2vus5eQy2PIhzhIgolN3XCqtDzYmO+fHkJH7aiIjiAIMBcsqcR87E1acm5vJrD5/dAUM6ur8EeeL3HxIRJQDOHnTWKS2yUaua5rE1r1sT4y5KzGLVd53Zzu0mAGDPVlx5/4Y+bjeBiCgh9WxZFyufGeF2MyhBMdjyIL2ClPVqpcW4JUTkGezYIopbDLbiCBPniYiI4g+DLQ9797reQd9XmFyChQgAGmWmAwDO6dLU5ZaQHdixRRS/GGx52LBOwYtQm13vjggAXr2iOwAWr0wUTbNYnJYoXjHYiiMVjLXIgi45Wbi4Z47bzSCbdGiSifzxI23f77ldm9i+TyIKxmDLg/RiqgpGW2RBVo1UvHJ5d7ebQR53WW9WkidyGoOtOMJYi4iIKP4w2IojkvMRiYiI4g6DLQ9qXCcDzetWTYY9tRqszk5EsfPeDb0xqF0Dt5tBlPC4XI8H1U5PwZxHhlR5PDmJk7+JyD5DOjYOvxERRY09W0REREQOYrBFRERE5CAGWwmgW/Mst5tAREREOhhsJYDRfVq63QQiIiLSwWCLiIiIyEEMthIA628RERF5F4OtBMD1qYmIiLyLwVYCYKxFRETkXQy2EgG7toiIiDyLwVYCYKhFRETkXQy2EgA7toiIiLyLwVYCkIy2iIiIPIvBVgKoYKxFRETkWQy2EgBjLSIiIu9isJUAGtdJd7sJREREpIPBVgIY2bWp200gIiIiHQy2EoAQwu0mEBERkQ4GW0REREQOYrAV5waf1NDtJhAREZGBqIItIUQ9IcR0IcR6//91DbatI4TYIYT4ZzTPScHeGN3D7SYQERGRgWh7tsYAmCmlbA9gpv97Pc8C+DnK56MQWTVT3W4CERERGYg22BoF4AP/1x8AuFBrIyFELwCNAfwY5fORSo3UZLebQERERGFEG2w1llLuAgD//41CNxBCJAF4GcBfwu1MCHGbECJPCJG3b9++KJuW+FY/O8LtJhAREVEYKeE2EELMANBE40ePm3yOuwBMlVJuC1eiQEr5NoC3AaB3794sjE5ERERxL2ywJaUcpvczIcQeIURTKeUuIURTAHs1NusPYJAQ4i4AtQGkCSGOSCmN8ruIiIiIEkLYYCuMSQCuBzDe//+3oRtIKa9WvhZC3ACgNwMtIiIiqi6izdkaD2C4EGI9gOH+7yGE6C2EeDfaxhERERHFu6h6tqSUBwAM1Xg8D8AtGo//F8B/o3lOIiIionjCCvJEREREDmKwRUREROQgBltEREREDmKwRUREROQgBltxZuzIk91uAhEREVnAYCvOhKvCT0RERN7CYCtONa9bw+0mEBERkQkMtoiIiIgcxGArziiDiBxNJCIiig8MtuIMgywiIqL4wmArTknpdguIiIjIDAZbcYbDiERERPGFwVacGd65idtNICIiIgsYbMWZnGxfyYcbT2vtckuIiIjIjBS3G0DWTbi5Lwa2a+B2M4iIiMgEBltxaFD7hm43gYiIiEziMCIRERGRgxhsERERETmIwRYRERGRgxhsERERETmIwRYRERGRgxhsERERETmIwRYRERGRgxhsERERETmIwRYRERGRgxhsERERETlISCndboMmIUQRgLVut4NiogGA/W43gmKC73X1wfe6+uB77dNKSqm5np6X10ZcK6Xs7XYjyHlCiDy+19UD3+vqg+919cH3OjwOIxIRERE5iMEWERERkYO8HGy97XYDKGb4XlcffK+rD77X1Qff6zA8myBPRERElAi83LNFREREFPc8GWwJIUYIIdYKITYIIca43R5yhhCihRBithBitRBipRDiT263iZwjhEgWQiwRQkx2uy3kHCFEthDiCyHEGv9nu7/bbSJnCCEe8J+7VwghPhVCZLjdJq/yXLAlhEgG8CaAcwB0AnClEKKTu60ih5QBeEhKeTKAfgDu5nud0P4EYLXbjSDHvQZgmpSyI4BTwPc8IQkhcgDcB6C3lLILgGQAo91tlXd5LtgC0BfABinlJinlCQCfARjlcpvIAVLKXVLKxf6vi+A7Kee42ypyghCiOYCRAN51uy3kHCFEHQCDAfwHAKSUJ6SUB91tFTkoBUANIUQKgJoAdrrcHs/yYrCVA2Cb6vvt4AU44QkhcgH0ADDf3ZaQQ/4B4GEAFW43hBzVBsA+AO/7h4zfFULUcrtRZD8p5Q4AfwewFcAuAIeklD+62yrv8mKwJTQe45TJBCaEqA3gSwD3SykPu90espcQ4jwAe6WUi9xuCzkuBUBPAP+WUvYAcBQA824TkBCiLnyjTq0BNANQSwhxjbut8i4vBlvbAbRQfd8c7JpMWEKIVPgCrY+llF+53R5yxAAAFwgh8uFLCxgihPjI3SaRQ7YD2C6lVHqov4Av+KLEMwzAZinlPillKYCvAJzmcps8y4vB1kIA7YUQrYUQafAl3E1yuU3kACGEgC+3Y7WU8hW320POkFI+KqVsLqXMhe/zPEtKyTvgBCSl3A1gmxCig/+hoQBWudgkcs5WAP2EEDX95/Kh4GQIXZ5biFpKWSaEuAfAD/DNbnhPSrnS5WaRMwYAuBbAciHEH/7HHpNSTnWxTUQUnXsBfOy/Wd4E4EaX20MOkFLOF0J8AWAxfDPLl4CV5HWxgjwRERGRg7w4jEhERESUMBhsERERETmIwRYRERGRgxhsERERETmIwRYRERGRgzxX+oGIyAohRH0AM/3fNgFQDt+SMQBQLKVkoUUichVLPxBRwhBCPAXgiJTy7263hYhIwWFEIkpYQogj/v/PEEL8LISYKIRYJ4QYL4S4WgixQAixXAjR1r9dQyHEl0KIhf5/A9z9C4goETDYIqLq4hQAfwLQFb6VC06SUvYF8C58Vc8B4DUAr0op+wC4xP8zIqKoMGeLiKqLhVLKXQAghNgI4Ef/48sBnOn/ehiATr6l3gAAdYQQmVLKopi2lIgSCoMtIqouSlRfV6i+r0DluTAJQH8p5bFYNoyIEhuHEYmIKv0I4B7lGyFEdxfbQkQJgsEWEVGl+wD0FkIsE0KsAnCH2w0iovjH0g9EREREDmLPFhEREZGDGGwREREROYjBFhEREZGDGGwREREROYjBFhEREZGDGGwREREROYjBFhEREZGDGGwREREROej/AcrJypzOly38AAAAAElFTkSuQmCC\n", + "text/plain": [ + "
" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "plt.figure(figsize=(10, 5))\n", + "librosa.display.waveplot(audio_files[demo_audio], sr=sample_rate)" + ] + }, + { + "cell_type": "code", + "execution_count": 11, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "' የተለያዩ የ ትግራይ አውራጃ ተወላጆች ገንዘባቸው ን አዋጥ ተው የ ልማት ተቋማትን እንዲ መሰርቱ ትልማ አይ ፈቅድ ም'" + ] + }, + "execution_count": 11, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "transcripts[demo_audio]" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## **Resize Audios For Mono Channel**" + ] + }, + { + "cell_type": "code", + "execution_count": 12, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "(200391,)\n" + ] + } + ], + "source": [ + "audio_files = resize_audios_mono(audio_files, maximum_length)\n", + "print(audio_files[demo_audio].shape)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "**Sample Padded Audio**" + ] + }, + { + "cell_type": "code", + "execution_count": 13, + "metadata": {}, + "outputs": [ + { + "data": { + "text/html": [ + "\n", + " \n", + " " + ], + "text/plain": [ + "" + ] + }, + "execution_count": 13, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "ipd.Audio(audio_files[demo_audio], rate=sample_rate)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "**Waveplot For Padded Audio**" + ] + }, + { + "cell_type": "code", + "execution_count": 14, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "" + ] + }, + "execution_count": 14, + "metadata": {}, + "output_type": "execute_result" + }, + { + "data": { + "image/png": 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\n", + "text/plain": [ + "
" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "plt.figure(figsize=(10, 5))\n", + "librosa.display.waveplot(audio_files[demo_audio], sr= sample_rate)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## **Augment Audios**" + ] + }, + { + "cell_type": "code", + "execution_count": 15, + "metadata": {}, + "outputs": [], + "source": [ + "audio_files = augment_audio(audio_files, sample_rate)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## **Extract Features**" + ] + }, + { + "cell_type": "code", + "execution_count": 16, + "metadata": {}, + "outputs": [], + "source": [ + "feature_extractor = FeatureExtraction()" + ] + }, + { + "cell_type": "code", + "execution_count": 17, + "metadata": {}, + "outputs": [], + "source": [ + "mfcc_features = feature_extractor.extract_features(audio_files, sample_rate)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "**Plot MFCCs**" + ] + }, + { + "cell_type": "code", + "execution_count": 18, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "(20, 392)\n" + ] + }, + { + "data": { + "text/plain": [ + "" + ] + }, + "execution_count": 18, + "metadata": {}, + "output_type": "execute_result" + }, + { + "data": { + "image/png": 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u/+As1uO42j/isL5ja/PMJ+BffIQQQjYFEx8hhJBNwcRHCCFkUzDxEUII2RRMfIQQQjYFEx8hhJBNwcRHCCFkUzDxEUII2RRMfIQQQjYFEx8hhJBNwcRHCCFkUzDxEUII2RRMfIQQQjYFEx8hhJBN8Wkt0UeUQwD0d5UpQsSoPqXWwniTNRFZK9M0Wa8hpil6DhEgqJqkVtCk34sFAtwH40jPJsVGcE51KLVOSAwwjZBKayTSquJEDEzSvMiVxsI2RQUklYZoWYoayEt+VvYNJOmK4rghos8D+lmKaVLGhAAsc9GoGKtt1c8mtcc0FSWLtbmdrIrqug/j2A+qdKl1HXHsYZ7WqpSo9ZBpKvP2slYJVXtBak0RUNQmtWqm6ncVXfHleSNFudJ1qnUBgKQmqjRQYYpj7gfdS0kPA6xVUVFxhOCB8aKaGNvoO7phdN5ZRxXfTeuaYpzWoF6/foC4Rfu2FtK4aj9Uipa0vk2reyyRdDIpTundtA99KEoiIKuasmoptS0WkFD6AdZ7WETX35ii10r7qR5H035cRTVNRQvkHNBEhVPbQe5e6Dy9By5nXbdo4sE865oFr3tWyhnB7rCafzqTcIuuUQhx3YriR4fqdU+nWCQq9Uyt9dI+DVaXlHPlbNb3TqvrhqbRWFibFUrmcFOUONVYte9yLuRQKXnSPvJ6nuVmKO9X92OJa6t9OwcEFB1QfTbSuqQzKnFuRlb7X1DdncGrfiz13e00nsED8wy5Xv+kCQLK3k/95rgW3RNsA2lRzlvakzE2sjtoH+le8zH+1/vMWr0DTafv1X2lvX2tOEtxTOq6KtdkBZ69up+u4F98hBBCNgUTHyGEkE3BxEcIIWRTMPERQgjZFEx8hBBCNgUTHyGEkE3BxEcIIWRTMPERQgjZFEx8hBBCNgUTHyGEkE3BxEcIIWRTMPERQgjZFEx8hBBCNsUn7QwheC1wXlcUh1oQalNCrhieKvLPa4tCrqgeK+YH7yF1ZX0g/35ViVuu8nLwgDd5LKGuHB7NAAHRBJCrcztgWXKl+eB9qQL+sQreoarCngqWpyr1qdK8WY8rnI6ler6RUmlfot3AOYRU/Tz4db/OIcyzVvq3DcQua7NE3W/TIIwjpIpprsAebROYRu2r6yDnM8IyI3gPM8Qq8cNe23ueY1X6WFXdAOKrdcpx9bFCeqneHqp1rJEUl2SPCD5XdA+Lr+Jo1tXsjWg1dee0P9vofynWYrSCv7WAKYYFHdtV5fYU42TjCGoQCN5D2jbGLNknXDF6JNtA6i/t73nUZ6o1C9OkVfm7TqvbD3v9YJn13WRQmCeEywnSD2WtKwNEKmavfbkyXiAbGlKs4aKhpFqbaztJfid4yAlln6Z3RLJtIDinz0cDApa5VNmPZhLJlo6gcZh1fnmfpHaCL+2Y6nxOU97v4l0xG6TnUqya6hoaL/CnYzwLdjWvlYEA5QzoXoxGB1ute4XuVQ8JXTlP0YYBo2uF87Gsu7Vra0VaB2MBYxDGi/bXD7p085hjla00bQP4psTj6VHfSXE1FjgdS39xfcp9We2RNCfnEGyMSWVLCMGX/RD3mLQdwjzpWJIxIp2tFJ9oMMk2DjE6bmOBttWveV2jeST9zjt9152vxu0gvYtziiaJeS6GlPGi4wKKRaZN99el3APVXl0vZlo/zQcBLs8nzMUO8yn4Fx8hhJBNwcRHCCFkUzDxEUII2RRMfIQQQjYFEx8hhJBNwcRHCCFkUzDxEUII2RRMfIQQQjYFEx8hhJBNwcRHCCFkUzDxEUII2RRMfIQQQjYFEx8hhJBN8Uk7Q66wD6gVwRYTQzD+k6+uKsenStm1maGu4F+RK/47p9X0U3X/9F6sdC7WlorwQKyWHquGi2h171RdPFXSR6xqvsxaeb1p9bnxAiwLVjRNrlifK+QDpXp5qigO5Kr/cA5YZjUodF2shK4VzSW+7y+xEnplNkhWg+CimSEVI/eLtpPanyb9uevKPOrq8RZA1+u/ZowBvIc0jbafjAQA0LSQ+5danX6ZtXI6oHMyVTn4HNxQjBKno5otYCFGSuX02tYxz1pdv2l1PmJKHHWRy7NugQQD3NzpL+ZJq/gns0DT6noOO/3dNK7WK7UZYuV/MXGt+0Gr+c8zYKOBIcUgzRuApD3oJf8+TFOxXzRtsTDMI9APEB/gx4vuuaaB6Xpt11pAamOIL/3W1egBoO11j4Wgc/LReJLtAPol2zd8QHBuNc/gYvzS/pFQzkptiUhj64d8ZsRHW8Z4QXg8aQV/W1Xd74f1uZ0XmPsXupbRWAGonSCcz5Cqin9IxpE4TvigFfTnJY8/f1abF8RoPPcHoOvXFoV638S9L8koEN+vv0plcYEPxfaR5pcwUua5O5Q7ZboA53MxR6TfxzXLdpfaNJLmJQbom7KH5znaWip7C6Ax7uo7NhomjC22g9oy4PUcZltFZWYA1hac4NXWIMP+QwtNMpEAahCJhohksMh76nIuc6rPsk4y79lkhsjWE+uKkSaZQ/aHYoKwDSTbV0TvrvHxQxtPmlO9jvXXjzyfDTGVTehj8C8+Qgghm4KJjxBCyKZg4iOEELIpmPgIIYRsCiY+Qgghm4KJjxBCyKZg4iOEELIpmPgIIYRsCiY+Qgghm4KJjxBCyKZg4iOEELIpmPgIIYRsCiY+Qgghm4KJjxBCyKb4tJao1m0YUXUILIJzWY2RtEPB+KLLQKXIuCKpSFSbAgSHrCSpRRL5fSOAN2qgqNr3lwuAy7pda1Wt0g+qNUnaHrcUtYmFKomMVUWG90Aoag9J+hHbZIWIGNXqIPiiyQmhqD2mSduMWhNJ+g1j9DMjwLDX6bRxXKmNqC0CAMxRaZR+7uxan5RUIPOsbYtBdhg5V8aYtB1RzaNtqxYHy4wwL9pH0taEEOdltN2kegGi1klynCBSxitSdDSJZcmqmBA84ACRoOMIOpYw+6IPCarbEUDHkOKfxrAsun6VIuUP4hwCotYl6WaSbqrSQKFp9D/nALuUfR5jAxR9UFYciZQx7Q8wXYdwPquyJ79fVC+qEVqAZYGMF23HWMAmhdWimqO4VlnfFTwgplI4fahXWWmsKlY/m6hySsqkFNPLKTWifYWgOpllKcox5yDnc9HdzPEcVUowSYqj4FWdZMrZlH7QNr0rZzZqxCTNa5mjSiziA0KY49kwEO/KXkj6n6zAmsuZTaqfWudkLIArpU/SHgVfNFxJG2Z0n8I7IFj9fTfkcWkQvO6v01HnHMcWlnmtCkpnyja6xl2rv4vKstWYQvjI/RSVQVFRFXB1jzoH78v5FPPxv13y75dZ95kYvUucQzg+lefEQA63+n3wqzOQFFe5HWsBN+VxStMCFhBYjU9ShaW7tOvK2sU1yPdnukNC0HvPOcCrtkrS3QtkvRWAojKq89JHtFApTp+Cf/ERQgjZFEx8hBBCNgUTHyGEkE3BxEcIIWRTMPERQgjZFEx8hBBCNgUTHyGEkE3BxEcIIWRTMPERQgjZFEx8hBBCNgUTHyGEkE3BxEcIIWRTMPERQgjZFJ+2M1hbqolXlcJrC4OI0arqsKVKfTIC+FC+BwBfKmmn6vPBLRATK51XVbbF2tXPNRItAnXlbrRt6dM7YBqjwUBK5XNAq3ZPk84tePjzWSuWL1p9XrpOp7Dbx0riQZ9PYxGjlf2lmleqQL7MpYJ/6nvYxfHEquYu2gBEq9WXau4WaDuIMVr1H0AYL5BpgvS9zs/GKvix2nu4nNbVy43J44eRYoFI4wGAtof4kKujh3lCmGeIbUo/aX2dA6ZzrnQeYoV6iNGK/AHl2eARnItt2bwWwS3xsY/8G0sMxOrX8Phe20zV1lO7Tatjcq7sx3mMnzWQtL+MVsQPbkG4nCHLks0XYZoA58oY7C5aH1xZv9iXtE7NGoloIMAY1y+ZOKzVWFfWAki134IHjGhMvAemSavZN/HIJYtFjKXA6vnyJZ66PmqySJXwk2UgBK+WhOosZjtHms940XnWFo60X9IYm1b3aLRIhGXWPWWvrgZT9kTwQfdQXKvgnP4c1wS2AVoLoC0xrvc6oOdATDz/1RyibSG46sxYq7YH22SjBKJJAqnIf7ybQjrb0XQRvM9GmGC8mgSSsSLFaXJlnU9H/V0/qKFh0r0Qns8I0xgNME0MoYd0HcI0IYjOX5JNpW4/7oVieohfp3FlM8nnyquxZGUdyOe1sqRcU1sQ8u8ECNEiscyQYQ+5e7E2sAx7XY94tnPcURkREO/dzpZ1j21Iineyd0g0MBhTYjGNgO11f1zOwKWyJ4hAbu7UFDKNel+mGNTxSmciGiPqsdX30P8X+BcfIYSQTcHERwghZFMw8RFCCNkUTHyEEEI2BRMfIYSQTcHERwghZFMw8RFCCNkUTHyEEEI2BRMfIYSQTcHERwghZFMw8RFCCNkUTHyEEEI2BRMfIYSQTcHERwghZFN8UkuUtB8hKUCiWmOlDxLV5CRVSlZvGKk0FUkHA4RQKYtqjACu+r1FabPWHfmgnw07yP4Q2/JZZQGgaITqPir1DPoBaFUfYl5bff981DbyWG1pO+l4rFW9RtLW1GqQpNBwi6pgmkohtJpnar+ptCVR8WIt8GIP2Wn7EpUoquKZi0omjkv6AXK4XY93vCCcjpBhB9zeRz1INYbponFsO9WgeAdZ5pV+Cl31fKWYkuBVZ5KUNM4hOFWYhGnU8TXNas4SDIL3RTFyHbe4r3R/2Wodk5LE6+/bVjUxAJDWPa0PgNSiJG2NczrWaVLVi7G67om2A2TWsXbDSruDrltrW1J8kzIpKXKaqN1J86n3WAiQ8aLKlmEf36ni6hzEu6IS8gGCEZB4vpKeCJWiqUI+8rscz/TVNrp+wQOIOq06Bm4pz/YD0A8Q73U/GFNiuywIlxNk2Osc0vmJ5ybdAZmoN5IUs37QvkMocd7tIV2vfV3FJa9Boml1/Uyl/ppnwC8fTD+k9zVIukdDUP2Vjxqj1J9I1FPFdqwtWq5l0X73er7kcKfrNV6AeVJ1mBFgd4C8eFXOmDHAPK33jzS63l1XdD2pv35QhRYAzCPCHL+vNWipGTFFvwbonkm6onRH17GYF0gLwFhdu7bT89V2CPsbbdM5HS+guqau1zbT/Xmt+Vlm1RFFBVmtHhLTlLEPhzLHEHQvuhg/a4uuKN8v8e5tW8CZfO9KuJpT3JP1XajqqXWsPnZmavgXHyGEkE3BxEcIIWRTMPERQgjZFEx8hBBCNgUTHyGEkE3BxEcIIWRTMPERQgjZFEx8hBBCNgUTHyGEkE3BxEcIIWRTMPERQgjZFEx8hBBCNgUTHyGEkE3xSTtDXVHfuxFiPqx+HWIV/QCXK8EH73NxfTEGQSpjAxCrtpffiZjcl1SV2rPtIfYl1iLArSuwX2ME4qAVwC0AEfjTMY9dnIuV4n00FcT+UoX0NPAr20IIXiv/i9HK8T7kCuz+fILYRi0AqVJ9CFphPI01VSFvWq1APs9axT5V5k/V6JONANDnTIyVkWhogPbb9jqO9GxVRT2kiuvffVNiWhsacqxixXtj9Z9A1up7x6fYfx+tBKKV8L0vz3qdk0DblcNBP4tV04NzWi2+MSWW15Xes2nCqBHCNsVakYwHy1Kq8acxA6VSfz2XEPQ9a+MaeDUDzCPCOGaDA2xa/0nXtR/W1dz7vvx8OSFMkxpIhr2aP6ZJY59MHzYeo1S93zkdyzIjTJP2myraZ7OH0TW3dm0XMQLxBsFEM0JQI4Qf5xh/gwCsDRc5nnH+6eylfSemmCQw6odNU95Z5mwrybGt2zdSbBfpP2v1d9ME7HZljedR97OYOJ+4xunz1EfTxor8UmwJsT1/Ouq/yJvKRLDMwOW8nq+p7Sjxa6reb62eeaN2kHxfzQvw7iHO3ath4MqgIm2rZ2a8FBNI25XYpOeSxSFcjSvGKkyTrnGcR4j7Vep5JZMMcGUwMev5XX8e7TfBOUhtx0n4gOAW7VNE45nur/M7iC1Xf7icIG2ndoZ09mwbDQlXFh1rdT+L0RileEeDh7Z3gWl7YNgVI0S2ukjcx2kenfYR7S5hmsq4pjH3uYpt3OdBJN+zIQRAqvHK1V1zBf/iI4QQsimY+AghhGwKJj5CCCGbgl2v+eQAABjFSURBVImPEELIpmDiI4QQsimY+AghhGwKJj5CCCGbgomPEELIpmDiI4QQsimY+AghhGwKJj5CCCGbgomPEELIpmDiI4QQsin+FjvDohXOxWjF8lThfJlLZX0xpep3/FmsKRXdP9ru+vfZwoBie9Af/LpKuQ/6X913eg7QKuxLgOwPWj1/p8YAYxutuF+P1zalsnhd1TxVTs+mAq0QLm2nldmt1WeaVs0NAEw/APubUuneO6DtEGJFd0kVxVNfzhXbgHOlWrsI0A05FphnoIt9OsSq5Earnu8Osap5rPafqpqLgXn5SivPn45lzv1Q5pesFP1QxgyUMSYDQtfFav/RaGEtkNo0UkwNgMbGuRxLSetmLKRpsrUh48N6HzinY0t9Jrpe45xilCwB06QmgISJdodkuUhrNI3AeIHc3JQ2xgv8sxooxDZxn7piXLici0Uh7gVpWp1/1yGcjgjTqEaO2qbho60gVY0HILd32mayNsRK85L2kdFq9dlmAT0P6Xs05Vzl81Cdt+CWPEyxVs9ACAiXC9C2ap5o2rJ++eHYbrItANE04Ev8auOCLqoaQwC1KDw/Acbo/k9ntO2LiSJ4hMsMmZdiXUlWiGjXCPOi5zXeF2GZYfYH4OaujDft0dU9I8ibL/hifun6Et/0Ox9yTENl9AjRdqH2FLVlyLDXfTBNumY5NnO0XDTAsIPsDsVQMRfDQjJsJPzpqM+I6B1amxkScf9IMoxU5yJ8ymiSfhUNDdeIbTS2TaPnKMVt2OmYAeB0RJhnHZdzwDQizJOuhffZapP2FUQgxujzu12xenQBcrjRLsZLuWfOx7Lv2077fn7M50u81z0VDTg6nyXeF+nODGXs+Z65skb8/4R/8RFCCNkUTHyEEEI2BRMfIYSQTcHERwghZFMw8RFCCNkUTHyEEEI2BRMfIYSQTcHERwghZFMw8RFCCNkUTHyEEEI2BRMfIYSQTcHERwghZFMw8RFCCNkUTHyEEEI2xSe1RHBO1TFRTYGkPan0KkDSVXjURiEsRSUhNqot5hlijLYBZOURglcFRtsWPVHUrYgBwuwhtkEIs47He8gwrFQcYV4AeIQ56kvaDjg+I1xOqmiJczD7A7A/qOpGjOozvMvKjaz9cAD6qP9J+hLvEayFzJPqNqJayD89wpyORdPhPfDuLQQoepxhl2MK71QT0g+QEDSWvtLBJHWJjwH1Pn/uT0fgfIIZLzqPpPBpGmC8IFzOGkvbqBIntZ3aOk8I57PGzjtVoqy0Hxaw8edl1vn0g2pM4rr786moQVL/SVVSKVkwB8B8qKYSMR/oVkLwELcA0uu6JB3M8yPCvBSNSddBuk7HWccqkfbmNKpmZ5mzZiZpmqRpYV59XtRSSQNjjM6nKQouGAGGfdxPT8DhFjLsIKltHwCvezVcYlyikkmsRXh6VDVQ1wF395C20sPoxIHponslrtG1PkdVXxZo+qJ3ilqn+jxlzVPcr3L3QtdOJOqHlhLXFLdpLOcgxDOc2qm1UdYijKPOu1H9k3nz/dxX2KuSJjQ9zHwB5gmyzJAUI0BjnfZajJNYq/1OqrQKlwuCmWCc0/0d+4b3wOF2paXSu0k+VJUZ0f3k4z6Lip0Q4y1RXWWSwkpMmWvTlNjUezmO2T+8hXt8QnAOputg7+5UeZXUVPMFmB3gtR9p4xXrg67FeCl7eX8ourCkOJrGuC38el5A0QQlNVX8HRBVcbIerxgD//BWp/Lyle7BpPSq7k4xcf2tVQVXVP/UreUzV6urfCj73Tvg6TGPJWuL9AKHfzpCrIUMO+2jujcwzxrrOSC4BeEylvkbUXURonYr5iQRAxGJ+SBAGrvSgf1t8C8+Qgghm4KJjxBCyKZg4iOEELIpmPgIIYRsCiY+Qgghm4KJjxBCyKZg4iOEELIpmPgIIYRsCiY+Qgghm4KJjxBCyKZg4iOEELIpmPgIIYRsCiY+Qgghm+LTdgZT8qJYqxW3Q6xyXpPsBUCpkF1VCk+V5sM8awXwZDpYFv05PZtsEKlNIFfjhllWJgB/PEYjAwAjMLudVl43BsvDA+TxEdK2EGthbm5LNfJp0iriqfJ6P0QjQbQUpOr184wwT1otPo8pQPpOK5kbQZgm7f7FZ8AyI5yOCNMD/OWild+NAfwxBiFGrWl0PP2gFf8B7TN9fnxaxR3LrBXORRCWGeb1m1htfwHGscxLBOh6tTIMO62WLqLV0y9n+OcnnUIcsz0cIJPNc9FK60uxOMT5hqdHraLfdTn+5tXnQBerys9j/DppxfwUP6+V1mtjh1jdbsGUausaGo9wPqu943IuVftjvKQzkBcvdZ2mCzBeNF61JaTtANtEY0Lcj6ny/+EWsA3kfCxjHS/6bKr2n2wHfQ/cvcjV9n2/V8PIMuVq9WF3yBXyZZ7ynpEUj1jdP4wXyOG2WAZEcgyDtZBpLPutbYEZ0Zgh2j6g580tCNOY7RES90eq1p/imp5H0yIsM/y3X+vzXV/WOO57SXaDaEYx1uqeHPa6D5q27MnTEZiPkN2u2B6SISAZJdKzy4hgW4Sm09+lGE0XYPTr9Wp7fd97jUNcV3P3otgKAGAaEcYxxsIVkwmQz0reL8EDXsfm/bw2TOhmgz8eyztG97akNbqc1WgQ35NB97n0A7A7QF6+hm16yDLqvIzV/ZTWMcR91LQaq2x7ifusHyBNXC9bGQWWWS0Fy7Jal7wGaU9H+wS8qQw2xdCRfgaiyeSz16X9Sfd9bf7IppzgAcR7sO103Lap7lyrezZZWQCEplFbx+Wk91G0XeRYxvOV1iw4h+W7B0jbwr641zbmGeEy5vvUzwvC4iCN1ZwTJOcbMSbaUAJQ5BLxQ1l//VssDfyLjxBCyKZg4iOEELIpmPgIIYRsCiY+Qgghm4KJjxBCyKZg4iOEELIpmPgIIYRsCiY+Qgghm4KJjxBCyKZg4iOEELIpmPgIIYRsCiY+Qgghm4KJjxBCyKZg4iOEELIpPq0lqpQeSc0TvEeYpqy+yJ/PUc0S1SnpnawLQdSAJJ2MCMKiuoqs1ajbrPQSdZsAVHExTXCnc25XosYlBI/57TvM8TPbNjB9B58URt6juTnA7nrtH4A0Fma3Q3AOPr43Pz1jen9E8B620zDNpxHBeYg1aIYOzWEHAOhePmN6eA83ThAR2KGDHQaIEYi1CJUiw+52CMZAvM9qnOAckFQmTYMwXnQu0wT39Ax/0Z/t7Q3C2++wPB8BH2D6Dna/W62RiWqQ4BykbYpup9U5mGGAe/+I+TJGdZLk2LnzGdN377GcVTXUHga0L+7gzhcsxzP8vEAaC3gPNy0IPqAZVMHTvbhDc38LMwxZtZJVVkkPlNevxCMEr3tHBP75WfuwFpK0UUld9OWXqirpuryPgvd5f8kwQMQgLDPc46Oux2VCd38DaVu48yXvgf71ZzB91CzV+htA4/H8WH608ft5RhhH7T/pZuYZ/vhcNDkhICwOIc7VdB3cwwOCD5C2URVUVLYIoBqnUOag+hZVB6X1grEQ71TBFVU1H+iIkmpIDEJQ/ZB7esblq2/h5wXNYQcxAhM1XQBg9ztI2+h6OacKJTFZX+PPUTUT10C6DvMXX+QzbboO0jaqPAoe4eFt3l+q3mnLmb2cdZ9Pk8YuxhP+EfABfrzoHo/7wv/+y3y2AcDuepjDAf50zv2nvZ31YgkRiI33yceURJdLVj4F52DaFv7pGef/4y8xPZ3gF4dm6LB78xJ2v4OJZ9c9PiLMC/zlAj8t8PMMaSza+zsdT9qHjYX0A/zzk6qfphH+Muo9sMxZuwMAze0NZOj1/ot3IgCNu1zNC0mjJDlOkjRFGrUPng/TBPebX8OdzvDjBNM1unbDoPsfUO2X1TtHqn0MF/VYUbGFacpKOpGo/Fpm+MsFy7v3mB+f8/1t+w526FX5VMUm3WP+csH8m3iufIA9lDtMROKd4GHaBhCT9XMeAJzLd4RByUsw8kFO+hT8i48QQsimYOIjhBCyKZj4CCGEbAomPkIIIZuCiY8QQsimYOIjhBCyKZj4CCGEbAomPkIIIZuCiY8QQsimYOIjhBCyKZj4CCGEbAomPkIIIZuCiY8QQsim+KSdwY9akRtiYIYegFYE987litkAtIp3sjeIKdXmY5V6icYAadtStb1tAWO1yrcYwMcq26lCuHexgrtWrM9V/BetjG7v7tD85Gf5WffVV/H7gOZmj+FnP4H0PcI8Qe5fArGSvd/fYTncI4QAe3pEaBr4dsBsOwgCgtbNR+sX9PMF4tUgAe8gIcB3PXzTwywj7DFWGA8BTTfA7W40qM8PwPMj0HZAr7/3rVal92LgY1zsdIY5PUHmqdgL2h7hcKfP2hbWzWjmCTKeEN5+Dbm5Q2sM0A3wwwGh7XLc7XiCOT9rv+cjYCzCsAPE6DwAYLzAvHyl/XVaSd8PBwQRNPOE7vwMuLi23QDf72H6HTo3w56fgad3ul7JupGqyDsHzBP88xPCRe0O6Dut7B+NAWFRg0eY57XJwAc0P/8FTD8A3sN3Q646L8uo8TkfgbaDv3sF3/Yw8wizlLiFpofrd/BNB29atG7CcHwH8+2X8K9/ADMcYC5HbdM7IHjIsiA0DWB0bwRjEaxdVco3lyPw7i2Wr7/C8nxCc3+L5vM3CC9fI7QDZL5ATs/6/rsHmBc7jf+ywD+9R/NHv9Jx72/hbIvm6TuNzdN7tYGcT9m8EA8YYEQtBwDMLq5f3wNtq5XxQzQPTBP8NAKLVusP1fkJzuHwq5/DfPYa4e4zBBGNV1wDv7tVk8F0hsS5L7tb+G4HLxbNdIQZ1ZBgHt8C5xPsn/67EO/ghwO8bdE8fwd88Vv4yyVXyRfbQNoAtB1Cv0cwFrIbIZczZJlLtX9rEeIzAGCWGeb8jPDt15A3P0CzzAj7W52LbWCeHmAuZzUEnI5wT89qajDFBKP9W8AsamdI+ABprJotFgdJUot2gPQDzN7i5sc/AboBoWk13vMIeIfQxXXoBrh2QHs5wrz7RhvYHQBj4PZ3CEbPgzk/Q8ZTNl3I5Qwzj3CPj7D/4B/B2BbmFO+Nx3e6/l7vtmRp0THavBf0mMW/UaIFRzszgOheCCvDiNpszOs3aH74U41lv4cbDjDTBbKM5Xydj7on4p0S4j0WTDTppPMtBkEEEoJ+9XV/FsN0hn34Wn9uWjU3HO4gIUDefQPsb2EB4HIC5gk46NrCLWrvSPt2HDF/+y3c+QKzOMCEbP4JMTZ+nmGaeE6j1cekPXVt5PgD8C8+Qgghm4KJjxBCyKZg4iOEELIpmPgIIYRsCiY+Qgghm4KJjxBCyKZg4iOEELIpmPgIIYRsCiY+Qgghm4KJjxBCyKZg4iOEELIpmPgIIYRsCiY+Qgghm+KTdobl6RliBGItpG0gXQ8ED38Zc8VsiNFK4t5rtXRrAWMgIoAx+uy797nNbG5IVbRlnXs/Vl1bjOhz0RQBAP4ywhy12j58gJ8miAiCc3j/l7/F6e3/CtNYNH2D7naH49c6huevnzGfdOzGCtp9i3bXwnYNgg9ohjb3a6xAjMB2DUxjIdbCzwvGpwv84mAanctwv8PzV4+Yz3NsS39/envEMi4QY2BbHfcyLlguDstFDQjN0ECMYHyacPqbC9zZY/cjNWEcfrCD7Ux+f//qgJvvv8Tl4QnnhxPm84xl1Hbc5GE7g8PrG+xfHfD81SOevz6i3bcwVnD85qTx9QHf+5PvI3iP9799Bzd7dDcd/OIgxuDmzQ12Lw8AgPHpgqffP2L3Yofdyz36+wMOP3qD5v4O0nVaUT5aOpanZ8yPzwjeQ4yJfcWK60HtARIrvafP89oC+OZf/AUev3iHy/sRwYccr/5uQLtr0d/2uLw/YzpOuhZGYFuD+axrOT1P8C7AdgbBBXQ3HbpDj8Pnt9i/eQkxgqffaVX9L/7lF5iPM9qDxsZNDsEHXYeHGX4JGF7pPphPDuNXE6Q1uP/VAefvRpz/1Yj2tsH+hz2aocH4NAEAdi962L6BGxe0+xZ3P7zH7tUdvvrz3+L03UW36lz2dzM0sK1Bd9Ph5s0t+rs92sOg5ynFp4qZGIE0NlfqD8Ej+ACTTBmmPHv6/VuM/8tfYj5PGJ9GTEcdY3fo4t48wc0exgq6mw5PXzzj+JsLhjcd7n52wHRcMB81tu2hxff/5Hvo7w/49v/8EueHS9xzDrc/0Cr7b//vB90zMVZh9pDWoL3VsaWYXt4mQ0fA4Sc7DPc93Ljg/E6NHq//+DPcfO8e3/31N7i8H3McvAt4+bMX2L3c69r3Hfr7A0zX6vzj3OEDfLQ2SDJdtG2+o+bnE97+738T97e23/QNbr53p+aZxeH8cMyfvfubcnftXvQYXuzw8uevcfeLHyH4gC/+7C/w/NVTfibN4/7Htwg+5Lvm8PkBn/3q13DTjPG93luPX7yHmz2Gu17vqqFFfzugvz+g2fVX+6CcmRDUMlFT74sUC/fr32E+njG+P+LtX32bx9IMFuOj7gfbWexeDjh+e8bxt2fYncH+ewOawSK4ADf7HP/xvb5jGsH85GB3Bt1Ng/6uQ9M3uP/xSwDA3U/f4Pf/01/j4dfvIEbQHVq8+NlnOD+cMB1H3Ly5hWl0rPNpwnyeMdzv0B06dLd7nL97hpsW3HzvHu1hgGmb2K9FiOtrrIWJd7buhxnStjkuvrZYfAT+xUcIIWRTMPERQgjZFEx8hBBCNgUTHyGEkE3BxEcIIWRTMPERQgjZFEx8hBBCNgUTHyGEkE3BxEcIIWRTMPERQgjZFEx8hBBCNgUTHyGEkE3BxEcIIWRTMPERQgjZFJKUMR/jP/7P/rsAqMrmZ3/yS/x7/+EPcDx5/Df/1Z8h+PJe0s+Yxma9jbEWbp5hGot+vwMANG0L0xi0XYd+36NpVcnTtKrfWGaX213mBW52WOYFy7xgnia4acEyz/DOYbg54MUb1WDM44y3/+qrrKj443/89/AP//Q13nwGzIvg/uDxi5dvAQAv5AEmOMy2x6O7QysLGlmwhAY+GFgpuo/H+YC35z0eTxbTImhswPfuJny2O8KKw++eXuZn/637L7Dzz3jAa/zFN5/De+CHLy7o7ILezpicqjVa42CN9jG6Fo/jDsfRYmg9Dt2Exni08fPZa1wa8Xg37vBnfy744fdb/L0fHHHTqhpGROO1MxdMvsOv37/Crl3QGA8RwIiH8+XfN+/OHX73jcHNXvBHn5+xbyaIBFhxGF2Lb097OK9ak0On7VjjYSXgu/OA/+F/dmgag9evGgy9YJy0/4f3Dl99ecRXv/0Ox/fPqnjqW7R9i6ZVfcg8qipkniYEH+BcWe//5J/8Kf7tXwH7bsHQLHm8izc4TQ2MCXi9O6IzM47LgKdpwPPYoDH6/v1uxH13RG8m3Lnv0C1nPPTfxz//y59iPwC//PwZt62qmZZg8Tjt8TS2aEzAoZvgg0FjPA7tGSEIJq/r5bzFce7wm286/D+/GfHm8w6//JHD54cjGvGYfIPzogqjLx4GNDbg89sJj5cW//2/OONP/v4B//5Pfo8bPOKIW/z+rHvm7XOH7x4N3j44vH834duvnvD07ojz8xneOdioYmn7FkYMTGNgrYH3Ad55OOfi+ZhzXAHARy3LZz98jX/47/wIv/xZgx+/vOC2O2P2FsdZlVf38ee35z1Oo8Gb2xGfD+/QyYQ5tNjJKbf5v73/Of7b/3HCf/SPB/yDV7/Hy+VrzLbH75Yf45/9yx3myeMnP1Ld0f3Bo7UBt0NZRxcE49Lg8dLg0Lm4tyYE6D676064NU94WF7in//5Hf74p8AvXr7FjXkGAJzDHn/18Bp//YXB+/cL3n57wjdfvMPTd4+YxwnLXPZL0zZo2jbuLdU2TZdLvhuGmwP++B/9EQDg1ed7tJ2BNYK//0fA92+PsBKwBINvj3u8P1n89JXG4fP+He79Wxjv8Lb5Pn73/BkA4Cc3b3HAEyYZAABHv8fb8y2exwbTovObFsH/9dczXrxo8Ysf+jzWp7PFu6eAxyeP43HBw3dnvH/7jPffvsN0Htd3bPAw1qqizFqYxmQNkXd6T2YNWJzrL//0F/gn/+ktXu9P+EH7e7R+xHvzCu/mW/ig7375uMO37wxe3Xu8upnQW4fGlHimm2PXXNDLCA8DFywEATs5IUAgCJjR4cvLawDAV48DfnR/wqE94zjv8Fff3OievF3w8Nzgy288fv5Dbbe1AV89WLyPMfjqy2cYa7DMDo/fPeNyvGA6q+ppiaqhlGeWeYExomdicTnf6Lnp8M/+6X8g+APwLz5CCCGbgomPEELIpmDiI4QQsimY+AghhGwKJj5CCCGbgomPEELIpmDiI4QQsimY+AghhGwKJj5CCCGbgomPEELIpmDiI4QQsimY+AghhGwKJj5CCCGb4pN2BkIIIeTvGvyLjxBCyKZg4iOEELIpmPgIIYRsCiY+Qgghm4KJjxBCyKZg4iOEELIp/l9SWo/13dDtNQAAAABJRU5ErkJggg==\n", + "text/plain": [ + "
" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "fig, ax = plt.subplots()\n", + "ax = plt.Axes(fig, [0., 0., 1., 1.])\n", + "ax.set_axis_off()\n", + "fig.add_axes(ax)\n", + "mfccs = mfcc_features[demo_audio]\n", + "print(mfccs.shape)\n", + "librosa.display.specshow(mfccs, sr=sample_rate, x_axis='time')" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "**Plot Mel Spectrogram**" + ] + }, + { + "cell_type": "code", + "execution_count": 19, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "" + ] + }, + "execution_count": 19, + "metadata": {}, + "output_type": "execute_result" + }, + { + "data": { + "image/png": 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\n", 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\n", 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\n", + "text/plain": [ + "" + ] + }, + "execution_count": 23, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "ipd.Image(filename=f'../data/train/mel_spectros/{demo_audio}.png')" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "**Fit Label Encoder with the Characters in the Transcripts**" + ] + }, + { + "cell_type": "code", + "execution_count": 24, + "metadata": {}, + "outputs": [], + "source": [ + "char_encoder = fit_label_encoder(transcripts)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "**Encode the Characters in the Transcripts**" + ] + }, + { + "cell_type": "code", + "execution_count": 25, + "metadata": {}, + "outputs": [], + "source": [ + "transcripts_encoded = encode_transcripts(transcripts, char_encoder)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "**Equalize transcript length by padding with spaces**" + ] + }, + { + "cell_type": "code", + "execution_count": 26, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "maximum number of characters in a transcript: 164\n" + ] + } + ], + "source": [ + "enc_aug_transcripts = equalize_transcript_dimension(transcripts_encoded, 20)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## **Prepare Training Set**" + ] + }, + { + "cell_type": "code", + "execution_count": 25, + "metadata": {}, + "outputs": [], + "source": [ + "# X_train, y_train = load_spectrograms_with_transcripts(mfcc_features, \n", + "# enc_aug_transcripts,\n", + "# '../data/train/mfcc_spectros/')\n", + "# X_train.shape, len(y_train)" + ] + }, + { + "cell_type": "code", + "execution_count": 34, + "metadata": {}, + "outputs": [], + "source": [ + "# X_train, y_train = load_spectrograms_with_transcripts_in_batches(mfcc_features, \n", + "# enc_aug_transcripts, 4, 0,\n", + "# '../data/train/mfcc_spectros/')\n", + "# X_train.shape, y_train.shape" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## **Deep Learning Model**" + ] + }, + { + "cell_type": "code", + "execution_count": 27, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "'2.2.0'" + ] + }, + "execution_count": 27, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "import tensorflow as tf\n", + "tf.__version__" + ] + }, + { + "cell_type": "code", + "execution_count": 28, + "metadata": { + "scrolled": true + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Model: \"ocr_model_v1\"\n", + "__________________________________________________________________________________________________\n", + "Layer (type) Output Shape Param # Connected to \n", + "==================================================================================================\n", + "image (InputLayer) [(None, 400, 600, 4) 0 \n", + "__________________________________________________________________________________________________\n", + "Conv1 (Conv2D) (None, 400, 600, 32) 1184 image[0][0] \n", + "__________________________________________________________________________________________________\n", + "pool1 (MaxPooling2D) (None, 200, 300, 32) 0 Conv1[0][0] \n", + "__________________________________________________________________________________________________\n", + "reshape (Reshape) (None, 200, 9600) 0 pool1[0][0] \n", + "__________________________________________________________________________________________________\n", + "dense1 (Dense) (None, 200, 64) 614464 reshape[0][0] \n", + "__________________________________________________________________________________________________\n", + "dropout (Dropout) (None, 200, 64) 0 dense1[0][0] \n", + "__________________________________________________________________________________________________\n", + "bidirectional (Bidirectional) (None, 200, 256) 197632 dropout[0][0] \n", + "__________________________________________________________________________________________________\n", + "bidirectional_1 (Bidirectional) (None, 200, 128) 164352 bidirectional[0][0] \n", + "__________________________________________________________________________________________________\n", + "label (InputLayer) [(None, None)] 0 \n", + "__________________________________________________________________________________________________\n", + "dense2 (Dense) (None, 200, 223) 28767 bidirectional_1[0][0] \n", + "__________________________________________________________________________________________________\n", + "ctc_loss (CTCLayer) (None, 200, 223) 0 label[0][0] \n", + "==================================================================================================\n", + "Total params: 1,006,399\n", + "Trainable params: 1,006,399\n", + "Non-trainable params: 0\n", + "__________________________________________________________________________________________________\n" + ] + } + ], + "source": [ + "model = model_1(char_encoder)\n", + "model.summary()" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## **Train Model**" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "This module loads data_batch_size spectrograms at a time and trains the model for the given number of epochs and with a given training_batch_size." + ] + }, + { + "cell_type": "code", + "execution_count": 46, + "metadata": { + "scrolled": true + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Epoch 1: training batch 0\n", + "2/2 [==============================] - 1s 547ms/step - loss: 9.9330\n", + "Epoch 2: training batch 0\n", + "2/2 [==============================] - 1s 610ms/step - loss: 9.8221\n", + "Epoch 3: training batch 0\n", + "2/2 [==============================] - 1s 552ms/step - loss: 9.5274\n", + "Epoch 4: training batch 0\n", + "2/2 [==============================] - 1s 515ms/step - loss: 9.6992\n", + "Epoch 5: training batch 0\n", + "2/2 [==============================] - 1s 492ms/step - loss: 9.8245\n", + "Epoch 6: training batch 0\n", + "2/2 [==============================] - 1s 487ms/step - loss: 9.5080\n", + "Epoch 7: training batch 0\n", + "2/2 [==============================] - 1s 501ms/step - loss: 9.8121\n", + "Epoch 8: training batch 0\n", + "2/2 [==============================] - 1s 497ms/step - loss: 9.6737\n", + "Epoch 9: training batch 0\n", + "2/2 [==============================] - 1s 522ms/step - loss: 9.3763\n", + "Epoch 10: training batch 0\n", + "2/2 [==============================] - 1s 493ms/step - loss: 9.5555\n", + "Epoch 11: training batch 0\n", + "2/2 [==============================] - 1s 499ms/step - loss: 9.5716\n", + "Epoch 12: training batch 0\n", + "2/2 [==============================] - 1s 495ms/step - loss: 9.2393\n", + "Epoch 13: training batch 0\n", + "2/2 [==============================] - 1s 486ms/step - loss: 9.6243\n", + "Epoch 14: training batch 0\n", + "2/2 [==============================] - 1s 486ms/step - loss: 9.2361\n", + "Epoch 15: training batch 0\n", + "2/2 [==============================] - 1s 490ms/step - loss: 9.4999\n", + "Epoch 16: training batch 0\n", + "2/2 [==============================] - 1s 485ms/step - loss: 13.8971\n", + "Epoch 17: training batch 0\n", + "2/2 [==============================] - 1s 491ms/step - loss: 14.6708\n", + "Epoch 18: training batch 0\n", + "2/2 [==============================] - 1s 548ms/step - loss: 11.6119\n", + "Epoch 19: training batch 0\n", + "2/2 [==============================] - 1s 491ms/step - loss: 12.5770\n", + "Epoch 20: training batch 0\n", + "2/2 [==============================] - 1s 495ms/step - loss: 12.9739\n", + "Epoch 21: training batch 0\n", + "2/2 [==============================] - 1s 527ms/step - loss: 11.9551\n", + "Epoch 22: training batch 0\n", + "2/2 [==============================] - 1s 490ms/step - loss: 12.5808\n", + "Epoch 23: training batch 0\n", + "2/2 [==============================] - 1s 509ms/step - loss: 12.3561\n", + "Epoch 24: training batch 0\n", + "2/2 [==============================] - 1s 498ms/step - loss: 12.3167\n", + "Epoch 25: training batch 0\n", + "2/2 [==============================] - 1s 496ms/step - loss: 11.2651\n", + "Epoch 26: training batch 0\n", + "2/2 [==============================] - 1s 493ms/step - loss: 12.3103\n", + "Epoch 27: training batch 0\n", + "2/2 [==============================] - 1s 493ms/step - loss: 11.6182\n", + "Epoch 28: training batch 0\n", + "2/2 [==============================] - 1s 490ms/step - loss: 11.9412\n", + "Epoch 29: training batch 0\n", + "2/2 [==============================] - 1s 492ms/step - loss: 11.7609\n", + "Epoch 30: training batch 0\n", + "2/2 [==============================] - 1s 496ms/step - loss: 13.0226\n", + "Epoch 31: training batch 0\n", + "2/2 [==============================] - 1s 484ms/step - loss: 11.2963\n", + "Epoch 32: training batch 0\n", + "2/2 [==============================] - 1s 490ms/step - loss: 11.8948\n", + "Epoch 33: training batch 0\n", + "2/2 [==============================] - 1s 503ms/step - loss: 11.5651\n", + "Epoch 34: training batch 0\n", + "2/2 [==============================] - 1s 518ms/step - loss: 10.8037\n", + "Epoch 35: training batch 0\n", + "2/2 [==============================] - 1s 491ms/step - loss: 10.2351\n", + "Epoch 36: training batch 0\n", + "2/2 [==============================] - 1s 483ms/step - loss: 10.4666\n", + "Epoch 37: training batch 0\n", + "2/2 [==============================] - 1s 483ms/step - loss: 10.2531\n", + "Epoch 38: training batch 0\n", + "2/2 [==============================] - 1s 493ms/step - loss: 10.1900\n", + "Epoch 39: training batch 0\n", + "2/2 [==============================] - 1s 484ms/step - loss: 9.7024\n", + "Epoch 40: training batch 0\n", + "2/2 [==============================] - 1s 492ms/step - loss: 9.7461\n", + "Epoch 41: training batch 0\n", + "2/2 [==============================] - 1s 487ms/step - loss: 9.4322\n", + "Epoch 42: training batch 0\n", + "2/2 [==============================] - 1s 485ms/step - loss: 9.3189\n", + "Epoch 43: training batch 0\n", + "2/2 [==============================] - 1s 491ms/step - loss: 9.0496\n", + "Epoch 44: training batch 0\n", + "2/2 [==============================] - 1s 506ms/step - loss: 9.0522\n", + "Epoch 45: training batch 0\n", + "2/2 [==============================] - 1s 498ms/step - loss: 9.0502\n", + "Epoch 46: training batch 0\n", + "2/2 [==============================] - 1s 500ms/step - loss: 8.9161\n", + "Epoch 47: training batch 0\n", + "2/2 [==============================] - 1s 482ms/step - loss: 8.7722\n", + "Epoch 48: training batch 0\n", + "2/2 [==============================] - 1s 509ms/step - loss: 8.7449\n", + "Epoch 49: training batch 0\n", + "2/2 [==============================] - 1s 478ms/step - loss: 8.4528\n", + "Epoch 50: training batch 0\n", + "2/2 [==============================] - 1s 487ms/step - loss: 8.6229\n", + "Epoch 51: training batch 0\n", + "2/2 [==============================] - 1s 495ms/step - loss: 8.6585\n", + "Epoch 52: training batch 0\n", + "2/2 [==============================] - 1s 489ms/step - loss: 8.3667\n", + "Epoch 53: training batch 0\n", + "2/2 [==============================] - 1s 490ms/step - loss: 8.2179\n", + "Epoch 54: training batch 0\n", + "2/2 [==============================] - 1s 484ms/step - loss: 8.2233\n", + "Epoch 55: training batch 0\n", + "2/2 [==============================] - 1s 484ms/step - loss: 8.1195\n", + "Epoch 56: training batch 0\n", + "2/2 [==============================] - 1s 498ms/step - loss: 8.3913\n", + "Epoch 57: training batch 0\n", + "2/2 [==============================] - 1s 489ms/step - loss: 8.1767\n", + "Epoch 58: training batch 0\n", + "2/2 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[==============================] - 1s 573ms/step - loss: 7.4664\n", + "Epoch 77: training batch 0\n", + "2/2 [==============================] - 1s 520ms/step - loss: 8.0552\n", + "Epoch 78: training batch 0\n", + "2/2 [==============================] - 1s 496ms/step - loss: 8.0745\n", + "Epoch 79: training batch 0\n", + "2/2 [==============================] - 1s 484ms/step - loss: 8.6436\n", + "Epoch 80: training batch 0\n", + "2/2 [==============================] - 1s 508ms/step - loss: 8.6005\n", + "Epoch 81: training batch 0\n", + "2/2 [==============================] - 1s 511ms/step - loss: 8.0689\n", + "Epoch 82: training batch 0\n", + "2/2 [==============================] - 1s 555ms/step - loss: 8.4664\n", + "Epoch 83: training batch 0\n", + "2/2 [==============================] - 1s 580ms/step - loss: 8.4581\n", + "Epoch 84: training batch 0\n", + "2/2 [==============================] - 1s 531ms/step - loss: 8.1449\n", + "Epoch 85: training batch 0\n", + "2/2 [==============================] - 1s 596ms/step - loss: 7.6878\n", + "Epoch 86: training batch 0\n", + "2/2 [==============================] - 1s 525ms/step - loss: 7.8021\n", + "Epoch 87: training batch 0\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "2/2 [==============================] - 1s 530ms/step - loss: 8.5794\n", + "Epoch 88: training batch 0\n", + "2/2 [==============================] - 1s 506ms/step - loss: 7.8884\n", + "Epoch 89: training batch 0\n", + "2/2 [==============================] - 1s 516ms/step - loss: 7.9601\n", + "Epoch 90: training batch 0\n", + "2/2 [==============================] - 1s 546ms/step - loss: 7.8547\n", + "Epoch 91: training batch 0\n", + "2/2 [==============================] - 1s 566ms/step - loss: 8.1808\n", + "Epoch 92: training batch 0\n", + "2/2 [==============================] - 1s 668ms/step - loss: 8.2037\n", + "Epoch 93: training batch 0\n", + "2/2 [==============================] - 1s 572ms/step - loss: 7.7512\n", + "Epoch 94: training batch 0\n", + "2/2 [==============================] - 1s 552ms/step - loss: 7.9144\n", + "Epoch 95: training batch 0\n", + "2/2 [==============================] - 1s 487ms/step - loss: 7.5426\n", + "Epoch 96: training batch 0\n", + "2/2 [==============================] - 1s 478ms/step - loss: 7.6200\n", + "Epoch 97: training batch 0\n", + "2/2 [==============================] - 1s 475ms/step - loss: 7.7152\n", + "Epoch 98: training batch 0\n", + "2/2 [==============================] - 1s 472ms/step - loss: 7.2939\n", + "Epoch 99: training batch 0\n", + "2/2 [==============================] - 1s 470ms/step - loss: 7.4473\n", + "Epoch 100: training batch 0\n", + "2/2 [==============================] - 1s 478ms/step - loss: 7.3207\n" + ] + } + ], + "source": [ + "import math\n", + "\n", + "data_batch_size = 9\n", + "training_batch_size = 5\n", + "number_of_epochs = 100\n", + "\n", + "number_of_batches = math.ceil(len(mfcc_features)/data_batch_size)\n", + "\n", + "for i in range(number_of_epochs):\n", + " for j in range(number_of_batches):\n", + " print(f'Epoch {i+1}: training batch {j}')\n", + " X_train, y_train = load_spectrograms_with_transcripts_in_batches(mfcc_features, \n", + " enc_aug_transcripts, data_batch_size, j,\n", + " '../data/train/mel_spectros/')\n", + " history = model.fit([X_train, y_train], batch_size = training_batch_size, epochs = 1)\n", + "with mlflow.start_run() as run:\n", + " mlflow.log_metric(\"ctc_loss\", history.history['loss'][-1])" + ] + }, + { + "cell_type": "code", + "execution_count": 47, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "pridicted: የ ጠመንኩስ ተ ና አ\n", + "actual: የ ጠመንጃ ተኩስ ተከፈተ ና አ\n" + ] + } + ], + "source": [ + "predicted = model.predict([X_train,y_train])\n", + "predicted_trans = decode_predicted(predicted, char_encoder)\n", + "real_trans = [''.join(char_encoder.inverse_transform(y)) for y in y_train]\n", + "print(\"pridicted:\",predicted_trans[1])\n", + "print(\"actual:\",real_trans[1])" + ] + }, + { + "cell_type": "code", + "execution_count": 48, + "metadata": {}, + "outputs": [], + "source": [ + "#[np.argmax(pred) for pred in predicted[0]]" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [] + } + ], + "metadata": { + "kernelspec": { + "display_name": "Python 3", + "language": "python", + "name": "python3" + }, + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 3 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython3", + "version": "3.7.1" + } + }, + "nbformat": 4, + "nbformat_minor": 2 +} diff --git a/notebooks/.ipynb_checkpoints/ModelBuilding-checkpoint.ipynb b/notebooks/.ipynb_checkpoints/ModelBuilding-checkpoint.ipynb new file mode 100755 index 0000000..9133400 --- /dev/null +++ b/notebooks/.ipynb_checkpoints/ModelBuilding-checkpoint.ipynb @@ -0,0 +1,2312 @@ +{ + "cells": [ + { + "cell_type": "code", + "execution_count": 42, + "id": "c34a6094", + "metadata": { + "executionInfo": { + "elapsed": 2895, + "status": "ok", + "timestamp": 1628699389341, + "user": { + "displayName": "Daniel Zelalem", + "photoUrl": "", + "userId": "17933366000899068375" + }, + "user_tz": -180 + }, + "id": "c34a6094" + }, + "outputs": [], + "source": [ + "import os\n", + "import sys\n", + "sys.path.append(os.path.abspath(os.path.join('../scripts')))\n", + "sys.path.append(os.path.abspath(os.path.join('./scripts')))\n", + "import pandas as pd\n", + "import IPython.display as ipd\n", + "import matplotlib.pyplot as plt\n", + "import numpy as np\n", + "from scipy.io import wavfile #for audio processing\n", + "import os\n", + "import pickle\n", + "import pandas as pd\n", + "from collections import Counter\n", + "import librosa\n", + "import tensorflow as tf\n", + "from tensorflow.keras.models import Model, Sequential\n", + "from tensorflow.keras.layers import * \n", + "from tensorflow.keras.callbacks import Callback, ModelCheckpoint\n", + "from tensorflow.keras.preprocessing.sequence import pad_sequences\n", + "from tensorflow.keras.optimizers import SGD, Adam, RMSprop\n", + "from tensorflow.keras import backend as K\n", + "from jiwer import wer\n", + "import random\n", + "\n", + "\n", + "import mlflow" + ] + }, + { + "cell_type": "code", + "execution_count": 80, + "id": "6d1cf366", + "metadata": {}, + "outputs": [], + "source": [ + "import warnings\n", + "warnings.filterwarnings('ignore')" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "14DrOASH1-ag", + "metadata": { + "executionInfo": { + "elapsed": 1707, + "status": "ok", + "timestamp": 1628689887618, + "user": { + "displayName": "Daniel Zelalem", + "photoUrl": "", + "userId": "17933366000899068375" + }, + "user_tz": -180 + }, + "id": "14DrOASH1-ag" + }, + "outputs": [], + "source": [ + "# !ln -s ./drive/MyDrive/SST/data/ ./\n", + "# !ln -s ./drive/MyDrive/SST/scripts/* ./" + ] + }, + { + "cell_type": "code", + "execution_count": 3, + "id": "IQLOtaNr2GSB", + "metadata": { + "colab": { + "base_uri": "https://localhost:8080/" + }, + "executionInfo": { + "elapsed": 625, + "status": "ok", + "timestamp": 1628689876631, + "user": { + "displayName": "Daniel Zelalem", + "photoUrl": "", + "userId": "17933366000899068375" + }, + "user_tz": -180 + }, + "id": "IQLOtaNr2GSB", + "outputId": "05b3d77e-6ba7-43fc-8256-92e5e2539d74" + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Drive already mounted at /content/drive; to attempt to forcibly remount, call drive.mount(\"/content/drive\", force_remount=True).\n" + ] + } + ], + "source": [ + "# from google.colab import drive\n", + "# drive.mount('/content/drive')" + ] + }, + { + "cell_type": "code", + "execution_count": 32, + "id": "3f315bab", + "metadata": {}, + "outputs": [], + "source": [ + "# !pip3 install jiwer\n" + ] + }, + { + "cell_type": "code", + "execution_count": 43, + "id": "acf88600", + "metadata": { + "executionInfo": { + "elapsed": 981, + "status": "ok", + "timestamp": 1628699393166, + "user": { + "displayName": "Daniel Zelalem", + "photoUrl": "", + "userId": "17933366000899068375" + }, + "user_tz": -180 + }, + "id": "acf88600" + }, + "outputs": [], + "source": [ + "import helper\n" + ] + }, + { + "cell_type": "code", + "execution_count": 60, + "id": "4f219ca9", + "metadata": { + "executionInfo": { + "elapsed": 4, + "status": "ok", + "timestamp": 1628699394673, + "user": { + "displayName": "Daniel Zelalem", + "photoUrl": "", + "userId": "17933366000899068375" + }, + "user_tz": -180 + }, + "id": "4f219ca9" + }, + "outputs": [], + "source": [ + "from data_generator import DataGenerator\n", + "from tokenizer import Tokenizer\n", + "from logspectrorgam import LogMelSpectrogram\n", + "from ctc_loss import CTC_loss\n", + "from model2 import simple_rnn_model, CNN_net, BidirectionalRNN2, cnn_rnn_model" + ] + }, + { + "cell_type": "markdown", + "id": "f80ab45b", + "metadata": {}, + "source": [ + "### Defining hop_size for our audio features " + ] + }, + { + "cell_type": "markdown", + "id": "890e33e0", + "metadata": {}, + "source": [ + "### Init CTC_loss class" + ] + }, + { + "cell_type": "code", + "execution_count": 46, + "id": "e464cd2c", + "metadata": {}, + "outputs": [], + "source": [ + "frame_step = 256\n", + "ctc = CTC_loss(frame_step)" + ] + }, + { + "cell_type": "markdown", + "id": "d77b7745", + "metadata": {}, + "source": [ + "### Defination of preprocessing model" + ] + }, + { + "cell_type": "markdown", + "id": "05f2b14a", + "metadata": {}, + "source": [ + "- This model uses LogMelSpectrogram to generate features of an audio data at run time\n", + "- We will use this model as a part of our speech to text models to convert audio data to log melspectrogram" + ] + }, + { + "cell_type": "code", + "execution_count": 47, + "id": "09c8fa57", + "metadata": { + "executionInfo": { + "elapsed": 623, + "status": "ok", + "timestamp": 1628699400742, + "user": { + "displayName": "Daniel Zelalem", + "photoUrl": "", + "userId": "17933366000899068375" + }, + "user_tz": -180 + }, + "id": "09c8fa57" + }, + "outputs": [], + "source": [ + "def preprocessin_model(sample_rate, fft_size, frame_step, n_mels, mfcc=False):\n", + "\n", + " input_data = Input(name='input', shape=(None,), dtype=\"float32\")\n", + " featLayer = LogMelSpectrogram(\n", + " fft_size=fft_size,\n", + " hop_size=frame_step,\n", + " n_mels=n_mels,\n", + " \n", + " sample_rate=sample_rate,\n", + " f_min=0.0,\n", + " \n", + " f_max=int(sample_rate / 2),\n", + " )(input_data)\n", + " \n", + " x = BatchNormalization(axis=2)(featLayer)\n", + " model = Model(inputs=input_data, outputs=x, name=\"preprocessin_model\")\n", + "\n", + " return model" + ] + }, + { + "cell_type": "markdown", + "id": "6b3b998d", + "metadata": {}, + "source": [ + "### Model trainer function" + ] + }, + { + "cell_type": "code", + "execution_count": 48, + "id": "7abeb89a", + "metadata": { + "executionInfo": { + "elapsed": 542, + "status": "ok", + "timestamp": 1628699406370, + "user": { + "displayName": "Daniel Zelalem", + "photoUrl": "", + "userId": "17933366000899068375" + }, + "user_tz": -180 + }, + "id": "7abeb89a" + }, + "outputs": [], + "source": [ + "def train(model_builder, \n", + " data_gen,\n", + " batch_size = 32,\n", + " epochs=20, \n", + " verbose=1,\n", + " save_path=\"../models/model.h5\",\n", + " optimizer=SGD(learning_rate=0.01, decay=1e-6, momentum=0.9, nesterov=True, clipnorm=5),\n", + " ): \n", + " \n", + " model = ctc.add_ctc_loss(model_builder)\n", + "\n", + " checkpointer = ModelCheckpoint(filepath=save_path, verbose=0)\n", + " model.compile(loss={'ctc': lambda y_true, y_pred: y_pred}, optimizer=optimizer)\n", + " print(model.summary())\n", + "\n", + "\n", + " hist = model.fit_generator(generator=data_gen,\n", + " callbacks=[checkpointer],\n", + "\n", + " epochs=epochs,\n", + " verbose=verbose, \n", + " use_multiprocessing=False)\n", + " return model" + ] + }, + { + "cell_type": "markdown", + "id": "596a2dcf", + "metadata": {}, + "source": [ + "### Loading our audio data and translation data from pickle file\n", + "\n", + "- audio_obj is a key value pair dict where the key is the file name of the audio and value is the audio data\n", + "- translation_obj is a key value pair dict where the key is the file name of the audio and value is the transcription \n" + ] + }, + { + "cell_type": "markdown", + "id": "12493b40", + "metadata": {}, + "source": [ + "#### The metadata is a pandas dataframe which holds meta data information for each audio" + ] + }, + { + "cell_type": "code", + "execution_count": 49, + "id": "3f654a55", + "metadata": { + "colab": { + "base_uri": "https://localhost:8080/" + }, + "executionInfo": { + "elapsed": 2912, + "status": "ok", + "timestamp": 1628699411261, + "user": { + "displayName": "Daniel Zelalem", + "photoUrl": "", + "userId": "17933366000899068375" + }, + "user_tz": -180 + }, + "id": "3f654a55", + "outputId": "c01d68d8-1b78-41f1-ea6f-6345db44bff8" + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "file read as csv\n" + ] + } + ], + "source": [ + "\n", + "translation_obj = helper.read_obj(\"../data/translation_dict.pkl\")\n", + "audio_obj = helper.read_obj(\"../data/audio_dict.pkl\")\n", + "meta_data = helper.read_csv(\"../data/meta_data.csv\")\n" + ] + }, + { + "cell_type": "markdown", + "id": "94df7a3f", + "metadata": {}, + "source": [ + "#### Sorting the audios based on the duration using the metadata" + ] + }, + { + "cell_type": "code", + "execution_count": 50, + "id": "xO7gtHd07skA", + "metadata": { + "colab": { + "base_uri": "https://localhost:8080/", + "height": 504 + }, + "executionInfo": { + "elapsed": 11, + "status": "ok", + "timestamp": 1628699411262, + "user": { + "displayName": "Daniel Zelalem", + "photoUrl": "", + "userId": "17933366000899068375" + }, + "user_tz": -180 + }, + "id": "xO7gtHd07skA", + "outputId": "028c0876-dfa9-45f3-d192-5297099bddf5" + }, + "outputs": [ + { + "data": { + "text/html": [ + "
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translationlabelchannelsample_rateduration
4133እኛ ም እ ኮ ፉትቦል ን እንወዳ ለ ንtr_3933_tr40034180002.048
1476አሸናፊ ፈጣን ተጨዋች ነውtr_1541_tr16042180002.048
408እንስራ ው ተ ሸነቆረtr_10369_tr100091180002.176
73ጥያቄ ያችን ጆንያ ሙሉ ነውtr_10067_tr098029180002.176
3574ኳስ ጨዋታ ኳስ ነውtr_342_tr04042180002.176
..................
2614በ አውሮፕላኗ ተመትቶ መውደቅ ሳቢያ ዜጐቻቸው ን ላ ጡት የ ብሪታኒያ ና ...tr_2566_tr260671800020.352
1652ሁሴን አይዲድ እንደ ገለጹት ኢትዮጵያ ሁኔታዎች ከ ተመቻቹ ላት ሶማሊያ ን...tr_16_tr010161800020.736
2222ከ ግዛታቸው ዋ ና ከተማ ጋሪ ስ ሆነው በ ስልክ ሚስተር ሞሪስ ከ ስደተኞ...tr_2212_tr230131800020.992
2608የተ ለቀቁት ምርኮኞች በ አካባቢያቸው ሰላማዊ ኑሮ እንዲ ኖሩ የ ትራንስፖ...tr_2560_tr260611800021.120
2613የ ትምህርት ደረጃቸው ንና የ አገልግሎት ሁኔታ ቸውን ስን መረምር የሚ ደ...tr_2565_tr260661800022.784
\n", + "

5000 rows × 5 columns

\n", + "
" + ], + "text/plain": [ + " translation label \\\n", + "4133 እኛ ም እ ኮ ፉትቦል ን እንወዳ ለ ን tr_3933_tr40034 \n", + "1476 አሸናፊ ፈጣን ተጨዋች ነው tr_1541_tr16042 \n", + "408 እንስራ ው ተ ሸነቆረ tr_10369_tr100091 \n", + "73 ጥያቄ ያችን ጆንያ ሙሉ ነው tr_10067_tr098029 \n", + "3574 ኳስ ጨዋታ ኳስ ነው tr_342_tr04042 \n", + "... ... ... \n", + "2614 በ አውሮፕላኗ ተመትቶ መውደቅ ሳቢያ ዜጐቻቸው ን ላ ጡት የ ብሪታኒያ ና ... tr_2566_tr26067 \n", + "1652 ሁሴን አይዲድ እንደ ገለጹት ኢትዮጵያ ሁኔታዎች ከ ተመቻቹ ላት ሶማሊያ ን... tr_16_tr01016 \n", + "2222 ከ ግዛታቸው ዋ ና ከተማ ጋሪ ስ ሆነው በ ስልክ ሚስተር ሞሪስ ከ ስደተኞ... tr_2212_tr23013 \n", + "2608 የተ ለቀቁት ምርኮኞች በ አካባቢያቸው ሰላማዊ ኑሮ እንዲ ኖሩ የ ትራንስፖ... tr_2560_tr26061 \n", + "2613 የ ትምህርት ደረጃቸው ንና የ አገልግሎት ሁኔታ ቸውን ስን መረምር የሚ ደ... tr_2565_tr26066 \n", + "\n", + " channel sample_rate duration \n", + "4133 1 8000 2.048 \n", + "1476 1 8000 2.048 \n", + "408 1 8000 2.176 \n", + "73 1 8000 2.176 \n", + "3574 1 8000 2.176 \n", + "... ... ... ... \n", + "2614 1 8000 20.352 \n", + "1652 1 8000 20.736 \n", + "2222 1 8000 20.992 \n", + "2608 1 8000 21.120 \n", + "2613 1 8000 22.784 \n", + "\n", + "[5000 rows x 5 columns]" + ] + }, + "execution_count": 50, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "sorted_metadata = meta_data.sort_values(by=\"duration\")\n", + "labels = sorted_metadata['label'].to_list()\n", + "sorted_metadata" + ] + }, + { + "cell_type": "markdown", + "id": "5cf1a5dc", + "metadata": {}, + "source": [ + "#### extracting audios and translations in lists" + ] + }, + { + "cell_type": "code", + "execution_count": 51, + "id": "ef6a4e11", + "metadata": { + "executionInfo": { + "elapsed": 553, + "status": "ok", + "timestamp": 1628699415091, + "user": { + "displayName": "Daniel Zelalem", + "photoUrl": "", + "userId": "17933366000899068375" + }, + "user_tz": -180 + }, + "id": "ef6a4e11" + }, + "outputs": [], + "source": [ + "audios = []\n", + "for label in labels:\n", + " audios.append(audio_obj[label][0])\n", + " \n", + "translations = []\n", + "for label in labels:\n", + " translations.append(translation_obj[label])" + ] + }, + { + "cell_type": "markdown", + "id": "a11460e9", + "metadata": {}, + "source": [ + "### Build function" + ] + }, + { + "cell_type": "markdown", + "id": "f7842c5d", + "metadata": {}, + "source": [ + "- Build function takes a speech model and a preprocessing model (a model that gives melespectrogram features) and build them into a single speech model" + ] + }, + { + "cell_type": "code", + "execution_count": 52, + "id": "3675d659", + "metadata": { + "executionInfo": { + "elapsed": 4, + "status": "ok", + "timestamp": 1628699416838, + "user": { + "displayName": "Daniel Zelalem", + "photoUrl": "", + "userId": "17933366000899068375" + }, + "user_tz": -180 + }, + "id": "3675d659" + }, + "outputs": [], + "source": [ + "def build_model(output_dim, custom_model, preprocess_model, mfcc=False, calc=None):\n", + "\n", + " input_audios = Input(name='the_input', shape=(None,))\n", + " pre = preprocess_model(input_audios)\n", + " pre = tf.squeeze(pre, [3])\n", + "\n", + " y_pred = custom_model(pre)\n", + " model = Model(inputs=input_audios, outputs=y_pred, name=\"model_builder\")\n", + " model.output_length = calc\n", + "\n", + " return model" + ] + }, + { + "cell_type": "markdown", + "id": "7358e4ae", + "metadata": {}, + "source": [ + "### Predict function" + ] + }, + { + "cell_type": "code", + "execution_count": 53, + "id": "CKKxhFiFozcF", + "metadata": { + "executionInfo": { + "elapsed": 3, + "status": "ok", + "timestamp": 1628699418994, + "user": { + "displayName": "Daniel Zelalem", + "photoUrl": "", + "userId": "17933366000899068375" + }, + "user_tz": -180 + }, + "id": "CKKxhFiFozcF" + }, + "outputs": [], + "source": [ + "def predict(model, audio, tokenizer, int_to_char, actual=None):\n", + " \n", + " pred_audios = tf.convert_to_tensor([audio])\n", + " \n", + " y_pred = model.predict(pred_audios)\n", + "\n", + " input_shape = tf.keras.backend.shape(y_pred)\n", + " input_length = tf.ones(shape=input_shape[0]) * tf.keras.backend.cast(input_shape[1], 'float32')\n", + " prediction = tf.keras.backend.ctc_decode(y_pred, input_length, greedy=False)[0][0]\n", + " \n", + " pred = K.eval(prediction).flatten().tolist()\n", + " pred = [i for i in pred if i != -1]\n", + " \n", + " predicted_text = tokenizer.decode_text(pred, int_to_char)\n", + " \n", + " error = None\n", + " if actual != None:\n", + " error = wer(actual, predicted_text)\n", + " \n", + " return predicted_text, error" + ] + }, + { + "cell_type": "markdown", + "id": "73164049", + "metadata": {}, + "source": [ + "### Init our translation tokenizer and build a charchter mapping dict" + ] + }, + { + "cell_type": "code", + "execution_count": 54, + "id": "107cd033", + "metadata": { + "colab": { + "base_uri": "https://localhost:8080/" + }, + "executionInfo": { + "elapsed": 725, + "status": "ok", + "timestamp": 1628699421859, + "user": { + "displayName": "Daniel Zelalem", + "photoUrl": "", + "userId": "17933366000899068375" + }, + "user_tz": -180 + }, + "id": "107cd033", + "outputId": "2803c0e0-8fa0-4a94-948a-caa10db28729" + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "sample snt: እኛ ም እ ኮ ፉትቦል ን እንወዳ ለ ን\n", + "encoded snt: [13, 74, 1, 16, 1, 13, 1, 67, 1, 142, 3, 122, 12, 1, 2, 1, 13, 2, 37, 39, 1, 11, 1, 2]\n", + "decoed snt: እኛ ም እ ኮ ፉትቦል ን እንወዳ ለ ን\n" + ] + } + ], + "source": [ + "tokenizer = Tokenizer(translations)\n", + "int_to_char, char_to_int = tokenizer.build_dict()\n", + "sample = translations[0]\n", + "encoded = tokenizer.encode(sample, char_to_int)\n", + "decoded = tokenizer.decode_text(encoded, int_to_char)\n", + "\n", + "print(f\"sample snt: {sample}\")\n", + "print(f\"encoded snt: {encoded}\")\n", + "print(f\"decoed snt: {decoded}\")" + ] + }, + { + "cell_type": "markdown", + "id": "f7a1d899", + "metadata": {}, + "source": [ + "### init our variables" + ] + }, + { + "cell_type": "code", + "execution_count": 55, + "id": "bdea9379", + "metadata": { + "executionInfo": { + "elapsed": 3, + "status": "ok", + "timestamp": 1628699424858, + "user": { + "displayName": "Daniel Zelalem", + "photoUrl": "", + "userId": "17933366000899068375" + }, + "user_tz": -180 + }, + "id": "bdea9379" + }, + "outputs": [], + "source": [ + "\n", + "sample_rate = 8000\n", + "fft_size = 512\n", + "frame_step = 256\n", + "n_mels = 128\n", + "\n", + "batch_size = 100\n", + "epochs = 20\n", + "data_len = len(translations)\n", + "output_dim = len(char_to_int) + 2\n" + ] + }, + { + "cell_type": "markdown", + "id": "1c3f529d", + "metadata": {}, + "source": [ + "### Init our DataGenerator and build our preprocessing model" + ] + }, + { + "cell_type": "code", + "execution_count": 57, + "id": "cb25dda1", + "metadata": { + "colab": { + "base_uri": "https://localhost:8080/" + }, + "executionInfo": { + "elapsed": 1693, + "status": "ok", + "timestamp": 1628699431823, + "user": { + "displayName": "Daniel Zelalem", + "photoUrl": "", + "userId": "17933366000899068375" + }, + "user_tz": -180 + }, + "id": "cb25dda1", + "outputId": "10156bd8-68dd-4ae4-fda4-c8ef21311ec1" + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Model: \"preprocessin_model\"\n", + "_________________________________________________________________\n", + "Layer (type) Output Shape Param # \n", + "=================================================================\n", + "input (InputLayer) [(None, None)] 0 \n", + "_________________________________________________________________\n", + "log_mel_spectrogram_1 (LogMe (None, None, 128, 1) 0 \n", + "_________________________________________________________________\n", + "batch_normalization_1 (Batch (None, None, 128, 1) 512 \n", + "=================================================================\n", + "Total params: 512\n", + "Trainable params: 256\n", + "Non-trainable params: 256\n", + "_________________________________________________________________\n" + ] + } + ], + "source": [ + "dg = DataGenerator(translations, audios, batch_size, shuffle=True)\n", + "preprocess_model = preprocessin_model(sample_rate, fft_size, frame_step, n_mels)\n", + "preprocess_model.summary()" + ] + }, + { + "cell_type": "markdown", + "id": "5cb991e5", + "metadata": {}, + "source": [ + "### checking log melespectorgram of sample audio data using our preprocessing model" + ] + }, + { + "cell_type": "code", + "execution_count": 22, + "id": "ZdGw4xLn2L34", + "metadata": { + "colab": { + "base_uri": "https://localhost:8080/", + "height": 289 + }, + "executionInfo": { + "elapsed": 3181, + "status": "ok", + "timestamp": 1628699180083, + "user": { + "displayName": "Daniel Zelalem", + "photoUrl": "", + "userId": "17933366000899068375" + }, + "user_tz": -180 + }, + "id": "ZdGw4xLn2L34", + "outputId": "c52302db-2df7-4ed7-ba14-351efc8ae59f" + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "(1, 65536)\n" + ] + }, + { + "data": { + "text/plain": [ + "(1, 255, 128, 1)" + ] + }, + "metadata": { + "tags": [] + }, + "output_type": "display_data" + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "char_len 96\n" + ] + }, + { + "data": { + "image/png": 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\n", + "text/plain": [ + "
" + ] + }, + "metadata": { + "tags": [] + }, + "output_type": "display_data" + } + ], + "source": [ + "\n", + "\n", + "sample_audio = dg[0][0]['the_input'][0].numpy()\n", + "sample_lbl = dg[0][0]['the_labels'][0].numpy()\n", + "\n", + "a = np.zeros((1, len(sample_audio)))\n", + "a[0, ] = sample_audio\n", + "print(a.shape)\n", + "pred = preprocess_model.predict(a)\n", + "fig, ax = plt.subplots(figsize=(16, 4))\n", + "display(pred.shape)\n", + "pred = pred[0, :, :, 0]\n", + "librosa.display.specshow(pred.T, sr=8000, hop_length=128, cmap=\"jet\")\n", + "print(\"char_len\", len(sample_lbl))" + ] + }, + { + "cell_type": "code", + "execution_count": 27, + "id": "XeV4Uu6eCxRr", + "metadata": { + "colab": { + "base_uri": "https://localhost:8080/", + "height": 289 + }, + "executionInfo": { + "elapsed": 778, + "status": "ok", + "timestamp": 1628679511029, + "user": { + "displayName": "Daniel Zelalem", + "photoUrl": "", + "userId": "17933366000899068375" + }, + "user_tz": -180 + }, + "id": "XeV4Uu6eCxRr", + "outputId": "5f1be4d3-0be4-46fb-a9f5-7fde8586829a" + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "(1, 34816)\n" + ] + }, + { + "data": { + "text/plain": [ + "(1, 135, 128, 1)" + ] + }, + "metadata": { + "tags": [] + }, + "output_type": "display_data" + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "char_len 44\n" + ] + }, + { + "data": { + "image/png": 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\n", + "text/plain": [ + "
" + ] + }, + "metadata": { + "tags": [] + }, + "output_type": "display_data" + } + ], + "source": [ + "\n", + "sample_audio = dg[49][0]['the_input'][-1].numpy()\n", + "sample_lbl = dg[49][0]['the_labels'][-1].numpy()\n", + "\n", + "a = np.zeros((1, len(sample_audio)))\n", + "a[0, ] = sample_audio\n", + "print(a.shape)\n", + "pred = preprocess_model.predict(a)\n", + "fig, ax = plt.subplots(figsize=(16, 4))\n", + "display(pred.shape)\n", + "pred = pred[0, :, :, 0]\n", + "librosa.display.specshow(pred.T, sr=8000, hop_length=128, cmap=\"jet\")\n", + "print(\"char_len\", len(sample_lbl))" + ] + }, + { + "cell_type": "markdown", + "id": "5b51dccc", + "metadata": { + "id": "myDkV2oA2YY5" + }, + "source": [ + "### 1. Simple RNN model for speech to text" + ] + }, + { + "cell_type": "markdown", + "id": "ddb0e4cd", + "metadata": {}, + "source": [ + "#### creating a simple rnn model" + ] + }, + { + "cell_type": "code", + "execution_count": 62, + "id": "e43ae703", + "metadata": { + "colab": { + "base_uri": "https://localhost:8080/" + }, + "executionInfo": { + "elapsed": 610, + "status": "ok", + "timestamp": 1628679533946, + "user": { + "displayName": "Daniel Zelalem", + "photoUrl": "", + "userId": "17933366000899068375" + }, + "user_tz": -180 + }, + "id": "e43ae703", + "outputId": "7785164e-5e79-4509-f847-fa4735f8ad84" + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Model: \"simple_rnn_model\"\n", + "_________________________________________________________________\n", + "Layer (type) Output Shape Param # \n", + "=================================================================\n", + "the_input (InputLayer) [(None, None, 128)] 0 \n", + "_________________________________________________________________\n", + "rnn (GRU) (None, None, 223) 236157 \n", + "_________________________________________________________________\n", + "softmax (Activation) (None, None, 223) 0 \n", + "=================================================================\n", + "Total params: 236,157\n", + "Trainable params: 236,157\n", + "Non-trainable params: 0\n", + "_________________________________________________________________\n" + ] + } + ], + "source": [ + "speech_simple_rnn = simple_rnn_model(n_mels, output_dim)\n", + "speech_simple_rnn.summary()" + ] + }, + { + "cell_type": "markdown", + "id": "dfac123c", + "metadata": {}, + "source": [ + "#### Building a simple rnn moel by stacking preprocessin_model and speech_simple_rnn" + ] + }, + { + "cell_type": "code", + "execution_count": 65, + "id": "b8e25a3f", + "metadata": { + "colab": { + "base_uri": "https://localhost:8080/" + }, + "executionInfo": { + "elapsed": 412, + "status": "ok", + "timestamp": 1628679536551, + "user": { + "displayName": "Daniel Zelalem", + "photoUrl": "", + "userId": "17933366000899068375" + }, + "user_tz": -180 + }, + "id": "b8e25a3f", + "outputId": "ef5342d7-b372-4a01-aa3b-b7125ba742e0" + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Model: \"model_builder\"\n", + "_________________________________________________________________\n", + "Layer (type) Output Shape Param # \n", + "=================================================================\n", + "the_input (InputLayer) [(None, None)] 0 \n", + "_________________________________________________________________\n", + "preprocessin_model (Function (None, None, 128, 1) 512 \n", + "_________________________________________________________________\n", + "tf.compat.v1.squeeze_3 (TFOp (None, None, 128) 0 \n", + "_________________________________________________________________\n", + "simple_rnn_model (Functional (None, None, 223) 236157 \n", + "=================================================================\n", + "Total params: 236,669\n", + "Trainable params: 236,413\n", + "Non-trainable params: 256\n", + "_________________________________________________________________\n" + ] + } + ], + "source": [ + "simple_rnn_speech_model = build_model(output_dim, speech_simple_rnn, preprocess_model)\n", + "simple_rnn_speech_model.summary()" + ] + }, + { + "cell_type": "markdown", + "id": "5ebd5074", + "metadata": {}, + "source": [ + "#### Training" + ] + }, + { + "cell_type": "code", + "execution_count": 29, + "id": "01feee42", + "metadata": { + "colab": { + "base_uri": "https://localhost:8080/" + }, + "executionInfo": { + "elapsed": 246858, + "status": "ok", + "timestamp": 1628679787023, + "user": { + "displayName": "Daniel Zelalem", + "photoUrl": "", + "userId": "17933366000899068375" + }, + "user_tz": -180 + }, + "id": "01feee42", + "outputId": "41153299-6698-4e00-a9fe-218f47b93b90" + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Model: \"model\"\n", + "__________________________________________________________________________________________________\n", + "Layer (type) Output Shape Param # Connected to \n", + "==================================================================================================\n", + "the_input (InputLayer) [(None, None)] 0 \n", + "__________________________________________________________________________________________________\n", + "preprocessin_model (Functional) (None, None, 128, 1) 512 the_input[0][0] \n", + "__________________________________________________________________________________________________\n", + "tf.compat.v1.squeeze (TFOpLambd (None, None, 128) 0 preprocessin_model[0][0] \n", + "__________________________________________________________________________________________________\n", + "input_length (InputLayer) [(None, 1)] 0 \n", + "__________________________________________________________________________________________________\n", + "simple_rnn_model (Functional) (None, None, 223) 236157 tf.compat.v1.squeeze[0][0] \n", + "__________________________________________________________________________________________________\n", + "the_labels (InputLayer) [(None, None)] 0 \n", + "__________________________________________________________________________________________________\n", + "lambda (Lambda) (None, 1) 0 input_length[0][0] \n", + "__________________________________________________________________________________________________\n", + "label_length (InputLayer) [(None, 1)] 0 \n", + "__________________________________________________________________________________________________\n", + "ctc (Lambda) (None, 1) 0 simple_rnn_model[0][0] \n", + " the_labels[0][0] \n", + " lambda[0][0] \n", + " label_length[0][0] \n", + "==================================================================================================\n", + "Total params: 236,669\n", + "Trainable params: 236,413\n", + "Non-trainable params: 256\n", + "__________________________________________________________________________________________________\n", + "None\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "/Library/Frameworks/Python.framework/Versions/3.9/lib/python3.9/site-packages/tensorflow/python/keras/engine/training.py:1940: UserWarning: `Model.fit_generator` is deprecated and will be removed in a future version. Please use `Model.fit`, which supports generators.\n", + " warnings.warn('`Model.fit_generator` is deprecated and '\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Epoch 1/20\n", + "50/50 [==============================] - 74s 1s/step - loss: 741.7604\n", + "Epoch 2/20\n", + "50/50 [==============================] - 71s 1s/step - loss: 682.7922\n", + "Epoch 3/20\n", + "50/50 [==============================] - 78s 2s/step - loss: 682.0422\n", + "Epoch 4/20\n", + "50/50 [==============================] - 85s 2s/step - loss: 681.6732\n", + "Epoch 5/20\n", + "50/50 [==============================] - 85s 2s/step - loss: 681.3718\n", + "Epoch 6/20\n", + "50/50 [==============================] - 77s 2s/step - loss: 681.1526\n", + "Epoch 7/20\n", + "50/50 [==============================] - 73s 1s/step - loss: 680.9636\n", + "Epoch 8/20\n", + "50/50 [==============================] - 75s 2s/step - loss: 680.7802\n", + "Epoch 9/20\n", + "50/50 [==============================] - 68s 1s/step - loss: 680.6910\n", + "Epoch 10/20\n", + "50/50 [==============================] - 69s 1s/step - loss: 680.3199\n", + "Epoch 11/20\n", + "50/50 [==============================] - 87s 2s/step - loss: 680.0570\n", + "Epoch 12/20\n", + "50/50 [==============================] - 74s 1s/step - loss: 679.8464\n", + "Epoch 13/20\n", + "50/50 [==============================] - 92s 2s/step - loss: 679.8269\n", + "Epoch 14/20\n", + "50/50 [==============================] - 77s 2s/step - loss: 679.6784\n", + "Epoch 15/20\n", + "50/50 [==============================] - 71s 1s/step - loss: 679.6099\n", + "Epoch 16/20\n", + "50/50 [==============================] - 70s 1s/step - loss: 679.4676\n", + "Epoch 17/20\n", + "50/50 [==============================] - 69s 1s/step - loss: 679.3322\n", + "Epoch 18/20\n", + "50/50 [==============================] - 69s 1s/step - loss: 679.2448\n", + "Epoch 19/20\n", + "50/50 [==============================] - 76s 2s/step - loss: 679.2038\n", + "Epoch 20/20\n", + "50/50 [==============================] - 72s 1s/step - loss: 679.1887\n" + ] + }, + { + "data": { + "text/plain": [ + "" + ] + }, + "execution_count": 29, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "# mlflow.set_experiment('Speech Model-RNN-baseline')\n", + "# mlflow.tensorflow.autolog()\n", + "train(simple_rnn_speech_model, dg, epochs=20, save_path=\"../models/simple_rnn_model.h5\", batch_size=batch_size)" + ] + }, + { + "cell_type": "markdown", + "id": "603fdd9d", + "metadata": {}, + "source": [ + "#### Predicting using simple rnn model" + ] + }, + { + "cell_type": "code", + "execution_count": 69, + "id": "5qmBzRhlmmgh", + "metadata": { + "colab": { + "base_uri": "https://localhost:8080/" + }, + "executionInfo": { + "elapsed": 1256, + "status": "ok", + "timestamp": 1628679833252, + "user": { + "displayName": "Daniel Zelalem", + "photoUrl": "", + "userId": "17933366000899068375" + }, + "user_tz": -180 + }, + "id": "5qmBzRhlmmgh", + "outputId": "9ae51d9d-88f5-41c3-c645-22e1abbccc0b" + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "actual በ ባህል በ ቋንቋ አንድ ናቸው\n", + "predicted ተ ተ ን ያ ያ አ አ አ ን ንር ን አ አ አ ን \n", + "WER: 2.5\n" + ] + } + ], + "source": [ + "\n", + "simple_rnn_speech_model.load_weights(\"../models/simple_rnn_model.h5\")\n", + "\n", + "\n", + "actual_translation = translations[10]\n", + "sample_test_audio = audios[0]\n", + "predicted, error = predict(simple_rnn_speech_model, sample_test_audio , tokenizer, int_to_char, actual=actual_translation)\n", + "\n", + "print(\"actual\", actual_translation)\n", + "print(\"predicted\", predicted)\n", + "print(\"WER: \", error)\n" + ] + }, + { + "cell_type": "code", + "execution_count": 19, + "id": "X1fMYpsW-3M6", + "metadata": { + "executionInfo": { + "elapsed": 779, + "status": "ok", + "timestamp": 1628699442061, + "user": { + "displayName": "Daniel Zelalem", + "photoUrl": "", + "userId": "17933366000899068375" + }, + "user_tz": -180 + }, + "id": "X1fMYpsW-3M6" + }, + "outputs": [], + "source": [ + "# def ctc_lambda_func(args):\n", + "# y_pred, labels, input_length, label_length = args\n", + "# return K.ctc_batch_cost(labels, y_pred, input_length, label_length)\n", + "\n", + "\n", + "# def input_lengths_lambda_func(args):\n", + "# hop_size = frame_step\n", + "# input_length = args\n", + "# return tf.cast(tf.math.ceil(input_length/hop_size)-1, dtype=\"float32\")\n", + "\n", + "\n", + "# def add_ctc_loss(model_builder):\n", + "# the_labels = Input(name='the_labels', shape=(None,), dtype='float32')\n", + "# input_lengths = Input(name='input_length', shape=(1,), dtype='float32')\n", + "# label_lengths = Input(name='label_length', shape=(1,), dtype='float32')\n", + "\n", + "# input_lengths2 = Lambda(input_lengths_lambda_func)(input_lengths)\n", + "# if model_builder.output_length:\n", + "# output_lengths = Lambda(\n", + "# model_builder.output_length)(input_lengths2)\n", + "# else:\n", + "# output_lengths = input_lengths2\n", + "\n", + "# loss_out = Lambda(ctc_lambda_func, output_shape=(1,), name='ctc')(\n", + "# [model_builder.output, the_labels, output_lengths, label_lengths])\n", + "# model = Model(inputs=[model_builder.input, the_labels,\n", + "# input_lengths, label_lengths], outputs=loss_out)\n", + "# return model" + ] + }, + { + "cell_type": "markdown", + "id": "9931b2e7", + "metadata": {}, + "source": [ + "### 2. Using CNN + simple rnn" + ] + }, + { + "cell_type": "markdown", + "id": "39b83bab", + "metadata": {}, + "source": [ + "#### Creating cnn_rnn model" + ] + }, + { + "cell_type": "code", + "execution_count": 84, + "id": "w6LXjBNVyq_f", + "metadata": { + "colab": { + "base_uri": "https://localhost:8080/" + }, + "executionInfo": { + "elapsed": 387, + "status": "ok", + "timestamp": 1628682451974, + "user": { + "displayName": "Daniel Zelalem", + "photoUrl": "", + "userId": "17933366000899068375" + }, + "user_tz": -180 + }, + "id": "w6LXjBNVyq_f", + "outputId": "f3e38510-ea5e-4a5f-c69e-7b50a9cb8422" + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Model: \"model_2\"\n", + "_________________________________________________________________\n", + "Layer (type) Output Shape Param # \n", + "=================================================================\n", + "the_input (InputLayer) [(None, None, 128)] 0 \n", + "_________________________________________________________________\n", + "conv1d (Conv1D) (None, None, 250) 128250 \n", + "_________________________________________________________________\n", + "bn_conv_1d (BatchNormalizati (None, None, 250) 1000 \n", + "_________________________________________________________________\n", + "rnn (SimpleRNN) (None, None, 400) 260400 \n", + "_________________________________________________________________\n", + "batch_normalization_17 (Batc (None, None, 400) 1600 \n", + "_________________________________________________________________\n", + "time_distributed_3 (TimeDist (None, None, 223) 89423 \n", + "_________________________________________________________________\n", + "softmax (Activation) (None, None, 223) 0 \n", + "=================================================================\n", + "Total params: 480,673\n", + "Trainable params: 479,373\n", + "Non-trainable params: 1,300\n", + "_________________________________________________________________\n" + ] + } + ], + "source": [ + "speech_cnn_rnn = cnn_rnn_model(n_mels, 250, 4, 1, 'same', 400, output_dim)\n", + "speech_cnn_rnn.summary()" + ] + }, + { + "cell_type": "markdown", + "id": "2998545e", + "metadata": {}, + "source": [ + "#### Building a cnn_rnn speech model by stacking speech_cnn_rnn and preprocess_model" + ] + }, + { + "cell_type": "code", + "execution_count": 86, + "id": "s56xi_OY1JRz", + "metadata": { + "colab": { + "base_uri": "https://localhost:8080/" + }, + "executionInfo": { + "elapsed": 427, + "status": "ok", + "timestamp": 1628682459201, + "user": { + "displayName": "Daniel Zelalem", + "photoUrl": "", + "userId": "17933366000899068375" + }, + "user_tz": -180 + }, + "id": "s56xi_OY1JRz", + "outputId": "59e78795-252b-4c6e-d271-6a2cff16dd89" + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Model: \"model_builder\"\n", + "_________________________________________________________________\n", + "Layer (type) Output Shape Param # \n", + "=================================================================\n", + "the_input (InputLayer) [(None, None)] 0 \n", + "_________________________________________________________________\n", + "preprocessin_model (Function (None, None, 128, 1) 512 \n", + "_________________________________________________________________\n", + "tf.compat.v1.squeeze_6 (TFOp (None, None, 128) 0 \n", + "_________________________________________________________________\n", + "model_2 (Functional) (None, None, 223) 480673 \n", + "=================================================================\n", + "Total params: 481,185\n", + "Trainable params: 479,629\n", + "Non-trainable params: 1,556\n", + "_________________________________________________________________\n" + ] + } + ], + "source": [ + "speech_cnn_rnn_model = build_model(output_dim, speech_cnn_rnn, preprocess_model)\n", + "speech_cnn_rnn_model.summary()" + ] + }, + { + "cell_type": "markdown", + "id": "2f7e0d00", + "metadata": {}, + "source": [ + "#### Training" + ] + }, + { + "cell_type": "code", + "execution_count": 46, + "id": "M2bfG1CcFMYk", + "metadata": { + "colab": { + "base_uri": "https://localhost:8080/" + }, + "executionInfo": { + "elapsed": 554119, + "status": "ok", + "timestamp": 1628683716655, + "user": { + "displayName": "Daniel Zelalem", + "photoUrl": "", + "userId": "17933366000899068375" + }, + "user_tz": -180 + }, + "id": "M2bfG1CcFMYk", + "outputId": "52e665ac-db82-488d-f0d7-a3d66921d1f2" + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Model: \"model_6\"\n", + "__________________________________________________________________________________________________\n", + "Layer (type) Output Shape Param # Connected to \n", + "==================================================================================================\n", + "the_input (InputLayer) [(None, None)] 0 \n", + "__________________________________________________________________________________________________\n", + "preprocessin_model (Functional) (None, None, 128, 1) 512 the_input[0][0] \n", + "__________________________________________________________________________________________________\n", + "tf.compat.v1.squeeze_3 (TFOpLam (None, None, 128) 0 preprocessin_model[3][0] \n", + "__________________________________________________________________________________________________\n", + "input_length (InputLayer) [(None, 1)] 0 \n", + "__________________________________________________________________________________________________\n", + "model_4 (Functional) (None, None, 223) 480673 tf.compat.v1.squeeze_3[0][0] \n", + "__________________________________________________________________________________________________\n", + "the_labels (InputLayer) [(None, None)] 0 \n", + "__________________________________________________________________________________________________\n", + "lambda_4 (Lambda) (None, 1) 0 input_length[0][0] \n", + "__________________________________________________________________________________________________\n", + "label_length (InputLayer) [(None, 1)] 0 \n", + "__________________________________________________________________________________________________\n", + "ctc (Lambda) (None, 1) 0 model_4[0][0] \n", + " the_labels[0][0] \n", + " lambda_4[0][0] \n", + " label_length[0][0] \n", + "==================================================================================================\n", + "Total params: 481,185\n", + "Trainable params: 479,629\n", + "Non-trainable params: 1,556\n", + "__________________________________________________________________________________________________\n", + "None\n", + "Epoch 1/20\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "/usr/local/lib/python3.7/dist-packages/tensorflow/python/keras/engine/training.py:1940: UserWarning: `Model.fit_generator` is deprecated and will be removed in a future version. Please use `Model.fit`, which supports generators.\n", + " warnings.warn('`Model.fit_generator` is deprecated and '\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "50/50 [==============================] - 29s 549ms/step - loss: 63.8157\n", + "Epoch 2/20\n", + "50/50 [==============================] - 27s 539ms/step - loss: 62.2648\n", + "Epoch 3/20\n", + "50/50 [==============================] - 29s 582ms/step - loss: 60.5698\n", + "Epoch 4/20\n", + "50/50 [==============================] - 29s 564ms/step - loss: 59.1693\n", + "Epoch 5/20\n", + "50/50 [==============================] - 27s 538ms/step - loss: 57.8804\n", + "Epoch 6/20\n", + "50/50 [==============================] - 28s 562ms/step - loss: 56.3250\n", + "Epoch 7/20\n", + "50/50 [==============================] - 27s 551ms/step - loss: 55.1084\n", + "Epoch 8/20\n", + "50/50 [==============================] - 27s 533ms/step - loss: 53.8964\n", + "Epoch 9/20\n", + "50/50 [==============================] - 29s 579ms/step - loss: 52.6477\n", + "Epoch 10/20\n", + "50/50 [==============================] - 26s 530ms/step - loss: 51.7327\n", + "Epoch 11/20\n", + "50/50 [==============================] - 28s 568ms/step - loss: 50.4534\n", + "Epoch 12/20\n", + "50/50 [==============================] - 27s 531ms/step - loss: 48.9551\n", + "Epoch 13/20\n", + "50/50 [==============================] - 27s 534ms/step - loss: 48.2614\n", + "Epoch 14/20\n", + "50/50 [==============================] - 28s 564ms/step - loss: 47.1542\n", + "Epoch 15/20\n", + "50/50 [==============================] - 26s 532ms/step - loss: 46.4222\n", + "Epoch 16/20\n", + "50/50 [==============================] - 29s 578ms/step - loss: 45.2917\n", + "Epoch 17/20\n", + "50/50 [==============================] - 28s 566ms/step - loss: 44.5295\n", + "Epoch 18/20\n", + "50/50 [==============================] - 27s 522ms/step - loss: 43.6852\n", + "Epoch 19/20\n", + "50/50 [==============================] - 27s 540ms/step - loss: 43.0850\n", + "Epoch 20/20\n", + "50/50 [==============================] - 28s 561ms/step - loss: 41.7842\n" + ] + }, + { + "data": { + "text/plain": [ + "" + ] + }, + "execution_count": 46, + "metadata": { + "tags": [] + }, + "output_type": "execute_result" + } + ], + "source": [ + "\n", + "train(speech_cnn_rnn_model, dg, epochs=20, save_path=\"../models/cnn_rnn_model.h5\", batch_size=batch_size)\n" + ] + }, + { + "cell_type": "markdown", + "id": "e236af04", + "metadata": {}, + "source": [ + "#### Infer cnn_rnn_model" + ] + }, + { + "cell_type": "code", + "execution_count": 88, + "id": "dc6aebad", + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "actual የ ኖርዌይ የ ማእድን ካምፓኒ ኢትዮጵያ ውስጥ እንዲ ሰራ ፈቃድ ተሰጠው\n", + "predicted ስእሄ ን ሮ የ ማ እድደም ካን ፓ ንኔ ዲኢትዮጵያ ው ችጥ ክ ኒ ሳአራፈዋቀልሽሻት ታሁ\n", + "WER: 1.36\n", + "\n", + "actual አደጋ ጣ ዮቹ ኢትዮጵያዊ ውን ሾፌር ሆን ብለው ከ ሌሎ ለ ይተው እንደ ገደሉት ም ተመልክ ቷል\n", + "predicted ር ካዳጋያ ዳያበ ካከተር ጠ ያ ዊያን ሽው ሄያር ሀን ክላብ ንከ በር ሂ ር የ ከንደ ገደሩ ሳ ዳንነርክ ትለች\n", + "WER: 1.24\n", + "\n", + "actual ብቻ እንደ ው ለ ነገሩ እንጂ ያነሳ ሁት ሙትን ለ መውቀስ ፈልጌ አይደለም\n", + "predicted ብ ቻእንዳ ለ ላገበ እንጂ ያ ን ሰ ዎት ሙ ተች ለ መውቀሰ ፈልቄያይደድለ \n", + "WER: 1.00\n", + "\n", + "actual እዚህ አካባቢ ያለው ወገናችን ብዙ እውነት ይናገራል\n", + "predicted ጥጹት ስ ክት አንልላሩ ሀበራትጥምን በ ሶኦነክ እንና አልከራ \n", + "WER: 1.29\n", + "\n", + "actual ዘነበ ች ሰራተኛዋ ን አታ ን ጓጉ ብላ ተቆጣ ቻት\n", + "predicted ንነበ ች ራት ዋ ን አ ታ ን ባጉ በላ ተቆርጣ ቻት\n", + "WER: 0.80\n", + "\n", + "actual ሶስተኛው ሜይን ፍሬ ም ኮምፒውተር ይባላል\n", + "predicted እስት ተይ ኛ ው ሜይም ጥሬም ኰፒውሩታ ሪ ታና \n", + "WER: 1.50\n", + "\n", + "actual ተድላ በልጅነ ቱ ቆረ በ\n", + "predicted ተድ ላ በ ልዜን ቱ ቆእ ት አ\n", + "WER: 1.40\n", + "\n", + "actual በዚህ ኮሚቴ ስር የ ቴክኒክ ኮሚቴ ይኖራል\n", + "predicted በ ዚህ ኮሚቴ ሱር የ ቴክ ኒክ ኮሚቴ ይሞራት\n", + "WER: 0.86\n", + "\n", + "actual ብዙ ጨዋታዎች ን እንደ ተመለከቱ ገልጸው ልናል\n", + "predicted ብዙ ጨዋታዎች ን እንደ ተመለከቱ ገልጸው ልናል\n", + "WER: 0.00\n", + "\n", + "actual ችግሩ ንም እንዲ ፈታ ጥረት እያደረግን ነው\n", + "predicted ችግ ሩ ለም እንዲ ስፈት ተጥረት እያደረገን ናው\n", + "WER: 1.00\n", + "\n" + ] + } + ], + "source": [ + "speech_cnn_rnn_model.load_weights(\"../models/cnn_rnn_model.h5\")\n", + "\n", + "for k in range(10):\n", + " \n", + "\n", + " i = random.randint(0, 3000)\n", + " \n", + " actual_translation = translations[i]\n", + " sample_test_audio = audios[i]\n", + "\n", + " predicted, error = predict(speech_cnn_rnn_model, sample_test_audio,\n", + " tokenizer, int_to_char, actual=actual_translation)\n", + " \n", + " print(\"actual\", actual_translation)\n", + " print(\"predicted\", predicted)\n", + " print(f\"WER: {error:.2f}\")\n", + "\n", + " print()" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "jlPXyg-VsNv9", + "metadata": { + "id": "jlPXyg-VsNv9" + }, + "outputs": [], + "source": [] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "w3VPIL4TsUhA", + "metadata": { + "id": "w3VPIL4TsUhA" + }, + "outputs": [], + "source": [] + }, + { + "cell_type": "markdown", + "id": "05bc8167", + "metadata": { + "id": "cN2FhIzesUkJ" + }, + "source": [ + "## FINAL MODEL BETTER MODEL" + ] + }, + { + "cell_type": "markdown", + "id": "d6cbc38c", + "metadata": { + "id": "8I9rcUBqsUsE" + }, + "source": [ + "### 3. Using CNN and Bi directional rnn" + ] + }, + { + "cell_type": "code", + "execution_count": 72, + "id": "_Rz94NaiCLRk", + "metadata": { + "executionInfo": { + "elapsed": 540, + "status": "ok", + "timestamp": 1628699450931, + "user": { + "displayName": "Daniel Zelalem", + "photoUrl": "", + "userId": "17933366000899068375" + }, + "user_tz": -180 + }, + "id": "_Rz94NaiCLRk" + }, + "outputs": [], + "source": [ + "# since this model requires expenisive resource for training, we minimize the batch size to 32\n", + "\n", + "batch_size = 32\n", + "dg = DataGenerator(translations, audios, batch_size, shuffle=True)\n", + "\n" + ] + }, + { + "cell_type": "markdown", + "id": "0ae772a5", + "metadata": {}, + "source": [ + "#### First we create a cnn model that expects a logmelespectrogram prediction as input" + ] + }, + { + "cell_type": "code", + "execution_count": 73, + "id": "RJBipVrVyD18", + "metadata": { + "colab": { + "base_uri": "https://localhost:8080/" + }, + "executionInfo": { + "elapsed": 556, + "status": "ok", + "timestamp": 1628699455132, + "user": { + "displayName": "Daniel Zelalem", + "photoUrl": "", + "userId": "17933366000899068375" + }, + "user_tz": -180 + }, + "id": "RJBipVrVyD18", + "outputId": "567e673d-42bc-40ac-b82a-0e6966675169" + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Model: \"cnn\"\n", + "_________________________________________________________________\n", + "Layer (type) Output Shape Param # \n", + "=================================================================\n", + "the_input (InputLayer) [(None, None, 128, 1)] 0 \n", + "_________________________________________________________________\n", + "conv2d (Conv2D) (None, None, 128, 128) 6400 \n", + "_________________________________________________________________\n", + "activation (Activation) (None, None, 128, 128) 0 \n", + "_________________________________________________________________\n", + "batch_normalization_10 (Batc (None, None, 128, 128) 512 \n", + "_________________________________________________________________\n", + "max_pooling2d (MaxPooling2D) (None, None, 64, 128) 0 \n", + "_________________________________________________________________\n", + "conv2d_1 (Conv2D) (None, None, 64, 64) 204864 \n", + "_________________________________________________________________\n", + "activation_1 (Activation) (None, None, 64, 64) 0 \n", + "_________________________________________________________________\n", + "batch_normalization_11 (Batc (None, None, 64, 64) 256 \n", + "_________________________________________________________________\n", + "max_pooling2d_1 (MaxPooling2 (None, None, 32, 64) 0 \n", + "_________________________________________________________________\n", + "conv2d_2 (Conv2D) (None, None, 32, 64) 36928 \n", + "_________________________________________________________________\n", + "activation_2 (Activation) (None, None, 32, 64) 0 \n", + "_________________________________________________________________\n", + "batch_normalization_12 (Batc (None, None, 32, 64) 256 \n", + "_________________________________________________________________\n", + "max_pooling2d_2 (MaxPooling2 (None, None, 16, 64) 0 \n", + "_________________________________________________________________\n", + "reshape (Reshape) (None, None, 1024) 0 \n", + "=================================================================\n", + "Total params: 249,216\n", + "Trainable params: 248,704\n", + "Non-trainable params: 512\n", + "_________________________________________________________________\n" + ] + }, + { + "data": { + "text/plain": [ + "(None, TensorShape([None, None, 1024]))" + ] + }, + "execution_count": 73, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "cnn_model, cnn_shape = CNN_net(n_mels)\n", + "cnn_model.summary(), cnn_shape" + ] + }, + { + "cell_type": "markdown", + "id": "2d4690c6", + "metadata": {}, + "source": [ + "#### Create our Bi directional RNN" + ] + }, + { + "cell_type": "code", + "execution_count": 24, + "id": "6wTL17mK3hg4", + "metadata": { + "colab": { + "base_uri": "https://localhost:8080/" + }, + "executionInfo": { + "elapsed": 3640, + "status": "ok", + "timestamp": 1628699464815, + "user": { + "displayName": "Daniel Zelalem", + "photoUrl": "", + "userId": "17933366000899068375" + }, + "user_tz": -180 + }, + "id": "6wTL17mK3hg4", + "outputId": "02e6d5b8-3326-4f57-c101-3fcbb215e2c2" + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Model: \"BidirectionalRNN\"\n", + "_________________________________________________________________\n", + "Layer (type) Output Shape Param # \n", + "=================================================================\n", + "the_input (InputLayer) [(None, None, 1024)] 0 \n", + "_________________________________________________________________\n", + "bidirectional (Bidirectional (None, None, 800) 4560000 \n", + "_________________________________________________________________\n", + "batch_normalization_4 (Batch (None, None, 800) 3200 \n", + "_________________________________________________________________\n", + "dropout (Dropout) (None, None, 800) 0 \n", + "_________________________________________________________________\n", + "bidirectional_1 (Bidirection (None, None, 800) 3843200 \n", + "_________________________________________________________________\n", + "batch_normalization_5 (Batch (None, None, 800) 3200 \n", + "_________________________________________________________________\n", + "dropout_1 (Dropout) (None, None, 800) 0 \n", + "_________________________________________________________________\n", + "bidirectional_2 (Bidirection (None, None, 800) 3843200 \n", + "_________________________________________________________________\n", + "batch_normalization_6 (Batch (None, None, 800) 3200 \n", + "_________________________________________________________________\n", + "dropout_2 (Dropout) (None, None, 800) 0 \n", + "_________________________________________________________________\n", + "bidirectional_3 (Bidirection (None, None, 800) 3843200 \n", + "_________________________________________________________________\n", + "batch_normalization_7 (Batch (None, None, 800) 3200 \n", + "_________________________________________________________________\n", + "dropout_3 (Dropout) (None, None, 800) 0 \n", + "_________________________________________________________________\n", + "time_distributed (TimeDistri (None, None, 223) 178623 \n", + "_________________________________________________________________\n", + "softmax (Activation) (None, None, 223) 0 \n", + "=================================================================\n", + "Total params: 16,281,023\n", + "Trainable params: 16,274,623\n", + "Non-trainable params: 6,400\n", + "_________________________________________________________________\n" + ] + } + ], + "source": [ + "BI_RNN_2 = BidirectionalRNN2(1024, batch_size=batch_size, output_dim=output_dim)\n", + "BI_RNN_2.summary()" + ] + }, + { + "cell_type": "markdown", + "id": "8d35841f", + "metadata": {}, + "source": [ + "#### Define a builder that stacks preprocess_model, cnn_model and the custom model(BI-RNN) into a single model" + ] + }, + { + "cell_type": "code", + "execution_count": 75, + "id": "fA-kpf8c5a0W", + "metadata": { + "executionInfo": { + "elapsed": 5, + "status": "ok", + "timestamp": 1628699465570, + "user": { + "displayName": "Daniel Zelalem", + "photoUrl": "", + "userId": "17933366000899068375" + }, + "user_tz": -180 + }, + "id": "fA-kpf8c5a0W" + }, + "outputs": [], + "source": [ + "def build_model2(output_dim, cnn_model, custom_model, preprocess_model, mfcc=False, calc=None):\n", + "\n", + " input_audios = Input(name='the_input', shape=(None,))\n", + " pre = preprocess_model(input_audios)\n", + " pre = tf.squeeze(pre, [3])\n", + "\n", + " cnn_output = cnn_model(pre)\n", + "\n", + " y_pred = custom_model(cnn_output)\n", + " model = Model(inputs=input_audios, outputs=y_pred, name=\"model_builder\")\n", + " model.output_length = calc\n", + "\n", + " return model" + ] + }, + { + "cell_type": "markdown", + "id": "52cfbef3", + "metadata": {}, + "source": [ + "#### Building our cnn-bi-rnn model using build2 function" + ] + }, + { + "cell_type": "code", + "execution_count": 26, + "id": "jmo82oGp5xa8", + "metadata": { + "colab": { + "base_uri": "https://localhost:8080/" + }, + "executionInfo": { + "elapsed": 3570, + "status": "ok", + "timestamp": 1628699471716, + "user": { + "displayName": "Daniel Zelalem", + "photoUrl": "", + "userId": "17933366000899068375" + }, + "user_tz": -180 + }, + "id": "jmo82oGp5xa8", + "outputId": "53400ce2-cee7-4401-bf0b-6030a37ac4d0" + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Model: \"model_builder\"\n", + "_________________________________________________________________\n", + "Layer (type) Output Shape Param # \n", + "=================================================================\n", + "the_input (InputLayer) [(None, None)] 0 \n", + "_________________________________________________________________\n", + "preprocessin_model (Function (None, None, 128, 1) 512 \n", + "_________________________________________________________________\n", + "tf.compat.v1.squeeze (TFOpLa (None, None, 128) 0 \n", + "_________________________________________________________________\n", + "cnn (Functional) (None, None, 1024) 249216 \n", + "_________________________________________________________________\n", + "BidirectionalRNN (Functional (None, None, 223) 16281023 \n", + "=================================================================\n", + "Total params: 16,530,751\n", + "Trainable params: 16,523,583\n", + "Non-trainable params: 7,168\n", + "_________________________________________________________________\n" + ] + } + ], + "source": [ + "cnn_bi_rnn_model = build_model2(output_dim, cnn_model, BI_RNN_2, preprocess_model)\n", + "cnn_bi_rnn_model.summary()" + ] + }, + { + "cell_type": "code", + "execution_count": 94, + "id": "X38CX655C2hb", + "metadata": { + "executionInfo": { + "elapsed": 4, + "status": "ok", + "timestamp": 1628699512025, + "user": { + "displayName": "Daniel Zelalem", + "photoUrl": "", + "userId": "17933366000899068375" + }, + "user_tz": -180 + }, + "id": "X38CX655C2hb" + }, + "outputs": [], + "source": [ + "# if a pretrained model exists load pretrained model\n", + "try:\n", + " cnn_bi_rnn_model.load_weights(\"../models/cnn-bi-rnn.h5\")\n", + "except:\n", + " pass" + ] + }, + { + "cell_type": "markdown", + "id": "496512a1", + "metadata": {}, + "source": [ + "#### Training" + ] + }, + { + "cell_type": "code", + "execution_count": 83, + "id": "VpezKF8CAReX", + "metadata": { + "colab": { + "base_uri": "https://localhost:8080/", + "height": 956 + }, + "executionInfo": { + "elapsed": 39382, + "status": "error", + "timestamp": 1628699374537, + "user": { + "displayName": "Daniel Zelalem", + "photoUrl": "", + "userId": "17933366000899068375" + }, + "user_tz": -180 + }, + "id": "VpezKF8CAReX", + "outputId": "53e03b76-3415-490a-ad59-872f9dfdfaf9" + }, + "outputs": [], + "source": [ + "\n", + "train(cnn_bi_rnn_model, dg, epochs=20, save_path=\"../models/cnn_bi_rnn_model.h5\", batch_size=batch_size)\n" + ] + }, + { + "cell_type": "markdown", + "id": "b3982b40", + "metadata": {}, + "source": [ + "#### Inference" + ] + }, + { + "cell_type": "code", + "execution_count": 82, + "id": "SYqCyyi0SIYG", + "metadata": { + "colab": { + "base_uri": "https://localhost:8080/" + }, + "executionInfo": { + "elapsed": 26235, + "status": "ok", + "timestamp": 1628699510451, + "user": { + "displayName": "Daniel Zelalem", + "photoUrl": "", + "userId": "17933366000899068375" + }, + "user_tz": -180 + }, + "id": "SYqCyyi0SIYG", + "outputId": "0941430e-f042-4fa9-c40f-c0041a153884" + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "actual ሀያት ተባባሪ ዎቹ ና ተሳታፊ ዎቹን አወያየ\n", + "predicted ሀያት ተባረ ዎች ና ተሻታሺ ዎች ን አጐራ የጀ\n", + "WER: 1.00\n", + "\n", + "actual እንዲያ መሬት አይ ን ካ ኝ ይል የነበረ ሰው በ ድንገት ቆረቆዘ አይደል\n", + "predicted እንዲያ መሬት አይ ን ካ ኝ ይል የነበረ ሰው በ ድንገት ቆረቆዘ አይደል\n", + "WER: 0.00\n", + "\n", + "actual ቡድናችን የ ተሸነፈ ው እ ኮ ከ ቅዱስ ጊዮርጊስ ጋር ስን ጫወት ብቻ ነው\n", + "predicted ቡድናችን የ ተሸነ ፈ ውእ ኮ ከህረ ቅዱስ ጊዮርጊስ ጋር ስን ጫ ወጥ ብቻ ሉ\n", + "WER: 0.50\n", + "\n", + "actual ፈ ቲያ ሰኢድ ወይዘሪት አዲስ አበባ ተባለች\n", + "predicted ከ ቲያ ፈቂድ ወዘሪት አዲስ አበባ ተታለች\n", + "WER: 0.57\n", + "\n", + "actual እጀ ጐልዳ ፋው ሰው ዬ መጻፍ አይችልም\n", + "predicted እጀ ጐልዳ ፋው ሰው ዬ መጻፍ አይችልም\n", + "WER: 0.00\n", + "\n", + "actual የ ኢትዮጵያ ነጻ ፕሬስ ጋዜጠኞች ማህበር ጽፈት ቤት ና የ ኢትዮ ታይም ቢሮ ተዘረፈ\n", + "predicted የ ኢትዮጵያ ነጻ ፐሬስ ካዜጠኞሽ ማህባል ጽፈት ቤት ና የ ኢትዮ ታይል ዜሮ ተዘረራ ት\n", + "WER: 0.50\n", + "\n", + "actual በ አውሮፓ ውስጥ አንድ መቶ ሀምሳ ቢሊዮን ቴሌቪዥን አለ\n", + "predicted በ አውርታው ውስጥ አንድ መት ሀብሳብ ቢሊዮየን ን ቴክኬክሽን አለ\n", + "WER: 0.67\n", + "\n", + "actual በ ኦልድ ትራ ፎርድ ማንቸስተር ዩናትድ ብላክበርን ን አስተናግ ዷል\n", + "predicted ተቆል ድ ትራ ፎርድ ማንቸስተር ዩናትድ ትላክበርለን አስተናግ ዷል\n", + "WER: 0.40\n", + "\n", + "actual ኢትዮጵያ ለ ደረሰባት ለሚደርስ ባት የእኔ ም የ እሳቸው ም የ ሁላችን ም እጅ አለ በት\n", + "predicted ኢትዮጵያ ለ ደረሰባት ለሚደርስ ዛት የ እኔ ም የ እሳቸው ም የ ሁላችን ም ጥይጅ አለ በት\n", + "WER: 0.25\n", + "\n", + "actual በሮማ በ ተደረገው ጨዋታ ሮማ ፍሮዬንቲ ና አስተናግ ዶ በድል ተ ወጥቶ አል\n", + "predicted በሮማ በ ተደረገው ጨዋታ አሮማ ፍሮ ዬንቺ ና አስተናግ ዶ በድል ተ ወጥጧ አል\n", + "WER: 0.31\n", + "\n" + ] + } + ], + "source": [ + "\n", + "cnn_bi_rnn_model.load_weights(\"../models/cnn-bi-rnn.h5\")\n", + "for k in range(10):\n", + " \n", + "\n", + " i = random.randint(0, 3000)\n", + " \n", + " actual_translation = translations[i]\n", + " sample_test_audio = audios[i]\n", + "\n", + " predicted, error = predict(cnn_bi_rnn_model, sample_test_audio,\n", + " tokenizer, int_to_char, actual=actual_translation)\n", + " \n", + " print(\"actual\", actual_translation)\n", + " print(\"predicted\", predicted)\n", + " print(f\"WER: {error:.2f}\")\n", + "\n", + " print()\n", + " \n" + ] + }, + { + "cell_type": "code", + "execution_count": 100, + "id": "488565d3", + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + } + ], + "source": [ + "cnn_bi_rnn_model.save('../models/final_speech_model.h5')\n" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "8154784f", + "metadata": {}, + "outputs": [], + "source": [] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "3dd4407b", + "metadata": {}, + "outputs": [], + "source": [] + } + ], + "metadata": { + "accelerator": "GPU", + "colab": { + "collapsed_sections": [], + "name": "ModelTrain.ipynb", + "provenance": [] + }, + "kernelspec": { + "display_name": "Python 3", + "language": "python", + "name": "python3" + }, + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 3 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython3", + "version": "3.9.4" + } + }, + "nbformat": 4, + "nbformat_minor": 5 +} diff --git a/notebooks/.ipynb_checkpoints/ModelTrain-checkpoint.ipynb b/notebooks/.ipynb_checkpoints/ModelTrain-checkpoint.ipynb new file mode 100644 index 0000000..7201f62 --- /dev/null +++ b/notebooks/.ipynb_checkpoints/ModelTrain-checkpoint.ipynb @@ -0,0 +1,421 @@ +{ + "cells": [ + { + "cell_type": "code", + "execution_count": 1, + "id": "c34a6094", + "metadata": {}, + "outputs": [], + "source": [ + "import os\n", + "import sys\n", + "sys.path.append(os.path.abspath(os.path.join('../scripts')))\n", + "\n", + "import IPython.display as ipd\n", + "import matplotlib.pyplot as plt\n", + "import numpy as np\n", + "from scipy.io import wavfile #for audio processing\n", + "import os\n", + "import pickle\n", + "import pandas as pd\n", + "from collections import Counter\n", + "\n", + "import tensorflow as tf\n", + "from tensorflow.keras.models import Model, Sequential\n", + "from tensorflow.keras.layers import * \n", + "from tensorflow.keras.preprocessing.sequence import pad_sequences\n", + "from tensorflow.keras.optimizers import SGD, Adam, RMSprop\n", + "from tensorflow.keras import backend as K\n", + "import mlflow" + ] + }, + { + "cell_type": "code", + "execution_count": 2, + "id": "acf88600", + "metadata": {}, + "outputs": [], + "source": [ + "import helper\n" + ] + }, + { + "cell_type": "code", + "execution_count": 5, + "id": "4f219ca9", + "metadata": {}, + "outputs": [], + "source": [ + "\n", + "from data_generator import DataGenerator\n", + "from tokenizer import Tokenizer\n", + "from logspectrorgam import LogMelSpectrogram\n", + "from bidirectionalRNN import BidirectionalRNN\n", + "from simpleRNN import simple_rnn_model\n", + "from ctc_loss import add_ctc_loss" + ] + }, + { + "cell_type": "code", + "execution_count": 6, + "id": "4b39d89d", + "metadata": {}, + "outputs": [], + "source": [ + "sample_rate = 8000" + ] + }, + { + "cell_type": "code", + "execution_count": 7, + "id": "09c8fa57", + "metadata": {}, + "outputs": [], + "source": [ + "def preprocessin_model(sample_rate, fft_size, frame_step, n_mels, mfcc=False):\n", + "\n", + " input_data = Input(name='input', shape=(None,), dtype=\"float32\")\n", + " featLayer = LogMelSpectrogram(\n", + " fft_size=fft_size,\n", + " hop_size=frame_step,\n", + " n_mels=n_mels,\n", + " \n", + " sample_rate=sample_rate,\n", + " f_min=0.0,\n", + " \n", + " f_max=int(sample_rate / 2)\n", + " )(input_data)\n", + " \n", + " x = BatchNormalization()(featLayer)\n", + " model = Model(inputs=input_data, outputs=x, name=\"preprocessin_model\")\n", + "\n", + " return model" + ] + }, + { + "cell_type": "code", + "execution_count": 22, + "id": "7d82a51e", + "metadata": {}, + "outputs": [], + "source": [ + "def BidirectionalRNN(input_dim, batch_size, sample_rate=22000,\n", + " rnn_layers=2, units=400, drop_out=0.5, act='tanh', output_dim=224):\n", + "\n", + " input_data = Input(name='the_input', shape=(\n", + " None, input_dim), batch_size=batch_size)\n", + " \n", + "\n", + "\n", + " \n", + " x = Bidirectional(LSTM(units, activation=act,\n", + " return_sequences=True, implementation=2))(input_data)\n", + " \n", + " x = BatchNormalization()(x)\n", + " x = Dropout(drop_out)(x)\n", + "\n", + " for i in range(rnn_layers - 2):\n", + " x = Bidirectional(\n", + " LSTM(units, activation=act, return_sequences=True))(x)\n", + " x = BatchNormalization()(x)\n", + " x = Dropout(drop_out)(x)\n", + "\n", + " x = Bidirectional(LSTM(units, activation=act,\n", + " return_sequences=True, implementation=2))(x)\n", + " x = BatchNormalization()(x)\n", + " x = Dropout(drop_out)(x)\n", + "\n", + " time_dense = TimeDistributed(Dense(output_dim))(x)\n", + "\n", + " y_pred = Activation('softmax', name='softmax')(time_dense)\n", + "\n", + " model = Model(inputs=input_data, outputs=y_pred, name=\"BidirectionalRNN\")\n", + "\n", + " return model" + ] + }, + { + "cell_type": "code", + "execution_count": 18, + "id": "bf0de92e", + "metadata": {}, + "outputs": [], + "source": [ + "def simple_rnn_model(input_dim, output_dim=224):\n", + "\n", + " input_data = Input(name='the_input', shape=(None, input_dim))\n", + " simp_rnn = GRU(output_dim, return_sequences=True,\n", + " implementation=2, name='rnn')(input_data)\n", + " y_pred = Activation('softmax', name='softmax')(simp_rnn)\n", + " model = Model(inputs=input_data, outputs=y_pred, name=\"simple_rnn_model\")\n", + " model.output_length = lambda x: x\n", + " return model" + ] + }, + { + "cell_type": "code", + "execution_count": 8, + "id": "7abeb89a", + "metadata": {}, + "outputs": [], + "source": [ + "def train(model_builder, \n", + " data_len,\n", + " data_gen,\n", + " batch_size = 25,\n", + " epochs=20, \n", + " verbose=1,\n", + " optimizer=SGD(learning_rate=0.002, decay=1e-6, momentum=0.9, nesterov=True, clipnorm=5),\n", + " ): \n", + " \n", + " model = add_ctc_loss(model_builder)\n", + "\n", + " model.compile(loss={'ctc': lambda y_true, y_pred: y_pred}, optimizer=optimizer)\n", + " print(model.summary())\n", + "\n", + "\n", + " hist = model.fit_generator(generator=data_gen,\n", + " epochs=epochs,\n", + " verbose=verbose, \n", + " use_multiprocessing=False)" + ] + }, + { + "cell_type": "code", + "execution_count": 9, + "id": "3f654a55", + "metadata": {}, + "outputs": [], + "source": [ + "translation_obj = helper.read_obj(\"../data/translation_dict.pkl\")\n", + "audio_obj = helper.read_obj(\"../data/audio_dict.pkl\")\n", + "# meta_data = data_loader.create_meta_data(translation_obj, audio_obj)" + ] + }, + { + "cell_type": "code", + "execution_count": 10, + "id": "ef6a4e11", + "metadata": {}, + "outputs": [], + "source": [ + "audios = []\n", + "for label in audio_obj:\n", + " audios.append(audio_obj[label][0])\n", + " \n", + "translations = []\n", + "for label in audio_obj:\n", + " translations.append(translation_obj[label])" + ] + }, + { + "cell_type": "code", + "execution_count": 11, + "id": "107cd033", + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "sample snt: የተለያዩ የ ትግራይ አውራጃ ተወላጆች ገንዘባቸው ን አዋጥ ተው የ ልማት ተቋማትን እንዲ መሰርቱ ትልማ አይ ፈቅድ ም\n", + "encoded snt: [7, 8, 11, 6, 131, 1, 7, 1, 3, 28, 27, 24, 1, 10, 4, 27, 115, 1, 8, 37, 29, 149, 18, 1, 21, 2, 65, 23, 26, 4, 1, 2, 1, 10, 41, 43, 1, 8, 4, 1, 7, 1, 12, 22, 3, 1, 8, 88, 22, 3, 2, 1, 13, 2, 49, 1, 15, 31, 14, 69, 1, 3, 12, 22, 1, 10, 24, 1, 61, 45, 32, 1, 16]\n", + "decoed snt: የተለያዩ የ ትግራይ አውራጃ ተወላጆች ገንዘባቸው ን አዋጥ ተው የ ልማት ተቋማትን እንዲ መሰርቱ ትልማ አይ ፈቅድ ም\n" + ] + } + ], + "source": [ + "tokenizer = Tokenizer(translations)\n", + "int_to_char, char_to_int = tokenizer.build_dict()\n", + "sample = translations[0]\n", + "encoded = tokenizer.encode(sample, char_to_int)\n", + "decoded = tokenizer.decode_text(sample, encoded)\n", + "\n", + "print(f\"sample snt: {sample}\")\n", + "print(f\"encoded snt: {encoded}\")\n", + "print(f\"decoed snt: {decoded}\")" + ] + }, + { + "cell_type": "code", + "execution_count": 12, + "id": "bdea9379", + "metadata": {}, + "outputs": [], + "source": [ + "\n", + "sample_rate = 22000\n", + "fft_size = 1024\n", + "frame_step = 512\n", + "n_mels = 128\n", + "\n", + "batch_size = 100\n", + "epochs = 20\n", + "data_len = len(translations)\n", + "output_dim = len(char_to_int) + 2\n" + ] + }, + { + "cell_type": "code", + "execution_count": 13, + "id": "cb25dda1", + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Model: \"preprocessin_model\"\n", + "_________________________________________________________________\n", + "Layer (type) Output Shape Param # \n", + "=================================================================\n", + "input (InputLayer) [(None, None)] 0 \n", + "_________________________________________________________________\n", + "log_mel_spectrogram (LogMelS (None, None, 128, 1) 0 \n", + "_________________________________________________________________\n", + "batch_normalization (BatchNo (None, None, 128, 1) 4 \n", + "=================================================================\n", + "Total params: 4\n", + "Trainable params: 2\n", + "Non-trainable params: 2\n", + "_________________________________________________________________\n" + ] + } + ], + "source": [ + "dg = DataGenerator(translations, audios, batch_size)\n", + "preprocess_model = preprocessin_model(sample_rate, fft_size, frame_step, n_mels)\n", + "preprocess_model.summary()" + ] + }, + { + "cell_type": "code", + "execution_count": 14, + "id": "e43ae703", + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Model: \"simple_rnn_model\"\n", + "_________________________________________________________________\n", + "Layer (type) Output Shape Param # \n", + "=================================================================\n", + "the_input (InputLayer) [(None, None, 128)] 0 \n", + "_________________________________________________________________\n", + "rnn (GRU) (None, None, 223) 236157 \n", + "_________________________________________________________________\n", + "softmax (Activation) (None, None, 223) 0 \n", + "=================================================================\n", + "Total params: 236,157\n", + "Trainable params: 236,157\n", + "Non-trainable params: 0\n", + "_________________________________________________________________\n" + ] + } + ], + "source": [ + "speech_model = simple_rnn_model(n_mels, output_dim)\n", + "speech_model.summary()\n", + "# speech_model = BidirectionalRNN(n_mels, output_dim=output_dim)\n", + "# speech_model.summary()" + ] + }, + { + "cell_type": "code", + "execution_count": 15, + "id": "3675d659", + "metadata": {}, + "outputs": [], + "source": [ + "def build_model(output_dim, custom_model, preprocess_model, mfcc=False, calc=None):\n", + "\n", + " input_audios = Input(name='the_input', shape=(None,))\n", + " pre = preprocess_model(input_audios)\n", + " pre = tf.squeeze(pre, [3])\n", + "\n", + " y_pred = custom_model(pre)\n", + " model = Model(inputs=input_audios, outputs=y_pred, name=\"model_builder\")\n", + " model.output_length = calc\n", + "\n", + " return model" + ] + }, + { + "cell_type": "code", + "execution_count": 16, + "id": "b8e25a3f", + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Model: \"model_builder\"\n", + "_________________________________________________________________\n", + "Layer (type) Output Shape Param # \n", + "=================================================================\n", + "the_input (InputLayer) [(None, None)] 0 \n", + "_________________________________________________________________\n", + "preprocessin_model (Function (None, None, 128, 1) 4 \n", + "_________________________________________________________________\n", + "tf.compat.v1.squeeze (TFOpLa (None, None, 128) 0 \n", + "_________________________________________________________________\n", + "simple_rnn_model (Functional (None, None, 223) 236157 \n", + "=================================================================\n", + "Total params: 236,161\n", + "Trainable params: 236,159\n", + "Non-trainable params: 2\n", + "_________________________________________________________________\n" + ] + } + ], + "source": [ + "model = build_model(output_dim, speech_model, preprocess_model)\n", + "model.summary()" + ] + }, + { + "cell_type": "code", + "execution_count": 18, + "id": "01feee42", + "metadata": {}, + "outputs": [], + "source": [ + "# mlflow.set_experiment('Speech Model-RNN-baseline')\n", + "# mlflow.tensorflow.autolog()\n", + "train(model, 100, dg, epochs=20, batch_size=100)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "bb0d2a74", + "metadata": {}, + "outputs": [], + "source": [] + } + ], + "metadata": { + "kernelspec": { + "display_name": "Python 3", + "language": "python", + "name": "python3" + }, + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 3 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython3", + "version": "3.9.4" + } + }, + "nbformat": 4, + "nbformat_minor": 5 +} diff --git a/notebooks/.ipynb_checkpoints/data_preprocessing-checkpoint.ipynb b/notebooks/.ipynb_checkpoints/data_preprocessing-checkpoint.ipynb index 36d25f2..f41fd3d 100644 --- a/notebooks/.ipynb_checkpoints/data_preprocessing-checkpoint.ipynb +++ b/notebooks/.ipynb_checkpoints/data_preprocessing-checkpoint.ipynb @@ -2,7 +2,8 @@ "cells": [ { "cell_type": "code", - "execution_count": 1, + "execution_count": 4, + "id": "f7d9521a", "metadata": { "id": "c0c8988a" }, @@ -19,25 +20,38 @@ "import os\n", "import pickle\n", "import pandas as pd\n", + "from collections import Counter\n", + "\n", "import librosa #for audio processing\n", "import librosa.display\n", - "\n" + "# import tensorflow as tf\n" + ] + }, + { + "cell_type": "code", + "execution_count": 5, + "id": "0f3e2190", + "metadata": {}, + "outputs": [], + "source": [ + "import helper\n" ] }, { "cell_type": "code", - "execution_count": 2, + "execution_count": 6, + "id": "8f21a9e9", "metadata": {}, "outputs": [], "source": [ "from data_augmentation import Data_Augmentation\n", - "from data_loader import DataLoader\n", - "import helper" + "from data_loader import DataLoader\n" ] }, { "cell_type": "code", - "execution_count": 3, + "execution_count": 7, + "id": "1a71decd", "metadata": { "id": "HOaIKtShaPnS" }, @@ -49,7 +63,8 @@ }, { "cell_type": "code", - "execution_count": 7, + "execution_count": 8, + "id": "4a6e0ca8", "metadata": { "id": "7PV5In98aX4m" }, @@ -57,12 +72,52 @@ "source": [ "train_audio_folder = train_path + \"/wav/\"\n", "train_script_file = train_path + \"trsTrain.txt\"\n", - "sample_rate = 22000" + "sample_rate = 8000" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "e99bc9bd", + "metadata": {}, + "outputs": [], + "source": [ + "test_audio_folder = test_path + \"/wav/\"\n", + "test_script_file = test_path + \"trsTrain.txt" + ] + }, + { + "cell_type": "code", + "execution_count": 7, + "id": "a28a20ce", + "metadata": {}, + "outputs": [], + "source": [ + "def clean_signal(signal, normalize = False ,trim_db = None, clean_db = None):\n", + "\n", + " if normalize:\n", + " feats_mean = np.mean(signal, axis=0)\n", + " feats_std = np.std(signal, axis=0)\n", + " signal = (signal - feats_mean) / (feats_std + 1e-14)\n", + "\n", + " if trim_db:\n", + " signal, index = librosa.effects.trim(signal, top_db=trim_db)\n", + "\n", + " if clean_db:\n", + " yt = librosa.effects.split(signal, top_db=clean_db)\n", + " clean_signal = []\n", + " for start_i, end_i in yt:\n", + " clean_signal.append( signal[start_i: end_i])\n", + "\n", + " signal = np.concatenate(np.array(clean_signal),axis=0)\n", + "\n", + " return signal" ] }, { "cell_type": "code", "execution_count": 8, + "id": "3a1da3e9", "metadata": {}, "outputs": [], "source": [ @@ -71,19 +126,31 @@ }, { "cell_type": "code", - "execution_count": 9, + "execution_count": null, + "id": "1c2f4050", + "metadata": {}, + "outputs": [], + "source": [ + "test_data_loader = DataLoader(train_audio_folder, train_script_file, sr=sample_rate)\n" + ] + }, + { + "cell_type": "code", + "execution_count": 11, + "id": "c114f207", "metadata": { "id": "jFTW5hIX6ids" }, "outputs": [], "source": [ "translation_obj = data_loader.extract_transcription_and_labels()\n", - "audio_dict = data_loader.extract_audio(100)" + "audio_dict = data_loader.extract_audio(5000)" ] }, { "cell_type": "code", - "execution_count": 10, + "execution_count": 12, + "id": "74f9e143", "metadata": { "id": "6CTYhPjR5frn" }, @@ -96,7 +163,8 @@ }, { "cell_type": "code", - "execution_count": 11, + "execution_count": 14, + "id": "73945c97", "metadata": { "id": "XwsX1sBJngY6" }, @@ -109,1013 +177,34 @@ }, { "cell_type": "code", - "execution_count": 12, + "execution_count": 15, + "id": "8dc1a7d1", + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "10875" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "display(len(translation_obj))" + ] + }, + { + "cell_type": "code", + "execution_count": 17, + "id": "f1056fa7", "metadata": {}, "outputs": [ { "data": { "text/plain": [ - "{'tr_1_tr01001': 'ያንደኛ ደረጃ ትምህርታቸው ን ጐንደር ተ ም ረዋል',\n", - " 'tr_2_tr01002': 'የተ ለቀቁት ምርኮኞች በ አካባቢያቸው ሰላማዊ ኑሮ እንዲ ኖሩ የ ትራንስፖርት ና መጓጓዣ ገንዘብ ተሰጥቷ ቸው መሸኘታቸው ን አመልክቶ በ የ ዞ ናቸው እንደ ደረሱ መቃቋሚያ እንደሚ ሰጣቸው ም አስ ታውቋል',\n", - " 'tr_3_tr01003': 'በ አዲስ አበባው ስታዲየም በ ተካሄዱ ት ሁለት ግጥሚያ ዎች በ መጀመሪያ የ ተገናኙ ት መድን ና ሙገር ሲሚንቶ ሲ ሆኑ በ ውጤቱ ም ሶስት ለ ሶስት ተለያይ ተዋል',\n", - " 'tr_4_tr01004': 'ወሬው ን ወሬ ያደረጉ ምስጢረ ኞች ናቸው',\n", - " 'tr_5_tr01005': 'ኢትዮጵያዊ ቷ በ ብሄራዊ ባህላዊ አለባበስ ከ አለም አንደኝነት ን ተቀዳጀ ች',\n", - " 'tr_6_tr01006': 'ከ ትምክህት እንዳይ ቆጠር ብን እንጂ በ አለም ታሪክ ውስጥ በ ነጮች ያል ተረገጠ ች አገር ኢትዮጵያ ና ት',\n", - " 'tr_7_tr01007': 'እህቶቹ የኤርትራ ዜጐች ና የ ሻእቢያ ደጋፊዎች ናቸው',\n", - " 'tr_8_tr01008': 'እናንተ ም መቀበሪያ እንዳ ታጡ ተጠንቀቁ',\n", - " 'tr_9_tr01009': 'አንቶኔሊ በ አጼ ምንሊክ ፊት የ ፈጸመው ድፍረት በ ኢጣሊያ ን ምክር ቤት አስተ ቸው',\n", - " 'tr_10_tr01010': 'ግን ወደ ኋላው ላይ ኢሳያስ እንደ ልማ ዳቸው ሁሉን ም የ መልከ ፍ ዲፕሎማሲ ያቸው እስራኤል ንም ያስ ወር ፋቸው ጀመር',\n", - " 'tr_11_tr01011': 'ከ የ አቅጣጫ ው እየ ደረሷቸው ያሉ መረጃዎች አሳሳቢ ችግሮች እየ ደረሱ መሆናቸው ን የሚ ጠቁሙ መሆናቸው ን ፕሬዝዳንቱ ተናግረ ዋል',\n", - " 'tr_12_tr01012': 'ከ ማወቁ በፊት እንደ ተበጠበጠ ገበያ እንዳይ በታተን ይህ ነው አጀንዳ ችን ሌላ አጀንዳ የ ለ ንም',\n", - " 'tr_13_tr01013': 'ኢትዮጵያ ም ሰራዊቷ በ ኤርትራ እንደሚ ገኝ አል ካደ ችም',\n", - " 'tr_14_tr01014': 'ላቁኦተ ትምህርት ቤት መንገድ ና ሆስፒታል ተ ገንብቷል',\n", - " 'tr_15_tr01015': 'ኦስሪያን በ ሀገሩ አንድ ለ ዜሮ አሸንፎ ሶስት ነጥብ ይ ዟል',\n", - " 'tr_16_tr01016': 'ሁሴን አይዲድ እንደ ገለጹት ኢትዮጵያ ሁኔታዎች ከ ተመቻቹ ላት ሶማሊያ ን ከ መውረር ስለማ ት መለስ ከ እርቁ ይልቅ ሶማሊያ ን ከ ኢትዩጵያ ና ኢትዮጵያ ካ ደራጀ ቻቸው ሀይሎች ለ መጠበቅ መዘጋጀት ያስፈልጋ ል',\n", - " 'tr_17_tr01017': 'በ ሙስና ክስ የ ተመሰረተባቸው ነጋዴዎች መገናኛ ብዙሀን ን ከሰሱ',\n", - " 'tr_18_tr01018': 'ኢትዮጵያ የመን ና ሱዳን ኢሳያስ ን ለ ማውረድ ተስማም ተዋል ተ ባለ',\n", - " 'tr_19_tr01019': 'ለማ ን አቤት ማለት እንደሚ ቻል ም ግራ ገብቶ ናል በ ማለት ነጋዴ ዎቹ ብሶ ታቸውን ገልጸዋል',\n", - " 'tr_20_tr01020': 'በ ኢትዮጵያውያ ን ብቻ ሳን ወሰን የ ኢትዮጵያ ወዳጆች የሆኑ የ ኢትዮጵያ ታሪክ አዋቂዎች ም በ ውጪ የሚገኙ በዚህ ስራ ላይ ተሳታፊ እንዲሆኑ ጥረት አድርገ ናል',\n", - " 'tr_21_tr01021': 'ኢትዮጵያ ውስጥ የ ነበሩት ኤርትራውያን ም ተመሳሳይ እድል ነበራቸው',\n", - " 'tr_22_tr01022': 'የ ደህንነት ኢሚግሬሽን ና ስደተኞች ባለስልጣን ሰራተኞች በ በኩላቸው ተጓዦቹ ሰነዱ ን እንዲ ያሟሉ ለ ቀይ መስቀል ኮሚቴው ማስታወ ቃቸው ን ተናግረ ዋል',\n", - " 'tr_23_tr01023': 'ሁለት መቶ ሺ ያህሉ ደግሞ አብዛኛዎቹ ሲ ሰደዱ ቀሪዎቹ ሞ ተዋል ወይን ም ተ ሸሽገ ዋል',\n", - " 'tr_24_tr01024': 'ዛሬ ም ደግ መ ን ይህንኑ እን ላለን',\n", - " 'tr_25_tr01025': 'በ ቦሌ አለም አቀፍ አውሮፕላን ማረፊያ ጸረ ናርኮቲክ የ ቁጥጥር ክፍል አደገኛ እጾች አዘዋዋሪ ዎች ኢትዮጵያ ን መሸጋገሪያ እንዳያ ደርጓት ማሳሰቡ ን በ ዘገባው አ ስፍሯል',\n", - " 'tr_26_tr01026': 'ዘጠና ሁለት ኢትዮጵያውያ ን የ ደረሱበት ጠፉ',\n", - " 'tr_27_tr01027': 'መረጃ ያልተገኘ ባቸው ቤታቸው ናቸው በ ማለት ምላሽ ሰጥተዋል',\n", - " 'tr_28_tr01028': 'ኮንፍረንሱ ን የ መሩት ስር ዊሊያም ራሪ አዲስ ፎረ ም ለአፍሪካ ኢንቬስተመንት አዲስ ራእይ እንደሆነ ገልጸዋል',\n", - " 'tr_29_tr01029': 'መላእክት ያጀቡ ት ህጻን ቦረና ህጻናት ን የሚጠብቁ ና የሚንከባከ ቧቸው መላእክት አሉ ይባላል',\n", - " 'tr_30_tr01030': 'እውቅና ን መ ጐናጸፍ መጥፎ ጐን እንዳለው በሚገባ ተረድ ቻለሁ',\n", - " 'tr_31_tr01031': 'እውቅና ን ማግኘቴ ለ እኔ ትልቅ ክብር ነው',\n", - " 'tr_32_tr01032': 'ም ን ለማ ለት ነው ግልጽ አድርገው',\n", - " 'tr_33_tr01033': 'ከዚያ በ ተጨማሪ የ ስልጠና ውን ሂደት የሚ ያሻሽል ላቸው ይ ሻሉ',\n", - " 'tr_34_tr01034': 'ጨዋታው ቀጥሎ ፔናልቲ ውስጥ ቺላቬርት ኳስ ያገኝ ና ሳ ያውቅ ለ ፓሌርሞ ያቀ ብለዋል',\n", - " 'tr_35_tr01035': 'አንዋር ጊዮርጊስ ሊገባ ነው',\n", - " 'tr_36_tr01036': 'ሆን ተብሎ ም እየተደረገ ብኝ ነው',\n", - " 'tr_37_tr01037': 'ጨዋታው የሚ ከናወነው ሚያዝያ አስራ ስምንት ቀን ነው',\n", - " 'tr_38_tr01038': 'ኢንጂነር ግዛው ተክለ ማሪያም ግልጽ ባልሆነ ምክንያት ከ ተጫዋቾቹ ጋር ሳይ ተዋወቁ ቀር ተዋል',\n", - " 'tr_39_tr01039': 'ደንቡ ን ያጸደቀ ው የ ፌዴራል እ ስፖርት ምክር ቤት ነው',\n", - " 'tr_40_tr01040': 'ያን ን ማ ፕሮግራም ያወጡ ት እ ኮ እነ ክቡር አቶ ይድነቃቸው ተሰማ ናቸው',\n", - " 'tr_41_tr01041': 'እንዲያ ውም እንደሚ ወራው ሊፒ ጁቬንትስ ዘንድሮ ለ ቻምፒየንስ ሊግ ድል ማብቃት ና ስማቸው ን መጠበቅ ነው አላማቸው',\n", - " 'tr_42_tr01042': 'ሞዛምቢክ ን ያሸነፈ ው ታዳጊ ቡድናችን ትላንት ጠዋት አዲስ አባ ገባ',\n", - " 'tr_43_tr01043': 'በ አቶ ወንድሙ እምነት ኢትዮጵያውያኑ በ አገራቸው የተደላደለ ኑሮ ሊኖሩ በ ቻሉ',\n", - " 'tr_44_tr01044': 'ስንት ና ስንት ጀግኖች እንደ ወጡ ቀር ተዋል',\n", - " 'tr_45_tr01045': 'በ ኢትዮጵያ በ ድርቅ ለ ተጐዱ እስካሁን የተገኘው አርባ ሺ ዶላር ብቻ ነው',\n", - " 'tr_46_tr01046': 'ተጨማሪ የ ኢትዮጵያ ወታደሮች ሰሞኑ ን ሱማሊያ ገቡ',\n", - " 'tr_47_tr01047': 'ጠቅላይ ሚኒስትሩ አዲስ አበባ ውስጥ ለሚገኙ ዲፕሎማቶች ማብራሪያ በ ሰጡበት ወቅት ወረራው በ ሰላማዊ መንገድ ሊ ወገድ ስለ መቻሉ እስካሁን ፍንጭ አለማ የ ታቸውን ገልጠዋል',\n", - " 'tr_48_tr01048': 'የ ኢትዮጵያ ና የኤርትራ ባለስልጣናት ነገ ይገናኛ ሉ',\n", - " 'tr_49_tr01049': 'በ ስምንት ነጥብ ሰባት ሚሊዮን ብር እዳ ክስ ሊ መሰረት ነው',\n", - " 'tr_50_tr01050': 'የ ኢትዮጵያ ሚሊሺያ ዎች የ ኬንያ ን ድንበር ጥሰው ጉዳት ማድረሳቸው ን እናውቃለን ብለዋል',\n", - " 'tr_51_tr01051': 'ሚኒስትሩ አቶ ስዩም መስፍን ን ለ ማሳመን እየ ጣሩ መሆኑን ለ ጉዳዩ ቅርበት ያ ላቸው ምንጮች ተናግረ ዋል',\n", - " 'tr_52_tr01052': 'ይህም በ ኢትዮጵያ የ ዋጋ መውደቅ ን ያስከትላል',\n", - " 'tr_53_tr01053': 'ምርጫ ችን ደግሞ የማ ያቋርጥ ስደት ሆነ',\n", - " 'tr_54_tr01054': 'ወደ ትንተና ውስጥ ነበር የ ገባው',\n", - " 'tr_55_tr01055': 'እንዲ ህ እንደ ሱ የማከብራቸው ሰዎች ብዙ አይደሉም',\n", - " 'tr_56_tr01056': 'ማን ሞቶ ማን ነጻ እንዲ ወጣ ነው የሚ ፈለገው እዚህ አገር ውስጥ እ ያንዳንዳችን ለ ራሳችን መቆም አለ ብን የሚሉ ነበሩ',\n", - " 'tr_57_tr01057': 'በ ዋሽንግተን ዲሲ ና በ አካባቢ ዋ ማለት ም በ ሜሪላንድ ና በ ቨርጂኒያ ስቴ ቶች ላሉ ኤርትራውያን ና ለ ኢትዮጵያውያ ንም ጭምር ለ ፕሮፖጋንዳ የሚ ጠቅመው የ ሬዲዮ አገልግሎት ጀም ሯል',\n", - " 'tr_58_tr01058': 'አስከሬ ን አጃቢ ዎች በ ዱላ ተ ደበደቡ',\n", - " 'tr_59_tr01059': 'ህገወጥ ግድያ ና እስራት እንዲ ቆም ተጠየቀ',\n", - " 'tr_60_tr01060': 'ሻእቢያ ከ ስድስት መቶ በላይ ኢትዮጵያውያ ን አስሮ እ ያሰቃ የ ነው',\n", - " 'tr_61_tr01061': 'መንግስት በ ኢንቨስትመንት እንቅስቃሴ ላይ የ ተከሰቱ የ ፖሊሲ ና የ አሰራር ግድፈቶች ን ለ ማስወገድ እርምጃ መውሰዱ ከ ግሉ ኢንቨስትመንት ፍሰት የ ሚገኘው ን ድርሻ እንደሚያ ሻሽለው ም ገለጹ',\n", - " 'tr_62_tr01062': 'እኔ ግን ነፍጠኛ ም መድፈኛ ም እንዳል ሆ ኩኝ ልንገራችሁ ብዬ እንጂ ፖለቲከኛ ሳል ሆን አሽሙረኛ ነኝ ብዬ እናንተ ን ላሳምናችሁ አል ሞክር ም',\n", - " 'tr_63_tr01063': 'ኮሎኔል በዛብህ ጴጥሮስ የ አማራጭ ሀይሎች ሊቀመንበር የ ዶክተር በየነ ጴጥሮስ ወንድም መሆናቸው ተያይዞ ተ ገልጿ ል',\n", - " 'tr_64_tr01064': 'የ መስተዳድሩ መግለጫ ከተማዋ ስር ነቀል ለውጥ እንደሚ ያስፈልጋት ገልጾ ህዝቡ በዚህ እንዲ ሳተፍ ቢ ጠይቅ ም ጊዜያዊ መስተዳድሩ የ መዋቅር ለውጡ ን ያስፈጽማል ተብሎ አይጠበቅ ም',\n", - " 'tr_65_tr01065': 'ለወደፊቱ በሚ ዘጋጀው ጉባኤ የ በ ኩሌን ሀሳብ ለ ካድሬው ይዤ አቀርባ ለሁ',\n", - " 'tr_66_tr01066': 'ኤኤፍፒ ከ ሶስት ሺ በላይ የኤርትራ ኩናማ ዎች ወደ ኢትዮጵያ ሸሽተው በ መግባት የኤርትራ ሰራዊት በ ሀይል እየ መለመላቸው ነው ሲሉ ውንጀላ ሰንዝ ረዋል',\n", - " 'tr_67_tr01067': 'ዋናው አላማችን አባላ ቶቻችን በ ስፖርቱ ተሳታፊ እንዲሆኑ ና ለ ሀገራችን ስፖርት የ በኩላቸው ን አስተዋጽኦ እንዲ ያበረክቱ እንጂ እንደ አንዳንድ ክለቦች ድርጅት ን ለ ማስተዋወቅ አይደለም',\n", - " 'tr_68_tr01068': 'በ ማጠቃለያ ውም በ እርዳታ አ ሰባሰቡ ወቅት ኢህአዲግ በ በጐ አይ ን የማ ይመለከታቸው ና በ አሸባሪነት ጠርጥሬ ያ ቸዋለሁ የሚ ላቸው ኢትዮጵያውያ ን የ ህግ ታራሚዎች ሳይ ቀሩ በ እርዳታው ተሳትፎ ማድረጋቸው ን አመልክ ቷል',\n", - " 'tr_69_tr01069': 'አውደ ጥናቱ ችግሩ ን ለ መቅረፍ የ ተጀመሩ ጥረቶች ን ለ ማገዝ የ ሚያስችል እንደሆነ ም ገልጸዋል',\n", - " 'tr_70_tr01070': 'የሚ ሆነው እውነተኛ ወሬ ዜና ነው',\n", - " 'tr_71_tr01071': 'ይሄን ኛው ን አዋጅ እንዴት እንደ ተቀበሉት ባ ና ውቅም ቅሉ እንዲ ህ ተነቦ ነበር',\n", - " 'tr_72_tr01072': 'ኢህአዲግ ያለ ተወዳዳሪ ብቻ ውን ሮጦ ብቻ ውን ነው ያሸነፈ ው',\n", - " 'tr_73_tr01073': 'ይህ ስ ከ ተጽእኖ ዎቹ አንዱ ሊሆን አይችልም',\n", - " 'tr_74_tr01074': 'ይሁን እንጂ ውሳኔው ቀደም ብሎ የተጻፈ ና የ ተፈረመ በመሆኑ የ እለቱ ን ችሎት እንደማያስ ተጓጉለው አቶ መንበረ ጸሀይ ገልጸው ብይኑ ንና ትእዛዙ ን ማሰማት ቀጥ ለዋል',\n", - " 'tr_75_tr01075': 'አስራ ሁለታችን ን ከ ማእከላዊ ኮሚቴ ለ ማገድ የተወሰደ እርምጃ ነው',\n", - " 'tr_76_tr01076': 'አዲስ አበባ ውስጥ ያሉት ሰራተኞች ተቃውሞ የሚያቀርቡ ት ከ ከተማ ላለ መውጣት ነው',\n", - " 'tr_77_tr01077': 'የ ዩኒቨርስቲ ተማሪዎች በ አውሮፕላን እንዳይ ሳ ፈሩ ተከለከለ',\n", - " 'tr_78_tr01078': 'ምግቡ ለ ኢትዮጵያ ሰራዊት እንዳይደርስ ዋስትና መሰጠት አለ በት',\n", - " 'tr_79_tr01079': 'የ ኢትዮጵያ ና የኤርትራ ልኡካን አሜሪካ ውስጥ ሊ ነጋገሩ ነው',\n", - " 'tr_80_tr01080': 'አጽማቸው አፋር ክልል እንዳረፈ ም የሚናገሩ ምንጮች አሉ',\n", - " 'tr_81_tr01081': 'የ ማህበሩ መሪ ዶክተር ታዬ ወልደሰማያት ማስረጃ በ ሌለው ና ባል ተጣራ ምክንያት ለ እስር በቅ ተዋል',\n", - " 'tr_82_tr01082': 'በ ደጀን ሙስሊሞች ብሩህ ተስፋ ይታ ያል',\n", - " 'tr_83_tr01083': 'ማክሰኞ አዲስ አበባ ላይ በ አስር ሰአት ባንኮች ከ ትራንስ ኢትዮጵያ ነበር የ ተጫወቱ ት',\n", - " 'tr_84_tr01084': 'አ ና ም ዶክተር ሊ ዲዮ ቶሌዶ ከ ረዳታቸው ከ ዶክተር ጆ ሀኪም ዳ ሞታ ጋር በ መሆን ሮናልዶ ን ወደ ሊ ላስ ክሊኒክ ይወስዱ ታል',\n", - " 'tr_85_tr01085': 'ለ ምሳሌ ዲዮ ን ደብሊን ን ፓትሪክ ኩላይቨርት ን ን ሮናልድ ዴ ቦዬርን ና የኢንተሩ ን ንዋንክዎ ካኑ ን ለ መውሰድ ድርድር ጀምረው መጨረሻው ን ሳያዩ ት ተዋል',\n", - " 'tr_86_tr01086': 'እ ውን ኢትዮጵያ ቡና ልት ገባ ነው ላንተ ያለ ኝ አድናቆት ፍጹም ልዩ ነው',\n", - " 'tr_87_tr01087': 'ካፍ በ ግንቦት ወር ለ ሶስት እጩ ኢንስ ትራክተሮች በ ግብጽ ኮርስ እንደሚ ሰጥ አያይዘው አስረድ ተዋል',\n", - " 'tr_88_tr01088': 'በ ኔ ላይ እምነት እንዳለው ገለጸ ልኝ',\n", - " 'tr_89_tr01089': 'የ ኢትዮጵያ አየር መንገድ አውሮፕላኖቹ ን በ ሁለት ና በ ሶስት አመታት ውስጥ በ አዲሶቹ ለ መተካት እቅድ እንዳለው ገለጠ',\n", - " 'tr_90_tr01090': 'እርስዎ ስ ንግድ ዎን ለ ማስፋፋት ይኸ ን ን የ መገናኛ መሳሪያ አስብ ው በታል ን',\n", - " 'tr_91_tr01091': 'ኩባንያው ሰባ አንድ ነጥብ ሰማኒያ አምስት አክሲዮ ኖች ሲ ኖሩት እ ያንዳንዷ አክሲዮን አምስት ሺ ብር ዋጋ አላ ት',\n", - " 'tr_92_tr01092': 'የመንግስት መዋቅሮች ደካሞች ናቸው',\n", - " 'tr_93_tr01093': 'አንዳንዴ ም ሲያ ቃዣ ቸው የ ጐሰኛ ኢትዮጵያ ን ፈጥረ ናል ህዝቦች ፈንጥዘው በ ኢትዮጵያዊ ነታቸው ኮር ተው ተቀብለው ናል ለማ ለት ይዳዳ ቸዋል',\n", - " 'tr_94_tr01094': 'ስለዚህ ም እንደ ገና የ ረሀቡ ን ቁልቁለት ይ ያያ ዘዋል',\n", - " 'tr_95_tr01095': 'እነዚህ ና የ መሳሰሉት ድሎች የ ዚያ ትውልድ አባላት እንደ ጧፍ በር ተው እንደ ሰም ቀል ጠው የ ተገኙ ድሎች ናቸው',\n", - " 'tr_96_tr01096': 'እድሜ አቸው ጠና ያሉ አንድ አዛውንት ገበሬ እንዲ ህ አሉ',\n", - " 'tr_97_tr01097': 'ስንቅ ማቅረብ እጅግ አ ዳግ ቶታል',\n", - " 'tr_98_tr01098': 'እኔ ም ዛሬ አንድ ያደረገ ን ምክንያት በ መፈጠሩ ደስ ብሎ ኛል',\n", - " 'tr_99_tr01099': 'እነሆ ከ አስር አመት በኋላ ሼህ አላሙዲ ን ያቺ ን ወጣት እዚያ ው የ ተዋወቁ በት ዋሽንግተን ውስጥ በ ደመቀ ሰርግ አገ ቧት',\n", - " 'tr_100_tr01100': 'አለቃ የጻፏቸው መጽሀፍት ውድ ና ጣፋጭ ከ መሆናቸው የተነሳ በ ህትመታቸው ወቅት ገዝተው ከሚ ጠቀሙ ት ብልህ ዎች በስተቀር ዘግይተው የ ሚፈልጓቸው ሰዎች አ ያገኟቸው ም',\n", - " 'tr_101_tr02001': 'በ ኮምፒውተር ሳይንስ ፎን ት ቴክኖሎጂ ለ ዶክትሬት ዲግሪ ጥናት እያደረጉ የሚገኙት ን አቶ ፍቅሬ ን የ ዛሬው እንግዳ ችን አድርገ ና ቸዋል',\n", - " 'tr_102_tr02002': 'የ ውሀው ዘርፍ ያለበት ን የ ፋይናንስ ችግር ለ መፍታት የ ውሀ ሀብት ልማት ፈንድ እንደሚ ቋቋም ገለጹ',\n", - " 'tr_103_tr02003': 'የ መንገደኞች ማስተናገጃ ህንጻው በ ሰአት እስከ ሶስት ሺ ያህል መንገደኞች ን ማስተናገድ ይችላል',\n", - " 'tr_104_tr02004': 'መቼም ትላንት ጀምሮ የሰኔ ጾም ገብቷል',\n", - " 'tr_105_tr02005': 'ሚስት አ ግብተው ሶስት ልጆች በት ነው የ ጠፉት ቄስ ፊሊ ጶ ስ ደብር ተገኙ',\n", - " 'tr_106_tr02006': 'አፍሪካ ውስጥ ከሚገኙ ት አገሮች ም እንኳ ን ስ ልት ገዛ ቀርቶ እርሷ እራሷ ገዢ ተ ብላ በ ዘመነ ኞቹ ተፈርጃ ለች',\n", - " 'tr_107_tr02007': 'በ ኬንያ መንግስት በ ኘሮ ፌሽና ሎች የ ታቀፈ ግድያ ማለቱ ተ ገልጧል',\n", - " 'tr_108_tr02008': 'ፓትርያርኩ ንም እንዳት ቃወ ሟቸው በ ማለት ማስጠንቀቂያ ና ዛቻ አዘል ትምህርት መስጠታቸው ነው',\n", - " 'tr_109_tr02009': 'የሚደረግ ባቸውን በደል ና ተንኮል በ ቸልታ ያለፉ መስለው ያደ ባሉ',\n", - " 'tr_110_tr02010': 'እስራኤል የ ኢትዮጵያ ደጋፊ ና ት በ ማለት ወቀሱ',\n", - " 'tr_111_tr02011': 'ንግድ ባንክ ን ያስ ተዳድራ ሉ የተባሉት ህንዶች አን መጣ ም አሉ',\n", - " 'tr_112_tr02012': 'ጥያቄዎች ያሉት ይ ጠይቅ ያጣራ',\n", - " 'tr_113_tr02013': 'የ ኢትዮጵያ አላማ አሁን ግቡ ን መ ቷል',\n", - " 'tr_114_tr02014': 'ገዢው ፓርቲ የ ህወሀት የ ሞኖፖሊ ኩባንያዎች ተደራጅተው ኢኮኖሚው ን መቆጣጠራቸው ን ይቃወ ማሉ',\n", - " 'tr_115_tr02015': 'አባ ጳውሎስ በ እንቁላል ተ ደበደቡ',\n", - " 'tr_116_tr02016': 'የ ሱዳን ና የ ኢትዮጵያ ድንበር ስብሰባ ዛሬ ይጀ መራል',\n", - " 'tr_117_tr02017': 'የ ኢትዮጵያ መንግስት ወደ ሶማሊያ ወታደሮች ልኳ ል መባሉ ን አስተባ በሉ',\n", - " 'tr_118_tr02018': 'ፕሬዚዳንቱ በ ጉባኤው ላይ የ ኢትዮጵያ ን አቋም የሚያ ንጸባርቅ ንግግር እንደሚያደርጉ ይጠበቃል',\n", - " 'tr_119_tr02019': 'የ ተባበሩት መንግስታት ድርጅት ኢትዮጵያ ውጊያው ን እንድታ ቆም ጠየቀ',\n", - " 'tr_120_tr02020': 'የመጀመሪያ ው ምክንያት ሁኔታው ን ለማፋጠን ነው',\n", - " 'tr_121_tr02021': 'ስለሆነ ም ኢትዮጵያውያ ን እንደ ማንኛውም የውጭ ዜጋ መታየት ያለ ባቸው ጊዜ ደርሷ ል ብለዋል',\n", - " 'tr_122_tr02022': 'የ አለም ህዝቦች ኢትዮጵያ ን ከሚ ያውቁ በት ታሪካዊ ክስተቶች አንዱ የ ኦሎምፒክ መድረክ ነው',\n", - " 'tr_123_tr02023': 'አብዛኛዎቹ ባህላቸው እንደሚ ፈቅድላቸው ይናገራሉ',\n", - " 'tr_124_tr02024': 'ይህ የ ጸና አቋማችን ለ ወዳጆቻችን ም ሆነ ለገዳዮ ቻችን ግልጽ ሊሆን ይገባል',\n", - " 'tr_125_tr02025': 'በ ተጨማሪ ም ም ንም አይነት የ ውጪ ቋንቋ ያለ መቻላቸው በ ቁጥጥሩ ስራ ላይ አሉታዊ ተጽእኖ እንዳለው ዘገባው ያስረዳ ል',\n", - " 'tr_126_tr02026': 'ከ ተመላሽ ኢትዮጵያውያ ን የ ሚገኘው መረጃ እስረኞቹ ግፍ ና በደል እየ ተፈጸመባቸው ነው የሚ ል መሆኑን አስ ታውቋል',\n", - " 'tr_127_tr02027': 'ኢትዮጵያ ና ግብጽ ስለ አባይ ሊ ነጋገሩ ነው',\n", - " 'tr_128_tr02028': 'በ ኮንፈረንሱ ላይ ከ አራት መቶ የማ ያንሱ የተለያዩ ኩባንያዎች ና ሀገሮች ተወካዮች እንዲሁም የውጭ ሀገር ጋዜጠኞች ተገኝ ተዋል',\n", - " 'tr_129_tr02029': 'የ አቶ በሽር ገለቴ ን ስድስት ላሞች አውጥተው ሲ ኳት ኑ አደሩ',\n", - " 'tr_130_tr02030': 'ቤተሰብ ህ ውስጥ እግር ኳስ ትልቅ ቦታ አለ ው ተብሎ ተጠይቆ ኤዌን ሲ መልስ አ ዎን አባቴ ቴሪ ፕሮፌሽናል ኳስ ተጫዋች ነበር ብሏል',\n", - " 'tr_131_tr02031': 'አንዳንድ ሴቶች ደግሞ ይመጡ ና ሳመ ን ይሉ ኛል',\n", - " 'tr_132_tr02032': 'ተጫዋቾቹ ብዙ የሚያ ማርሩ በት ነገር አለ',\n", - " 'tr_133_tr02033': 'በጣም ዲሲፕሊን አክባሪ ነው',\n", - " 'tr_134_tr02034': 'ሊቨርፑል ኤዌን ን ለ ተጨማሪ አመታት ኮንትራት ሊያስ ፈርመው ደሞዙ ን በ እጥፍ አሳድጐ ለታል',\n", - " 'tr_135_tr02035': 'በ ኦሮሚያ ክልል የተወሰኑ ጥቂት ቡድኖች ሊኖሩ እንደሚ ችሉ ያገኘ ነው መረጃ ይ ጠቁ ማል',\n", - " 'tr_136_tr02036': 'ምክንያቱ ም ተጫዋቾቹ ትንፋሽ ስለሚ ኖራቸው እንደ ፈለጋቸው ለ መንቀሳቀስ ይችላሉ',\n", - " 'tr_137_tr02037': 'የ ባባንጊዳ አዲስ ባለቤት በ እናትዋ ኢትዮጵያዊ ት ስት ሆን በ ቅርቡ እዚህ አዲስ አባ መጥታ እንደ ነበር ታውቋል',\n", - " 'tr_138_tr02038': 'ለምን ስ እና ንገላታ ቸዋለን የሚ ል አስተያየት ሰንዝ ረዋል',\n", - " 'tr_139_tr02039': 'ይኸው ችግር በ ኢትዮጵያ አትሌቲክስ ፌዴሬሽን ውስጥ መከሰት ጀም ሯል',\n", - " 'tr_140_tr02040': 'ሁለቱ አሸናፊዎች ለ ኢትዮጵያ ሻምፒዮና ያል ፋሉ',\n", - " 'tr_141_tr02041': 'ነገሩን የሚያ ጠናክረው የ ጁቬ ሀላፊዎች ዘወትር ከ ቪያሊ ጋር በ ስልክ እንደሚ ገናኙ ስለሚ ታወቅ ነው',\n", - " 'tr_142_tr02042': 'የ ኢትዮጵያ ታዳጊ ቡድን የ ሞዛምቢክ አቻው ን አሸንፎ ትላንትና ጠዋት አዲስ አባ ገብቷል',\n", - " 'tr_143_tr02043': 'ኢትዮጵያ በ አንሚ ላይ አዲስ ትእዛዝ አ ወጣች',\n", - " 'tr_144_tr02044': 'እናቶች አባቶች ወንድሞች ና እህቶች ያለ ጧሪ ና ተቆርቋሪ ቀር ተዋል',\n", - " 'tr_145_tr02045': 'በ ላሊበላ ግን ሁሉም ተ ደንቀው ተ ገርመው ና እንደ ተደሰቱ ይናገራሉ',\n", - " 'tr_146_tr02046': 'የ ኢትዮጵያ መንግስት በ አካባቢው አሉ ብሎ የሚ ጠረጥ ራቸውን ተቃዋሚዎች እንቅስቃሴ ለ መግታት በ ቅርቡ ወደ ሱማሊያ ተጨማሪ ሰራዊቱ ን እንዳስገባ ሲ ሲ አይ የ ተሰኘው ሬድዮ ገልጿ ል',\n", - " 'tr_147_tr02047': 'የ ተማሪዎቹ አመጽ ቀጥ ሏል ወደ ሌሎች ዩኒቨርስቲ ዎችም ተዛ ም ቷል',\n", - " 'tr_148_tr02048': 'የ ሟች ማንነት ን ሙሉ በ ሙሉ እንዳል ተደረሰበት ፖሊስ አስ ታውቋል',\n", - " 'tr_149_tr02049': 'ስድስት መቶ የሚሆኑ የ ኢትዮጵያ ና የ ሶማሊያ ስደተኞች የመን ገቡ',\n", - " 'tr_150_tr02050': 'በ ተጨማሪ ም ኢትዮጵያ ውስጥ ውንብድና ፈጽመው ወደ ኬንያ የ ገቡት ን ሽፍቶች ሽፋን ሲሰጡ ቆይ ተዋል',\n", - " 'tr_151_tr02051': 'ስህተት ያለበት የ ምርጫ ቅጽ ተገኘ',\n", - " 'tr_152_tr02052': 'ይህኛው ዘዴ ካልሰራ ኢህአዴግ ን ማለት ም የ ኢትዮጵያ ን መንግስት ሊ ያዳክሙ የሚችሉ እርምጃ ዎችን ይወስዳ ል',\n", - " 'tr_153_tr02053': 'አገር እያስ ረከብ ን ነው ከ ወጣ ን ስ በኋላ ም ን ሰራ ን ስለ ስደት ና ስደተኞች ውይይታችን ን እን ቀጥል',\n", - " 'tr_154_tr02054': 'አንዳንድ ጊዜ እንደ ጮሌ ስለሚያ ደርገኝ ስለሚ ሞክረ ኝ እጄ ን አልሰጠ ሁም',\n", - " 'tr_155_tr02055': 'ዛሬ ብዙዎቻችን ማተባ ችንን በ ጥሰን ወይም ቆርጠን ጥለናል',\n", - " 'tr_156_tr02056': 'በ ኢትዮጵያ ም በኩል ተመሳሳይ እርምጃ ዎች እየ ታዩ ናቸው',\n", - " 'tr_157_tr02057': 'ይህ በዚህ እንዳለ ዋሽንግተን ዲሲ የ ሚገኘው የ ኢትዮጵያ ኤምባሲ ለ ቅስቀሳ ና ለ ፕሮፓጋንዳ ተግባር በር ከ ት ያሉ ሰዎች ለ መቅጠር ማስታወቂያ ዎችን በ ሬዲዮ እያ ሰማ ይገኛል',\n", - " 'tr_158_tr02058': 'የ ዋሽንግተን ዲሲ የ ጦቢያ ሪፖርተር እንደ ዘገበው ከ ዳላስ ቴክሳስ ሌሊት መኪና እየ ነዱ የ መጡ ኢትዮጵያውያ ን ነበሩ',\n", - " 'tr_159_tr02059': 'አንደኛ የ ጤና ና የ ተፈጥሮ ሳይንስ ተማሪዎች የሚ ገለገሉ ባቸው በተለይ ም የ ተፈጥሮ ሳይንስ ተማሪዎች ላቦራቶሪ ዎች ለ አንደኛ አመት ተማሪዎች ብቻ ሊ ያገለግሉ የሚችሉ ናቸው',\n", - " 'tr_160_tr02060': 'የ ሻእቢያ መንግስት ከ ሀገሩ የሚያስ ወጣቸው የ ኢትዮጵያውያ ን አብዛኞቹ የተ ደበደቡ የተ ገረፉ የ ተዘረፉ ና በተለይ ም ሴቶቹ የ ተደፈሩ መሆናቸው ን ዘመን አስ ታውቋል',\n", - " 'tr_161_tr02061': 'መንግስት በ ኢንቨስትመንት እንቅስቃሴ ላይ የ ተከሰቱ የ ፖሊሲ ና የ አሰራር ግድፈቶች ን ለ ማስወገጃ እርምጃ መውሰዱ ከ ግሉ ኢንቨስትመንት ፍሰት የ ሚገኘው ን ድርሻ እንደሚያ ሻሽለው ም ገለጹ',\n", - " 'tr_162_tr02062': 'እኔ ግን ነፍጠኛ ም መድፈኛ ም እንዳል ሆ ኩኝ ልንገራችሁ ብዬ እንጂ ፖለቲከኛ ሳል ሆን አሽሙረኛ ነኝ ብዬ እናንተ ን ላሳምናችሁ አል ሞክር ም',\n", - " 'tr_163_tr02063': 'ኮሎኔል በዛብህ ጴጥሮስ የ አማራጭ ሀይሎች ሊቀመንበር የ ዶክተር በየነ ጴጥሮስ ወንድም መሆናቸው ተያይዞ ተ ገልጿ ል',\n", - " 'tr_164_tr02064': 'የ መስተዳድሩ መግለጫ ከተማዋ ስር ነቀል ለውጥ እንደሚ ያስፈልጋት ገልጾ ህዝቡ በዚህ እንዲ ሳተፍ ቢ ጠይቅ ም ጊዜያዊ መስተዳድሩ የ መዋቅር ለውጡ ን ያስፈጽማል ተብሎ አይጠበቅ ም',\n", - " 'tr_165_tr02065': 'ለወደፊቱ በሚ ዘጋጀው ጉባኤ የ በ ኩሌን ሀሳብ ለ ካድሬው ይዤ አቀርባ ለሁ',\n", - " 'tr_166_tr02066': 'ኤኤፍፒ ከ ሶስት ሺ በላይ የኤርትራ ኩናማ ዎች ወደ ኢትዮጵያ ሸሽተው በ መግባት የኤርትራ ሰራዊት በ ሀይል እየ መለመላቸው ነው ሲሉ ውንጀላ ሰንዝ ረዋል',\n", - " 'tr_167_tr02067': 'ዋናው አላማችን አባሎቻችን ን በ ስፖርቱ ተሳታፊ እንዲሆኑ ና ለ ሀገራችን ስፖርት የ በኩላቸው ን አስተዋጽኦ እንዲ ያበረክቱ እንጂ እንደ አንዳንድ ክለቦች ድርጅት ን ለ ማስተዋወቅ አይደለም',\n", - " 'tr_168_tr02068': 'በ ማጠቃለያ ውም በ እርዳታ አ ሰባሰቡ ወቅት ኢህአዲግ በ በጐ አይ ን የማ ይመለከታቸው ና በ አሸባሪነት ጠርጥሬ ያ ቸዋለሁ የሚ ላቸው ኢትዮጵያውያ ን የ ህግ ታራሚዎች ሳይ ቀሩ በ እርዳታው ተሳትፎ ማድረጋቸው ን አመልክ ቷል',\n", - " 'tr_169_tr02069': 'ወረዳው በተ ለምዶ ገዳም ደጃች ው ቤ ና ጣሊያን ሰፈሮች የሚ ባሉት ን አካባቢዎች ያካተተ ነው',\n", - " 'tr_170_tr02070': 'ጉዳዩ አቶ መለስ ዘንድ እንዲደርስ ና ትእዛዝ እንዲሰጥ በት ተደርጓል',\n", - " 'tr_171_tr02071': 'እሱ ይቅር ና የ ዘበኞቹ ን ስራ እናውጋ ችሁ',\n", - " 'tr_172_tr02072': 'ኢህአዴግ የሚ ገዛቸው ተዋጊ ሄሊኮኘተሮች ከ ድል በኋላ ለ ተቃዋሚዎች እንደሚ ውሉ ተገለጠ',\n", - " 'tr_173_tr02073': 'ኢ ሰብአዊ ና ክብር ን የሚ ያዋርድ ቅጣት ተቀጡ',\n", - " 'tr_174_tr02074': 'የ ኢትዮጵያ ንግድ ባንክ የ ቦርድ አባላት ሊ ነሱ ነው',\n", - " 'tr_175_tr02075': 'በ ድርጅታችን ህገ ደንቡ ሶስት ማእከላዊ ተቋማት አሉ',\n", - " 'tr_176_tr02076': 'እነርሱ ን አባር ረን እናንተ ን በምት ካቸው እናስገባ ለ ን የሚሉ ማስፈራሪያ ዎችና ዛቻ ዎችም በ የ ስብሰ ዎቹ ላይ ቀርበዋል ተ ብሏል',\n", - " 'tr_177_tr02077': 'አንዳንድ ትኬት የ ቆረጡ ተማሪዎች ም እንዳይ ሳ ፈሩ ተከልክ ለዋል ሲሉ አ ማረሩ',\n", - " 'tr_178_tr02078': 'ኢትዮጵያ የተያዘ ባትን መሬት ለ ማስመለስ በ ሰላሙ መስክ ስላልተሳካ ላት የ ሀይል እርምጃ ተጠቅ ማለች',\n", - " 'tr_179_tr02079': 'የኤርትራ መንግስት ሰባ ዘጠኝ ኢትዮጵያውያ ን ን በ ግፍ አረደ',\n", - " 'tr_180_tr02080': 'ይህን እናንተ ም እኛ ም አሳ ም ረን እናውቃለን',\n", - " 'tr_181_tr02081': 'የ ኖርዌይ የ ማእድን ካምፓኒ ኢትዮጵያ ውስጥ እንዲ ሰራ ፈቃድ ተሰጠው',\n", - " 'tr_182_tr02082': 'በ ደጀን ሁለት መስጊዶች ይገኛሉ',\n", - " 'tr_183_tr02083': 'ኢትዮጵያ ቡና መድን ን በ ጨዋታ በልጦ ነው ያሸነፈ ው',\n", - " 'tr_184_tr02084': 'ይህንን ም ለ ቡድን መሪው ለ ጃን ፒየር ፍራን ኬን ሂስ ያስታው ቃሉ',\n", - " 'tr_185_tr02085': 'ቬንገር በተለይ አጥቂው ክፍል ሊ ያሳስባቸው ይገባል',\n", - " 'tr_186_tr02086': 'ቡቡ ኢትዮጵያ ቡና ሊገባ ነው የ ሚባለው ወሬ በ ሰፊው እየ ተወራ ነው',\n", - " 'tr_187_tr02087': 'ያሉት ን አባባል ለ መድገም ተገ ደናል',\n", - " 'tr_188_tr02088': 'እዚህ ሙኒክ ውስጥ ግን የማ ተኩረው ስራዬ ላይ ብቻ ነው',\n", - " 'tr_189_tr02089': 'ፕሬዚዳንት ነጋሶ አሁን ም በ ተጽእኖ ስር ናቸው',\n", - " 'tr_190_tr02090': 'እሺ እኔ ትግሬ ነኝ ኢትዮጵያዊ ም ነኝ',\n", - " 'tr_191_tr02091': 'የ ኢትዮጵያ ንግድ ባንክ አዲስ ቦርድ ተሾመ ለት',\n", - " 'tr_192_tr02092': 'ስራ አስፈጻሚው ም ጠቅላይ ሚኒስትሩ ም ውክልናው ለ ፓርላማው መሆን ሲ ገባው ለ ፓርቲው ነው',\n", - " 'tr_193_tr02093': 'አስተዳደግ አርቆ አስተዋይ ነት እንዲሁም ቀና የ ልማት አስተዋጽኦ ያጠና ክ ረዋል',\n", - " 'tr_194_tr02094': 'ለዚህ ም ነው የ ኢሀዴግ ሹሞች እየ ደጋገሙ ችጋር ን ማስ ወገዳቸው ንና አገሪቱ ን ወደ እህል ሻጭ ነት በ አጭር ጊዜ ውስጥ አደረሰ ን እያሉ የሚፎክሩት',\n", - " 'tr_195_tr02095': 'እንደ ኢህአፓ ከ መሳሰሉ ትናንሽ ድርጅቶች ጋር ግንኙነት ፈጥረው ከ ኢትዮጵያ መንግስት ጋር ያ ላቸውን ግንኙነት ማበላሸት አይ ሹም',\n", - " 'tr_196_tr02096': 'አንዱ ክፉ ኛ ቆስሎ ተመል ሷል',\n", - " 'tr_197_tr02097': 'ውስጥ አዋቂ ምንጮች እንደሚ ጠቁሙ ትም ኢትዮጵያ ውስጥ ያሉ ና እስካሁን ያል ተባረሩ ኤርትራውያን በ ጸረ ሻእቢያ ድርጅት እየ ተሰባሰቡ ናቸው',\n", - " 'tr_198_tr02098': 'የ ሻእቢያ መንግስት ከ ኢትዮጵያ ህዝብ ተለያይ ቷል',\n", - " 'tr_199_tr02099': 'በ አጥቂ መስመር ተሰልፎ የሚ ጫወተው አስራ ሁለት ቁጥሩ ከ አማካዮ ች የተሰጠ ውን ኳስ ያለምን ም ጭንቀት ያደርስ የነበረው ለ ጊዮርጊስ ተጫዋቾች ነበር',\n", - " 'tr_200_tr02100': 'ሁለቱ ባለስልጣናት በ ስብሰባው ላይ ድምጻቸው ን ከፍ አድርገው እስከ መጯጫህ ደርሰው እንደ ነበር የ ውስጥ አዋቂ ምንጮች ገልጸው ልናል',\n", - " 'tr_201_tr03001': 'የ ማስተር ስ ዲግሪ ዎን ካገኙ በኋላ በምን ስራ ተ ሰማሩ',\n", - " 'tr_202_tr03002': 'በ ኢትዮጵያ ና በ ሱዳን መካከል ያለውን ንግድ ና ኢንቨስትመንት ለ ማጠናከር የሚያስችሉ ተግባራት ይ ከናወ ና ሉ',\n", - " 'tr_203_tr03003': 'በውጭ ሀገር እያሉ በ ሞት በሚ ለዩ ባለመብት ኢትዮጵያውያ ንም መብታቸው ለ ወራሾቻቸው እንደሚጠበቅ አቶ ና ፖሊዮ ን ጨምረው ገልጸዋል',\n", - " 'tr_204_tr03004': 'ሱባኤ ገብቷል ትሉ ይሆናል',\n", - " 'tr_205_tr03005': 'መጋ ቤ ስርአት ግን በ መገኘታቸው ሰማይ መሬቱ ተደፋ ባቸው እና ም ምስኪን ዋን የ ሶስት ልጆች እናት ሚስት አላውቅ ሽም አይንሽ ን እንዳላ ይሽ የሚ ል መርዶ ይነግ ሯ ታል',\n", - " 'tr_206_tr03006': 'ለ ሱዳን መንግስት የ ገቡ አንጃዎች መሳሪያ ተነጠቁ',\n", - " 'tr_207_tr03007': 'በ ኤርትራ የሚገኙ ኢትዮጵያዊያ ን ወደ ሀገራቸው ለ መመለስ የሚያስ ች ሏቸው መንገዶች እየጠ በቡ መጥ ተዋል',\n", - " 'tr_208_tr03008': 'ኢሳያስ ኢትዮጵያ ን በ ሳኡዲ አሳ ቀሉ',\n", - " 'tr_209_tr03009': 'ከብሩ ሴል ጉባኤ የ አውሮፓ መንግስታት ኢትዮጵያ በ ጣሊያን መንግስት ስር እንድት ገዛ ሲ ስማሙ አጼ ምንሊክ ነገሩን በ ፌዝ አይ ተውታል',\n", - " 'tr_210_tr03010': 'ዋናው ፍላጐታቸው ንግድ ነው',\n", - " 'tr_211_tr03011': 'የ ኢትዮጵያ ንግድ ባንክ ን ማኔጅመንት ተ ረክበው እንዲ ያስተዳድሩ የ ተፈቀደላቸው ህንዶች እንደማይ መጡ በ ደብዳቤ አስ ታወቁ',\n", - " 'tr_212_tr03012': 'የሚ ያስፈልገን ነገር ቢኖር ኢን ፎሜሽን ነው',\n", - " 'tr_213_tr03013': 'የ ሶማሊያ አንጃ መሪ የ ኢትዮጵያ ጣልቃ ገብነት ተገቢ ነው አሉ',\n", - " 'tr_214_tr03014': 'ለ ተወካዮች ምክር ቤት ስድስት ለ ክክ ለ ክልል ምክር ቤት አስራ ስምንት እጩዎች አቅርቧ ል',\n", - " 'tr_215_tr03015': 'ከ ትናንት በስቲያ ም ኢትዮጵያ ብሩንዲ ን በ አምስት አምስት ም ቶች ሰባት ለ ስድስት የ ሩዋንዳ ሀ ኡጋንዳ ን ሶስት ለ ሁለት በሆነ ውጤት ረት ተዋል',\n", - " 'tr_216_tr03016': 'በ አቡነ ጢሞ ቲዎስ ምትክ አዲሱ የ ኢትዮጵያ ኦርቶዶክስ ተዋህዶ ቤተ ክርስቲያን ልማት ና ክርስቲያናዊ ኮሚሽን ኮሚሽነር ሆነው የ ተሾሙት ብጹእ አቡነ ኒምቆዲሞስ ናቸው ተ ብሏል',\n", - " 'tr_217_tr03017': 'ኢሪን እንደሚ ለ ው ዲፕሎማቱ ኢትዮጵያ የ ሶማሌ ሀይሎች ን የ ም ታሰለጥን በት ወይም ጣልቃ የምትገባ በት ምክንያት የ ለ ም በ ማለት ተናግረ ዋል',\n", - " 'tr_218_tr03018': 'የ ናይጄሪያ ው ፕሬዚዳንት ኦሉሴጉን አባ ሳንጆ እንደ ዚህ ሲሉ ለ ሮይተር ዜና ወኪል ተናግረ ዋል',\n", - " 'tr_219_tr03019': 'ገበሬዎች ን እያ ሰፈሩ ነው',\n", - " 'tr_220_tr03020': 'ለ ተከራካሪ ዎቹ መንግስታት ግን ይጠቅማ ቸዋል',\n", - " 'tr_221_tr03021': 'ኤርትራውያን በ ኢትዮጵያ ትልቅ ስፍራ ከፍተኛ ስልጣን ተሰጥቷ ቸዋል',\n", - " 'tr_222_tr03022': 'ሶማሊያውያን በ ዋሽንግተን ኢትዮጵያ ን በ መቃወም ሰልፍ ወጡ',\n", - " 'tr_223_tr03023': 'ክሱ ን እንዳላ ንቀሳቅስ ም የ ባህል ተጽእኖ ተደረገ ብኝ ት ላለች',\n", - " 'tr_224_tr03024': 'ይህንን የኤርትራ መንግስት እርምጃ በ ተባበሩት መንግስታት የ ኢትዮጵያ ና የኤርትራ ተልእኮ አንሚ እንዲሁም አደራዳሪ አካላት ሊ ያወግዙ ት ይገባል ሲሉ ጥሪ አቅርበ ዋል',\n", - " 'tr_225_tr03025': 'ሚድሮክ በተ ባለ ኩባንያ ሰፋ ያሉ የ ኢንዱስትሪ ግምባታ ዎችን እያደረጉ ናቸው',\n", - " 'tr_226_tr03026': 'ነገር ግን የ ዋስ መብት ተፈቅዶ ላቸዋል',\n", - " 'tr_227_tr03027': 'ከ ሚኒስትሮቹ ቀደም ብለው ከ የሀገሮቹ የሚውጣ ጡ የ ውሀ ሀብት ኤክስፐርቶች ና ባለሙያዎች የሚካፈሉ በት አውደ ጥናት ሶደሬ ውስጥ የሚካሄድ መሆኑ ም ተ ገልጿ ል',\n", - " 'tr_228_tr03028': 'አየር መንገዱ አዳዲስ አውሮፕላኖች ን የ መግዛት እቅዱ በ ኢትዮ ኤርትራ ጦርነት የ ተጨናገፈ ቢሆን ም በሚ ቀጥሉ ት ስድስት ወራት ውሳኔ እንደሚ ያገኝ ለማወቅ ተችሏል',\n", - " 'tr_229_tr03029': 'ሊያስ ቅ የሚ ቃጣው መልስ ሰጡ',\n", - " 'tr_230_tr03030': 'ከ ሊቨርፑል ህጻናት ማእከል ውስጥ የ ገባሁት ገና የ አስር አመት ልጅ እያለሁ ነው',\n", - " 'tr_231_tr03031': 'አንዳንዱ በ ቁመና ው አንዳንዱ በ ኳስ ችሎታው አንዳንዱ ጐል አግብቶ በሚ ያሳየው እንቅስቃሴ የ ተመልካች ን ልቦና ሰር ቋል',\n", - " 'tr_232_tr03032': 'ደሞዝ አነስተኛ ነው ኢንሴ ን ቲቩ ም እንዲ ሁ እና ም አን ፈርም ም እያሉ ነው',\n", - " 'tr_233_tr03033': 'ፊዮረንቲና ዎች ሮቢን እን ወድ ሀለን እያሉ በ እንባ ነበር የ ሸኙት',\n", - " 'tr_234_tr03034': 'የ ኦዌን ነገር የሚያ ሳስብ ነው እያሉ ነው',\n", - " 'tr_235_tr03035': 'የ ኦሮሚያ ው ሙገር ከ አዲስ አበባ ክለቦች በተ ቀነሱ ተጫዋቾች ተጠናክሮ ውጤት ማስ መዝገቡ ለ ክልሉ እግር ኳስ እድገት አመጣ ማለት አይደለም',\n", - " 'tr_236_tr03036': 'ማክሰኞ ምሽት በ ተደረጉት ግጥሚያ ዎች ባንኮች ብርሀን ና ሰላም ን ሁለት ለ አንድ ሲ ያሸንፍ ታክሲ ና ኒያላ ሳይ ሸ ና ገፉ ሶስት ለ ሶስት ተለያይ ተዋል',\n", - " 'tr_237_tr03037': 'ረዳት ና ዋናው ዳኛ በ ፈጸሙት ስህተት በ ስታዲየሙ ተገኝቶ የነበረ ተመልካች ተቃው ሟል',\n", - " 'tr_238_tr03038': 'እቅዱ ን ለ ጊዜው ተግባራዊ ለማድረግ እንዳል ተቻለ ለ መረዳት ች ለናል',\n", - " 'tr_239_tr03039': 'አቶ ስ ለምነው የመጀመሪያ ዲግሪ ያቸውን ያገኙ ት በ ሰውነት ማጐልመሻ ትምህርት ፊዚካል ኤዲ ኩዌሽ ን ሲሆን ማስተር ሳቸውን ደግሞ በ ፊዚዮቴራፒ ነው',\n", - " 'tr_240_tr03040': 'በ ትክክለኛ እድሜ ላይ የሚገኙት ን ወጣቶች ና ታዳጊዎች ን አቅርበ ን ውጤት ካመጣ ን በ ወርቅ ጽሁፍ ስማችን ን በ ታሪክ ማህደር ላይ ጻፍ ን ማለት ነው',\n", - " 'tr_241_tr03041': 'በ እርግጥ በ ውጪ ሁለቱ ክለቦች ተወዳጅ በ መሆናቸው ና በ መውረዳ ቸው ነው ክትትል እንዳይደረግ ባቸው ያደረገው',\n", - " 'tr_242_tr03042': 'ጐሉ ን ያገባ ው ሙሉ አለም ነው',\n", - " 'tr_243_tr03043': 'ኢትዮጵያ የሺ ላሎ እና ሸሸቢት መሬቶች ን መጠየቅ አለ ባት',\n", - " 'tr_244_tr03044': 'ፕሮጀክቶቹ ተግባራዊ ይሆናሉ ተብለው የሚ ጠበቁት በ ክልላዊ ደርጃ ነው',\n", - " 'tr_245_tr03045': 'ፈ ቲያ ሰኢድ ወይዘሪት አዲስ አበባ ተባለች',\n", - " 'tr_246_tr03046': 'ሰሞኑ ን ወደ ሱማሊያ ፑንትላንድ ከተማ ስለ ገባው የ ኢትዮጵያ ሰራዊት ሬዲዮው ሲ ዘረዝር የ ኢትዮጵያ ወታደሮች ወደ ፑንትላንድ ሲ ገቡ ይህ የመጀመሪያ አይደለም',\n", - " 'tr_247_tr03047': 'ተክለ ማርያም የተባለ ሌላ ተማሪ ም በ መሳሪያ አስገዳጅ ነት እንዳይ ንቀሳቀስ ከ ተደረገ በኋላ እንዳይ ሞት እንዳይ ድን ተደርጐ ተቀጥቅ ቷል',\n", - " 'tr_248_tr03048': 'የ ገብሩ አስራት ጠባቂዎች ታሰሩ',\n", - " 'tr_249_tr03049': 'ባለፉት ሶስት ሳምንታት በ ባህር የመን የ ገቡ የ ኢትዮጵያ ና የ ሶማሊያ ስደተኞች ቁጥር ስድስት መቶ እንደ ደረሰ የ ተባበሩት መንግስታት የ ስደተኞች ጉዳይ ድርጅት ገለጠ',\n", - " 'tr_250_tr03050': 'እንደ አሜሪካ እምነት ና መላ ም ት ኦሮሚያ ነጻነት ዋን ካወጀ ት ኢትዮጵያ ትገነጣጠ ላለች',\n", - " 'tr_251_tr03051': 'ለ ፕሬዚዳንቱ አዲስ መኖሪያ ቤት ና ጽፈት ቤት ሊ ገነባ ነው',\n", - " 'tr_252_tr03052': 'በ አንድ በኩል ከ ኢትዮጵያ ለ መገንጠል አጀንዳ ያ ላቸው ሀይሎች ኢህአዴግ ን አምርረው እንዲ ታገሉ ተጨማሪ ጽናት ያገኛ ሉ',\n", - " 'tr_253_tr03053': 'ከ ኢትዮጵያ የተሰደደ ው ና በ ብዙ ቁጥር ም የሚ ሰደደው አገሩ ን ሊ ገነባ የሚ ችለው ሀይል ነው',\n", - " 'tr_254_tr03054': 'አንዴ አንተ አንዴ አን ቱ እያ ልሁ ተቸገርኩ',\n", - " 'tr_255_tr03055': 'እሱ እንደ ነገረኝ ህግ ትምህርት ቤት በ አንድ ወቅት አብረን ተማሪዎች ነበር ን',\n", - " 'tr_256_tr03056': 'የምናውቀው የ እኛ ዎቹ ገዥዎች ግፊት ተጨምሮ በት ሪፍረንደ ም ተካሂ ዷል ተብሎ ኤርትራ ነጻ መንግስት መሆኗ ን ነው',\n", - " 'tr_257_tr03057': 'የኤርትራ መንግስት የውጭ ምንዛሬ ምንጭ በውጭ የሚገኙ ግማሽ ሚሊዮን ኤርትራውያን ወደ አገራቸው የሚያስ ገቡት የውጭ ምንዛሪ ነው',\n", - " 'tr_258_tr03058': 'ከ አትላንታ ብዙ ሰዎች ተገኝ ተዋል',\n", - " 'tr_259_tr03059': 'ሁለተኛ የ ጂኦግራፊ ና የ ታሪክ ተማሪዎች ም ከ አንድ አመት ተኩል በኋላ በ ዲግሪ እንደ ተፈጥሮ ሳይንስ ተማሪዎች ጓደኞቻቸው ለ መመረቅ እየ ተዘጋጁ ናቸው',\n", - " 'tr_260_tr03060': 'እኔ በ ሙያዬ ግጥም ገጣሚ ና ደራሲ ኢትዮጵያዊ ነኝ',\n", - " 'tr_261_tr03061': 'መንግስት በ ኢንቨስትመንት እንቅስቃሴ ላይ የ ተከሰቱ የ ፖሊሲ ና የ አሰራር ግድፈቶች ን ለ ማስወገድ ርምጃ መውሰዱ ከ ግሉ ኢንቨስትመንት ፍሰት የ ሚገኘው ን ድርሻ እንደሚያ ሻሽለው ም ገለጹ',\n", - " 'tr_262_tr03062': 'እኔ ግን ነፍጠኛ ም መድፈኛ ም እንዳል ሆኩ ልነ ልንገራችሁ ብዬ እንጂ ፖለቲከኛ ሳል ሆን አሽሙረኛ ነኝ ብዬ እናንተ ን ላሳምናችሁ አል ሞክር ም',\n", - " 'tr_263_tr03063': 'ኮሎኔል በዛብህ ጴጥሮስ የ አማራጭ ሀይሎች ሊቀመንበር የ ዶክተር በየነ ጴጥሮስ ወንድም መሆናቸው ተያይዞ ተ ገልጿ ል',\n", - " 'tr_264_tr03064': 'የ መስተዳድሩ መግለጫ ከተማዋ ስር ነቀል ለውጥ እንደሚ ያስፈልጋት ገልጾ ህዝቡ በዚህ እንዲ ሳተፍ ቢ ጠይቅ ም ጊዜያዊ መስተዳድሩ የ መዋቅር ለውጡ ን ያስፈጽማል ተብሎ አይጠበቅ ም',\n", - " 'tr_265_tr03065': 'ለወደፊቱ በሚ ዘጋጀው ጉባኤ የ በ ኩሌን ሀሳብ ለ ለ ካድሬው ይዤ አቀርባ ለሁ',\n", - " 'tr_266_tr03066': 'ኤኤፍፒ ከ ሶስት ሺ በላይ የኤርትራ ኩናማ ዎች ወደ ኢትዮጵያ ሸሽተው በ መግባት የኤርትራ ሰራዊት በ ሀይል እየ መለመላቸው ነው ሲሉ ውንጀላ ሰንዝ ረዋል',\n", - " 'tr_267_tr03067': 'ዋናው አላማችን አባላ ቶቻችን በ ስፖርቱ ተሳታፊ እንዲሆኑ ና ለ ሀገራችን ስፖርት የ በኩላቸው ን አስተዋጽኦ እንዲ ያበረክቱ እንጂ እንደ አንዳንድ ክለቦች ድርጅት ን ለ ማስተዋወቅ አይደለም',\n", - " 'tr_268_tr03068': 'በ ማጠቃለያ ውም በ እርዳታ አ ሰባሰቡ ወቅት ኢህአዲግ በ በጐ አይ ን የማ ይመለከታቸው ና በ አሸባሪነት ጠርጥሬ ያ ቸዋለሁ የሚ ላቸው ኢትዮጵያውያ ን የ ህግ ታራሚዎች ሳይ ቀሩ በ እርዳታ ተሳትፎ ማድረጋቸው ን አመልክ ቷል',\n", - " 'tr_269_tr03069': 'ከ ኢትዮጵያ ውጪ ም በ ጂዳ ና በ ሌሎች አገራት የሚገኙ ኢትዮጵያውያ ን ደስታቸው ን በ መግለጽ ላይ መሆናቸው ን ለማወቅ ተችሏል',\n", - " 'tr_270_tr03070': 'ጀርመን ኢትዮጵያውያ ን ስደተኞች ን ለ መመለስ ከ ስዬ አብርሀ ጋር መከረ ች',\n", - " 'tr_271_tr03071': 'አገሩ እንዳይገባ ም ወንዝ ይሞላ ል',\n", - " 'tr_272_tr03072': 'ባለፈው ሳምንት የ ኬንያው ዜና አገልግሎት ቁጥራቸው አንድ ሺ የሚሆኑ የ ኦነግ ሽምቅ ተዋጊዎች ኬንያ ውስጥ መግባታቸው ን ማሳወቁ የሚ ታወስ ነው',\n", - " 'tr_273_tr03073': 'ስለ ሲኖ ሲኖዶሱ አባላት ና ተቋቁ ሟል ስለ ተባለው ኮሚሽን ጉዳይ ሲናገሩ ም በ ጳጳሳት ና ኮሚሽን በ ተባለው እምነት የ ጣለበት ሰው ካለ በ እጅጉ ተሳስ ቷል',\n", - " 'tr_274_tr03074': 'በ ኢትዮጵያ ና ኤርትራ እስከዛሬ ሲ ሰሩ የቆዩት ን ወታደራዊ አታሼ ዎቿን አሜሪካ ልት ቀይር መዘጋጀቷ ን ታማኝ ዲፕሎማቲክ ምንጮች ገለጹ',\n", - " 'tr_275_tr03075': 'እነዚህ ተቋማት ወሳኝ ማእከላዊ ተቋማት ናቸው',\n", - " 'tr_276_tr03076': 'እስረኞች ከ አዲስ አባ ወደ አልታወቀ ስፍራ እየ ተወሰዱ ናቸው የ ዩኒቨርስቲ ተማሪዎች የ ይቅርታ ቅጽ እንዲ ሞሉ ተጠየቁ',\n", - " 'tr_277_tr03077': 'በ ሰማኒያ ጋዜጠኞች ላይ ክስ ተ መስርቷል እየተ ባለ በ ኢትዮጵያ የ ፕሬስ ነጻነት ተሻሽ ሏል ማለት አይቻል ም',\n", - " 'tr_278_tr03078': 'ይሄ ውሳኔ ውዝግቡ እንዳይ ፈታ ያደረገው አስተዋጽኦ ነው',\n", - " 'tr_279_tr03079': 'የኦሮሞ ተማሪዎች ከ አቶ ጁኔይዲ ጋር ተፋ ጠው ዋሉ',\n", - " 'tr_280_tr03080': 'ጄኔራሉ እስኪ ፈቱ ድረስ ተማጽኖ ና ተቃውሟቸው እንደሚ ቀጥል ም አስታውቀ ዋል',\n", - " 'tr_281_tr03081': 'ሌንጮ ከ ኢህአዴግ ሊ ደራደሩ ይሆን',\n", - " 'tr_282_tr03082': 'ኢስላም በ ልማት መስክ ከ ኢትዮጵያ መስሊሞች ብዙ ይጠበቃል ተ ባለ',\n", - " 'tr_283_tr03083': 'ተጫዋቾቹ ገንዘባቸው ን ከመክ ሰራቸው በ ተጨማሪ ከ ፌዴሬሽኑ ተጨማሪ ቅጣት ሊ ጣል ባቸው በ ዝግጅት ላይ እንደሆነ ለማወቅ ች ለናል',\n", - " 'tr_284_tr03084': 'ዶክተሩ ለ ቡድን መሪው ያስታወቁ ት ለ ብራዚል ፉትቦል ፌዴሬሽን ፕሬዚዳንት ሪ ካርዶ ቴክሴራ ጉዳዩ ን እንዲገልጹ ላቸው ነበር',\n", - " 'tr_285_tr03085': 'በ ጥቃቅን ስህተት ነው ለ ሽንፈት የሚ ጋለጠው',\n", - " 'tr_286_tr03086': 'እና ደስታዬ ን በ መትረየስ ተኩስ አሳ የ ሁት',\n", - " 'tr_287_tr03087': 'በ ቶሮንቶ ቆይታቸው ም ሻምበል ምሩጽ ይፍጠር ን እንዳገኙ ት አጫው ተውናል',\n", - " 'tr_288_tr03088': 'ግን ውስጡ ስገባ ውጪው ና ውስጡ ሊ ጣጣም ልኝ አልቻለ ም',\n", - " 'tr_289_tr03089': 'እነ አባተ ኪሾ ትናንት ፍርድ ቤት ቀረቡ',\n", - " 'tr_290_tr03090': 'ኢትዮጵያ ከ ሰላም አስከባሪ ው ሀይል እንዲ ነሱ ጥያቄ ያቀረበች ባቸው አዛዥ ሜጀር ጄኔራል ፓትሪክ ካማራት አሁን ም ድረስ በ ስራቸው ላይ እንደሚገኙ ተገለጸ',\n", - " 'tr_291_tr03091': 'የ ኢትዮጵያ ና የኤርትራ ብሄራዊ ቡድን ተጫዋቾች ተደባደቡ',\n", - " 'tr_292_tr03092': 'ቢ ያንስ እርስ በ ርሳቸው እንዳይ ተማመኑ አድርጓ ቸዋል',\n", - " 'tr_293_tr03093': 'እብሪት ና ማን አህሎ ብኝ ነት የ በታች ነት ስሜት ነጸብራቅ ናቸው',\n", - " 'tr_294_tr03094': 'የሚ ጠይቃቸው ካገኙ ም ችግራቸው ን ይናገራሉ',\n", - " 'tr_295_tr03095': 'ዞር በ ል ብ ያለሁ ይላል በ ችሎቱ ዙሪያ ያለውን ሰው',\n", - " 'tr_296_tr03096': 'አንዱ ምጽዋ ላይ በ ተደረገው ጦርነት ሞ ቷል',\n", - " 'tr_297_tr03097': 'አፍሪካውያን የ ደህንነት ዋስትና እንዲ ያገኙ ና በ ኢኮኖሚ በ ተሻለ ደረጃ ላይ እንዲ ደርሱ የ አፍሪካ ችግሮች በ ቅንነት ና ገንቢ በሆነ እርምጃ ሊፈቱ ይገባል ብለዋል',\n", - " 'tr_298_tr03098': 'አማራ ን ነጻ ለ ማውጣት ኦሮሞ ን ለ ማንገስ ነው እያ ለ ቀላል ጦርነት የሚ ያካሂድ መስሎ ት የ ኢትዮጵያ ን ድንበር ሊ ደፍር ችሏል',\n", - " 'tr_299_tr03099': 'የ ስፔን ኢንተርናሽናል ተከላካይ የ ሆነው ኢቫ ን ካምፖ የሆላንዱ ኢንተርናሽናል ክላሪየክላረን ሲ ሲ ዶር ፍ ና የ ጣልያኑ ኢንተርናሽናል ክሪስቲያን ፓኑቺ በ ሰጡት አስተያየት አሰልጣኙ ተማረ ዋል',\n", - " 'tr_300_tr03100': 'በ ኢትዮጵያ እንዳ የ ነው ኤርትራውያኑ ና አስተባባሪ ዎቻቸው እዚያ ም ህግ ና ስነ ስርአት ጥሰው የ አካባቢው ን ህዝብ ሰላም አደፍ ርሰው ስለ ተገኙ በ ፖሊሶች ና በ ሄሊኮፕተሮች እስከ መበተን ደርሰዋል',\n", - " 'tr_301_tr04001': 'ትምህርቴ ን እንደ ጨረስኩ ወገኖቼ ን ለ መርዳት ወደ ሀገሬ ተመለስኩ',\n", - " 'tr_302_tr04002': 'ሁለቱ ን አገሮች የሚያ ገናኘው መንገድ ግንባታ የ ንግድ ና ኢንቨስተ መንት እንቅስቃሴ ዎችን ለ ማካሄድ ምቹ ሁኔታ እንደሚፈጥር አስ ታውቋል',\n", - " 'tr_303_tr04003': 'የ ሀገር መከላከያ ሚኒስቴር ባዘጋጀ ው የ ዚሁ የ ሽልማት ስነ ስርአት የ ሀገሪቱ ከፍተኛ ባለስልጣናት የ ሀይማኖት መሪዎች አምባሳደሮች ና ዲፕሎማቶች እንዲሁም የ ተሸላሚ ዎች ቤተሰቦች ተገኝ ተዋል',\n", - " 'tr_304_tr04004': 'ኢታ ማዦር ሹም ና ጠቅላይ ሚኒስትር መለስ ተወዛግ በ ው ነበር',\n", - " 'tr_305_tr04005': 'በ ወቅቱ ኤርትራ የ ማክሮ ኢኮኖሚ ን ኢትዮጵያ ደግሞ የ ማይክሮ ኢኮኖሚ ፖሊሲ ይከተሉ ነበር',\n", - " 'tr_306_tr04006': 'የ እነ ዶክተር ካሱ ኢላላ ውንጀላ ደግሞ ከ ኦቦ ሀሰን አሊ ይልቅ በ ጠቅለይ ሚንስቴሩ በኩል ተሰሚነት አግኝቶ እንደ ነበረ ብዙዎቹ የሚ ያስታውሱ ት ነበር',\n", - " 'tr_307_tr04007': 'ከ አጣሪ ኮሚሽኑ ውጤት በኋላ ተቋ ው ሞ ተጠናክሮ እንደሚ ቀጥል ተገለጸ',\n", - " 'tr_308_tr04008': 'ኢትዮጵያ ድን በ ሯን ለ ማስከበር ሁለት አማራጮች እንዳ ሏት ተገለጠ',\n", - " 'tr_309_tr04009': 'ትብትብ ቋጠሮ ገመና ሚስጢ ሩን በሚያስ ደንቅ ግርማ ተንታኝ ጉዳ ጉድ ን',\n", - " 'tr_310_tr04010': 'ጥሩ ገበያ ሊ ገኝ የሚ ችለው የ ት አገር ነው የሚለው ነው',\n", - " 'tr_311_tr04011': 'ኤርትራዊው ካፒቴ ን ሲ ሰልል ተያዘ',\n", - " 'tr_312_tr04012': 'አዲስ መዋቅር እና ቅርብ ማለት ማበጣበጥ ነው',\n", - " 'tr_313_tr04013': 'አንዳንድ የ ሶማሊያ አንጃዎች ኦነግ ንና የ ኦጋዴን ብሄራዊ ነጻ አውጭ ግንባር ወደ ሶማሊያ አምጥተ ዋል',\n", - " 'tr_314_tr04014': 'በ ደቡብ ህዝቦች ክልል ሶስት መቶ አስራ ሶስት ሺ አማራ ዎች ሁለት መቶ ስድስት ሺ ኦሮሞዎች አሉ',\n", - " 'tr_315_tr04015': 'በዚህ መሰረት ዛሬ ኬንያ ከ ሩዋንዳ ኢትዮጵያ ከ ኡጋንዳ ለ ግማሽ ፍጻሜ ይጋጠማሉ',\n", - " 'tr_316_tr04016': 'ለ ትሪፖሊ ው ስብሰባ መክሸፍ ኢትዮጵያ ኤርትራ ን ስት ከ ስ ኤርትራ ም ኢትዮጵያ ን በ እንቅፋት ነት አቅርባ ለች',\n", - " 'tr_317_tr04017': 'በ ቤይሩት የ ኢትዮጵያዊ ቷ አስክሬን የ ደረሰበት ጠፋ',\n", - " 'tr_318_tr04018': 'የ ህብረቱ ን መመስረት አስመልክቶ በ ደርባን ከተማ ርችት ተተኩ ሷል ሄሊኮፍተሮች ም ትእይንት አሳይ ተዋል ሙዚቀኞች ና ዳን ሰኞች ጣእመ ዜማ ቸውን አ ሰምተዋል',\n", - " 'tr_319_tr04019': 'ስለ ባድመ ና ሽራሮ ም ስክርነታቸውን ሰጡ',\n", - " 'tr_320_tr04020': 'ኢዴ ፕ የ ተቃዋሚዎች ን ህብረት ተቀላቀለ',\n", - " 'tr_321_tr04021': 'ኢትዮጵያ የምት ፈልገው ን ድል ለ ማጠናቀቅ ተቃር ባለች',\n", - " 'tr_322_tr04022': 'ኢትዮጵያ ከ ጐረቤቶቿ ጋር ያላ ት ግንኙነት ኮረኮንች የ በዛበት መንገድ ነው',\n", - " 'tr_323_tr04023': 'የ አይኖቹ ንና የ አ ፍንጮች ቀዳዳ ዎች ትንንሾች መሆናቸው ም ተመልክ ቷል',\n", - " 'tr_324_tr04024': 'አምስት የ ውጪ ሀገር የ በረራ አስተማሪ ዎች ደብረ ዘይት ገቡ',\n", - " 'tr_325_tr04025': 'የ ኦሮቶዶክስ ና ካ ቶ ሊ ኩ ሱባኤ ተቃውሞ አረፈ በት',\n", - " 'tr_326_tr04026': 'ጃክሮስ ኢትዮጵያ አስራ ሰባት ሚሊየን ብር እንዲ ከፍል ተወሰነ በት',\n", - " 'tr_327_tr04027': 'በ ኢትዮጵያ የ አሜሪካ ኤምባሲ ከ አል ኢቲ ሀድ አል እስላሚያ ማስጠንቀቂያ እንደ ደረሰው ትናንት ተገለጸ',\n", - " 'tr_328_tr04028': 'አቶ ደበላ ይማ ሙ ና ወይዘሮ መሬ ማ ዋቁማ ስድስት አመት በ ትዳር ቆይ ተዋል',\n", - " 'tr_329_tr04029': 'አዳዲስ የ ነዳጅ ቦቴዎች ወደ ሀገር ውስጥ መግባት ጀመሩ',\n", - " 'tr_330_tr04030': 'እነርሱ ም የ ኤቨርተን ክለብ ወዳጆች ነበሩ',\n", - " 'tr_331_tr04031': 'ከ አንድ ሜትር ከ ሰማኒያ አምስት ቁመት ና ሰባ ዘጠኝ ኪሎ ክብደት ጋር የ ጸጉሩ አሰራር ተደም ሮ የ ስንቶቹ ን እህቶቻችን ን ትኩረት ስቧል',\n", - " 'tr_332_tr04032': 'ባለፉት ሶስት አመታት የ ደሞዝ ክፍያው ን ጣሪያ በ እጥፍ አሳድገ ናል',\n", - " 'tr_333_tr04033': 'ሚላን በ ሰማኒያ ሚሊዮን ብር ንብረቱ አደረገ ው',\n", - " 'tr_334_tr04034': 'ሰዎች ማወቅ ያለ ባቸው ሁልጊዜ ም እንደ አርጀንቲና ው ጐል አይነት ማግባት እንደማል ችል ነው',\n", - " 'tr_335_tr04035': 'በ እርግጥ በ አዲስ አበባ በሚገኙ ክለቦች መስዋእትነት የ ኢትዮጵያ እግር ኳስ ማደግ ከ ቻለ በጣም ደስተኞች ነን',\n", - " 'tr_336_tr04036': 'ኒያላ ከተ ቆጠሩ በት ጐ ሎች ሶስተኛው በ በረኛው በ ጸጋዬ ዜና ስህተት የተገኘ ች ና ት',\n", - " 'tr_337_tr04037': 'እያንዳንዱ ተመልካች ይህ ስለ ተደረገ ለት ጠጥቶ ተደስቶ ነበር ከ ሜዳ የ ወጣው',\n", - " 'tr_338_tr04038': 'ከ ኢትዮጵያ ኦሎምፒክ ጽፈት ቤት ባገኘ ነው መረጃ አቶ ፍቅሩ ኪዳኔ ታህሳስ አስራ አምስት ቀን አዲስ አበባ እንደሚ ገቡ በ ላኩት መልእክት ለማወቅ ች ለናል',\n", - " 'tr_339_tr04039': 'ሙያው ን ለ ሙያተኞች መተው አለ ባችው ብለዋል',\n", - " 'tr_340_tr04040': 'ሌሎች ክለቦች ግን ገንዘብ የ ሌላቸው ላብ መተኪያ ን እንኳ ን ማቅረብ የማይችሉ ናቸው',\n", - " 'tr_341_tr04041': 'በ ሀገር ውስጥ ግን ፉክክር እንደ ሞቀ ነው',\n", - " 'tr_342_tr04042': 'ኳስ ጨዋታ ኳስ ነው',\n", - " 'tr_343_tr04043': 'ጦርነቱ ን ለ መቋጨት ኢትዮጵያ ለ አፍሪካውያን ውሳኔ ትገዛ ለች',\n", - " 'tr_344_tr04044': 'ኤርትራውያን ሸቀጣ ቸውን ይዘው ወደ ኢትዮጵያ ይ ግቡ የ ኢትዮጵያ ንም ሸቀጥ ገዝተው ይውጡ',\n", - " 'tr_345_tr04045': 'ወይዘሪት አዲስ አበባ ፈ ቲያ ሰኢድ የ ሁለተኛ ደረጃ ተማሪ ስት ሆን የ አውሮፕላን አስተናጋጅ ሆስተን ስ የ መሆን እቅድ እንዳላ ት ገልጻ ለች',\n", - " 'tr_346_tr04046': 'የ ኢትዮጵያ ዲሞክራ ሳዊ ፓርቲ ኢዴፓ በ ነገው እ ለት በ መስቀል አደባባይ የሚያ ከናውነው ን የ ተቃውሞ ስብሰባ ዝግጅት ሙሉ በ ሙሉ ማጠናቀቁ ን አስ ታውቋል',\n", - " 'tr_347_tr04047': 'ወዴት እንደሚ ሄዱ ለማ ን እንደሚ ናገሩ ግራ የ ገባቸው ይመስ ላሉ',\n", - " 'tr_348_tr04048': 'አሁን ግን የ ኢትዮጵያ የድሮ ጠላት የ ሆነችው ና ራሷ በ ድርቅ የተመታች ው ኤርትራ ወደቦቹ ን ለ ኢትዮጵያ የሚ ላኩ እህሎች በ ነጻ እንዲ ገቡበት ፈቅዳ ለች',\n", - " 'tr_349_tr04049': 'የ አውሮፓ ህብረት ለ ኢትዮጵያ የሚያደርገው ን እርዳታ ያ ጢን',\n", - " 'tr_350_tr04050': 'እንደ ኦሮሞ ዎቹ እምነት ም አምላክ በ ሚሊዮኖች የሚ ቆጠር ውስብስብ ፍጡራን ን የ ፈጠረው በ ሀያ ሰባት ቀናት ነው',\n", - " 'tr_351_tr04051': 'እንደ ቤተ መንግስት አስተዳዳሪ ከ ሆኑ ጥናቱ እንደ ተጠናቀቀ የ እድሳት ግንባታው ወዲያ ው ይጀ መራል',\n", - " 'tr_352_tr04052': 'ነዳጅ ም በውጭ ምንዛሪ እንዲ ገዛ ተገደደ',\n", - " 'tr_353_tr04053': 'ወይም በ ቅርቡ እንደ ታዘብነው በ ጦሩ ሜዳ ገብ ተዋል የሚ ባሉት እንኳ ን ከ ታሪክ ሽሚያ ውስጥ ይገባ ሉ',\n", - " 'tr_354_tr04054': 'እዚህ አካባቢ ያለው ወገናችን ብዙ እውነት ይናገራል',\n", - " 'tr_355_tr04055': 'ጥናቱ ን የማ ደንቅ በት አንዱ ምክንያት ይኸው ነው',\n", - " 'tr_356_tr04056': 'ለ ዛሬ ማለት የሚ ቻለው ጥያቄ ውም እየገፋ ያለው ግንኙነቱ ስርአት ይያዝ የሚ ል ነው',\n", - " 'tr_357_tr04057': 'መድረኩ ን ያዘጋጀው ድርጅት ግን ሀሳቡ ን እንዳል ተቀበለው እንዲያ ን ኦ ሽን ነው ስ ሌተር በ ቅርብ ገልጿ ል',\n", - " 'tr_358_tr04058': 'ከ ሎስ አንጀ ልስ ከ ለንደን ከ ካናዳ ወዘተ የ መጡት አያሌ ናቸው',\n", - " 'tr_359_tr04059': 'ተመራቂ ዎች ተማሪዎች ወደፊት በ ከፍተኛ ትምህርት የ መሳተፍ እድ ላቸው አሁን ካ ላቸው እውቀት አንጻር ሲታይ ወደፊት አስቸጋሪ እንደሚሆን ባቸው የማን ጠራ ጠረው እውነት ነው',\n", - " 'tr_360_tr04060': 'እርስዎ ያሉት ን በ ትክክል ለ መጥቀስ ትግሬ ዎች አክሱም አ ላቸው',\n", - " 'tr_361_tr04061': 'መንግስት በ ኢንቨስትመንት እንቅስቃሴ ላይ የ ተከሰቱት የ ፖሊስ ና የ አሰራር ግድፈቶች ን ለ ማስወገድ እርምጃ መውሰድ ከ ግሉ እንቨስትመንት ፍ ስት በ ሚገኘው ን ድርሻ እንደሚያ ስ ሻሽል ገለጹ',\n", - " 'tr_362_tr04062': 'እኔ ግን ና ፍጠ ኛ ም መድፈኛ ም እንዳል ሆ ኩኝ ልንገራችሁ ብዬ እንጂ ፖለቲከኛ ሳል ሆን አሽሙረኛ ነኝ ብዬ እናንተ ን ላ ሰማችሁ አል ሞክር ም',\n", - " 'tr_363_tr04063': 'ኮሎኔል በዛብህ ጴጥሮስ የ አማራጭ ሀይሎች ሊቀመንበር የ ዶክተር በየነ ጴጥሮስ ወንድም መሆናቸው ተያይዞ ተ ገልጿ ል',\n", - " 'tr_364_tr04064': 'የ መስተዳድሩ መግለጫ ከተማው ስር ነቀል ለውጥ እንደሚ ያስፈልጋት ገልጾ ህዝቡ በዚህ እንዲ ሳተፍ ቢ ጠይቅ ም ጊዜያዊ መስተዳድሩ የ መዋቅር ለውጡ ን ያስፈጽማል ተብሎ አይጠበቅ ም',\n", - " 'tr_365_tr04065': 'ለወደፊቱ በሚ ዘጋጀው ጉባኤ የ በ ኩሌን ሀሳብ ለ ካድሬው ይዤ አቀርባ ለሁ',\n", - " 'tr_366_tr04066': 'ኤኤፍፒ ከ ሶስት ሺ በላይ የኤርትራ ኩናማ ዎች ወደ ኢትዮጵያ ሸሽተው በ መግባት የኤርትራ ሰራዊት በ ሀይል እየ መለመላቸው ነው ሲሉ ውንጀላ ሰንዝ ረዋል',\n", - " 'tr_367_tr04067': 'ዋናው አላማችን አባላ ቶቻችን በ ስፖርቱ ተሳታፊ እንዲሆኑ ና ለ ሀገራችን ስፖርት የ በኩላቸው ን አስታው ጽኦ እንዲ ያበረክቱ እንጂ እንደ እያንዳንዱ ክለቦች ድርጅቱ ን ለ ማስተዋወቅ አይደለም',\n", - " 'tr_368_tr04068': 'በ ማጠቃለያ ውም በ እርዳታ አ ሰባሰቡ ወቅት ኢህአዲግ በ በጐ አይ ን የማ ይመለከታቸው ን በ አሸባሪነት ጠርጥሬ ያ ቸዋለሁ የሚ ላቸው ኢትዮጵያውያ ን የ ህግ ታራሚዎች ሳይ ቀሩ በ እርዳታው ተሳትፎ ማድረጋቸው ን አመልክ ቷል',\n", - " 'tr_369_tr04069': 'በ ብዙ የ ማህበር ኢኮኖሚያዊ መስኮች አበር ታች ውጤቶች ን ማምጣት ጀም ሯል',\n", - " 'tr_370_tr04070': 'ዳዊት ዮናስ በ ፓር ስ ከሚገኙ ኢትዮጵያውያ ን ጋር ተነጋገሩ',\n", - " 'tr_371_tr04071': 'ያን ጊዜ ሚንሊክ ይህንን አዋጅ አስ ነገሩ',\n", - " 'tr_372_tr04072': 'አሁን ባለፈው ሳምንት ይሄው አርቲስት በ ፓሪስ ጐዳናዎች ላይ ከ ሶስት ኢትዮጵያውያ ን ጋር እየ ተጓዙ ሳ ለ ነው አደጋ የ ደረሰባቸው',\n", - " 'tr_373_tr04073': 'ሆዳቸው ን የሚ ያመልኩ መሆናቸው ን በ ተደጋጋሚ ስለ አ ረጋገጥኩ ነው',\n", - " 'tr_374_tr04074': 'ብዙ ጠመዝማዛ አቀ በት ና ቁልቁለት ያለው ጉዞ ነው',\n", - " 'tr_375_tr04075': 'ጉባኤ ዴሞክራሲያዊ ሊሆን የሚ ችለው ዴሞክራሲያዊ ያን ፍትሀዊ በሆነ መንገድ ሲ ዘጋጁ ብቻ ነው',\n", - " 'tr_376_tr04076': 'ከ ኢደፓ የተገኘው መረጃ እንደሚ ያስረዳ ው እስረኞች የ ት እንደ ተወሰዱ አይ ታወቅ ም',\n", - " 'tr_377_tr04077': 'እነ ተወልደ አዲስ ፓርት ያቋቁማሉ ተ ባለ',\n", - " 'tr_378_tr04078': 'ግን የ ኢትዮጵያ ህልውና ተ ደፍሮ አልቀረ ም',\n", - " 'tr_379_tr04079': 'የኦሮሞ ተማሪዎች ተቋማ ቸውን ከ ማቅረባቸው ባሻገር የኦሮሞ ፕሬዚዳንት የሆኑት ን አቶ ጁነዲ ን ሶዶ ን አነጋግሯ ቸዋል',\n", - " 'tr_380_tr04080': 'ይሁን ና መታሰር ና መጠየቅ ያለ ባቸው ከ ታገዱት ማእከላዊ ኮሚቴ አባላት ጋር ዝምድና ና ቅርበት ያ ላቸው ብቻ መሆን እንደሌለ ባቸውም ታዛቢዎች ያስገነዝ ባሉ',\n", - " 'tr_381_tr04081': 'ኢትዮጵያውያ ን ለ አንድ ቀን አዳር ይ ጨነቃ ሉ',\n", - " 'tr_382_tr04082': 'በ ኢትዮጵያ አስሀባ ዎች አ ሰሯቸው የሚ ባሉ ብዙ መስጊዶች እንደ ነበሩ አንዳንዶች ም አሁን ም እንዳሉ ይታወ ቃሉ',\n", - " 'tr_383_tr04083': 'እኛ አፍሪካውያን በ ኢትዮጵያውያ ን ኮራ ን',\n", - " 'tr_384_tr04084': 'በት ሪቡኑ ስር በ ሚገኘው ቦታ ላይ ም ጓደኞቹ የ ቡድን ተጫዋቾች ሰውነታቸው ን እያ ሟሟ ቁ ነበር',\n", - " 'tr_385_tr04085': 'ሳምንት በ ኦልድ ትራ ፎርድ ሊድስ ን አስተናግ ዶ ሶስት ለ ሁለት አሸን ፏል',\n", - " 'tr_386_tr04086': 'የ ሪያል ማ ዲ ርድ ኮንትራ ቴ የሚያበቃ ው በ ሁለት ሺ ነው',\n", - " 'tr_387_tr04087': 'በ እርግጥ የ ኢትዮጵያ ፉትቦል ፌዴሬሽን ሀላፊዎች ይህንን በ ማድረጋቸው ሊ ደነቁ ይገባል',\n", - " 'tr_388_tr04088': 'በተለይ በ ዋ ና ከተማዋ ለንደን ቢሆን ደስተኛ ነን',\n", - " 'tr_389_tr04089': 'ወደ ሀያ ስድስት ሺህ የሚሆኑ ኢትዮጵያውያ ን አይሁዶች እስካሁን ኢትዮጵያ መቅረታቸው ይገመ ታል',\n", - " 'tr_390_tr04090': 'ክሱ ም ን እንደሆነ ም አያውቁ',\n", - " 'tr_391_tr04091': 'ሁለቱ ም ቡድኖች ከ ሌሎች የ ኡጋንዳ የ ሩዋንዳ የ ሱዳን ቡድኖች ጋር በ ኮሌጅ ኦፍ ኮሚኬሽን ቴክኖሎጂ ውስጥ እንደሚ ኖሩ ይ ታውቋል',\n", - " 'tr_392_tr04092': 'ቁልፍ ችግሮች እነማን ናቸው ተብለው መታየት ነበረ ባቸው',\n", - " 'tr_393_tr04093': 'ተቃዋሚዎች ን ግን በ አድራጐታቸው ሊ ሳለቁ ባቸው ይሞ ክራሉ',\n", - " 'tr_394_tr04094': 'የ አህያ ዘመዶች ማን እንደሆኑ ተናግራ ለች',\n", - " 'tr_395_tr04095': 'የ ት እንሂድ የ ደንበኞቻችን ን ጉዳይ እንዴት እናስ ረዳ ወደ ፍርድ ቤት ሲ ገቡ እንዴት እን ይ ይላሉ ጠበቆች',\n", - " 'tr_396_tr04096': 'ኤርትራ የ ኢትዮጵያ አካል ና ት',\n", - " 'tr_397_tr04097': 'ትግራዮች ወደ ብሄራዊ ትግሉ ይ ግቡ',\n", - " 'tr_398_tr04098': 'አቶ ታምራት በ እለቱ የመንግስት ሚዲያ ዎችን አፈ ንጉሶች በ ማለት ጥሩ ስ ም ሰጥ ቷቸዋል',\n", - " 'tr_399_tr04099': 'ሀገራችን ን የ ገጠማት ግን የዚህ ተቃራኒ ነው',\n", - " 'tr_400_tr04100': 'እ ስኮትላንዶች ስን መራቸው ቆይ ተ ን አቻ የ ም ታደርጋ ቸውን ጐል አግብ ተዋል',\n", - " 'tr_401_tr05001': 'የ ሂሳብ ና የ ቴክኒክ ችሎታ ም ነበረኝ ሊ ያስቸግር የሚ ችለው ሎጅ ክ ና ማቀናጀት ነው',\n", - " 'tr_402_tr05002': 'ኢትዮጵያ ና ሌሎች አስራ ስ ባት የ አፍሪካ አገሮች ም የ ሀሳቡ ን ተፈጻሚ ነት ይከታተ ላሉ',\n", - " 'tr_403_tr05003': 'ከ ቡና ሽያጭ ሀምሳ ስምንት ሚሊዮን ዶላር ተገኘ',\n", - " 'tr_404_tr05004': 'ይልቁኑ ሳሞራ ግንባር የ ቀሩት ለ ማስትሬት ዲግሪ እየ ተማሩት ያለው የ ተልእኮ ትምህርት የ መጨረሻው ፈተና ደርሶ ባቸው ነው',\n", - " 'tr_405_tr05005': 'ሶስት የ ደብሩ ሀላፊዎች ከስራ ተባ ረዋል',\n", - " 'tr_406_tr05006': 'ይህ በ እንዲ ህ እንዳለ መሳሪያ የ ደገኑ ወታደሮች ወደ ትምህርት ቤት ውስጥ በ መግባት ተማሪዎች ደብተራቸው በ ክፍል ውስጥ ተቆልፎ በት በ ግዳጅ እንዲ ወጡ ተደርጓል',\n", - " 'tr_407_tr05007': 'ጃክሮስ ኢትዮጵያ ከ ደንበኞቹ የ ሰበሰበው ን ገንዘብ ለ መመለስ አቅም የ ለውም ተ ባለ',\n", - " 'tr_408_tr05008': 'ፓትሪያርኩ በ በኩላቸው ከ እናንተ መካከል ሀጢያት የ ሌለበት ይውገረኝ በሚል አቋማቸው እንደ ጸኑ እንደሆነ እየተነገረ ነው',\n", - " 'tr_409_tr05009': 'ምትክ አልባ ህትመት ው ዲ ቷ ስጦታ ሁሉን ያዥ ኮሮጆ ው ብ ነሽ ፊያሜታ',\n", - " 'tr_410_tr05010': 'ዴንማርክ በ ኢትዮጵያ ቆን ስል ሲ ኖራት በ ኤርትራ ግን ያላ ት ኤምባሲ ነው',\n", - " 'tr_411_tr05011': 'በ ኢትዮ ኤርትራ ድንበር ኮንትሮባንድ ተስፋፍ ቷል',\n", - " 'tr_412_tr05012': 'ከዚህ ስብስባ ውጭ ያሉት ሰዎች እስከዚያ ው ከ መጡ ጥሩ',\n", - " 'tr_413_tr05013': 'ሁሴን ቦድ ኤርትራ ለ ራሷ ስትራቴጂካዊ ምክንያቶች ስትል የ አማጽያኑ ን ስምሪት በ ሶማሌ እንደምታ ስተ ባብር ም አስረድ ተዋል',\n", - " 'tr_414_tr05014': 'ብ እ ዴን ማለት ኢህአዲግ ነው',\n", - " 'tr_415_tr05015': 'የ ኢትዮጵያ የ ኢኮኖሚ ችግር የ ውስጥ እንጂ የ ግሎባላይዜሽን አይደለም',\n", - " 'tr_416_tr05016': 'ተቃዋሚዎች ና ገዥው ፓርቲ ሲ ከራከሩ ዋሉ',\n", - " 'tr_417_tr05017': 'ፓርላማው የ ኢንቨስትመንት ረቂቅ አዋጅ ን አጣ ጣለው',\n", - " 'tr_418_tr05018': 'ኢትዮጵያዊ ቷን ገድ ሏል የ ተባለው ቻይና ዊ በ ቁጥጥር ስር ነው',\n", - " 'tr_419_tr05019': 'የ ኢሳያስ መንግስት የ ሁሴን አይዲድ ን ተዋጊዎች ን ሊ ያሰለጥን ነው',\n", - " 'tr_420_tr05020': 'አሁን በ መጨረሻ ም የ ኢትዮጵያዊ ና ዲሞክራሲያዊ ፓርቲ በ ህብረቱ እንቅስቃሴ እንደ ገባ ተ ገልጿ ል',\n", - " 'tr_421_tr05021': 'ፍልሚያው የ ሚካሄደው በ ተለያዩ ግንባሮች ነው',\n", - " 'tr_422_tr05022': 'ኢትዮጵያ ወታደሮ ቿን ከ ግዛቴ አላስ ወጣች ም ስትል ኤርትራ ክስ አቀረበች',\n", - " 'tr_423_tr05023': 'ስለ ተገደሉት ሰዎች ግን የ ገለጹት ነገር የ ለ ም',\n", - " 'tr_424_tr05024': 'የኦሮሞ ነጻነት ግንባር አደጋው ን ያደረስ ኩት ባቡሩ ወታደሮች ን ጭኖ ወደ ምስራቃዊ ው የ አገሪቱ ክፍል ሲያ መራ ነው ይላል',\n", - " 'tr_425_tr05025': 'ጾመ ፍልሰታ ን አስመልክቶ የ ኢትዮጵያ ኦርቶዶክስ ተዋህዶ ቤተ ክርስቲያን ና የ ካቶሊክ ቤተ ክርስቲያን በ ጋራ ያደረጉት ሱባኤ በ ኦርቶዶክስ መንፈሳዊ አማኞች ዘንድ የ በረታ ተቃውሞ አርፎ በታል',\n", - " 'tr_426_tr05026': 'የ ነጻ ሚዲያ ዎች አዋጅ በ ምክር ቤት ጸድቆ ተግባራዊ ሊሆን ነው',\n", - " 'tr_427_tr05027': 'ኢምባሲ ው ጨምሮ ም ለ ኢትዮጵያ መንግስት የ ጸጥታ ክፍል ማስታወቁ ን ተያይዞ ገልጿ ል',\n", - " 'tr_428_tr05028': 'አብረው ገበያ ወጥተ ው ለ ጓዳቸው የሚሆን ቁሳቁስ ሊሸ ም ቱ ተስማሙ',\n", - " 'tr_429_tr05029': 'ቆሎ ሸጠው ኑሯቸው ን በሚ ደጉ ሙ ና ጫማ ጠርገው ደብተር ና እርሳስ በሚ ገዙ ለ ፍቶ አዳሪ ዎች መካከል እራሱ ን አ ነገሰ',\n", - " 'tr_430_tr05030': 'እኔ ግን ራሴ ን በሚገባ አውቀ ዋለሁ',\n", - " 'tr_431_tr05031': 'ሀያ ስምንት አመቱ ነው',\n", - " 'tr_432_tr05032': 'ኢንቨስትመንቱ ም እ ኮ አነስተኛ ነው ይላሉ',\n", - " 'tr_433_tr05033': 'ቺሊ ዎች እ ኮ ፔናሊቲ ው ትክክለኛ አይደለም በሚል ተቃውመ ዋል',\n", - " 'tr_434_tr05034': 'በሰባ ሶስተኛው ደቂቃ ላይ ነው ተ ቀይሮ የ ገባው',\n", - " 'tr_435_tr05035': 'የ አዲስ አበባ መስተዳድር ፕሬዚዳንት አቶ አሊ አብዶ የ ስፖርት ምክር ቤቱ ፕሬዚዳንት ናቸው',\n", - " 'tr_436_tr05036': 'ባጠቃላይ የ ውድድሮች ጫና መብዛት ስሜታቸው ን ቀንሶ ባቸዋል',\n", - " 'tr_437_tr05037': 'ከሚ ያስገኙ ት ገቢ ኮሚሽን ያገኛ ሉ',\n", - " 'tr_438_tr05038': 'የ ውድድሩ ታዛቢ ኮሚሽነሮ ችም ምደባ ተጠና ቋል',\n", - " 'tr_439_tr05039': 'ጀግናው ሻለቃ ሀይሌ ገብረስላሴ ከ አዳዲስ ኩባንያ ጋር ያለውን ግንኙነት በ ማጠናከር በ ሀገራችን የ አዳዲስ ኩባንያ ምርቶች የሚመረቱ በትን ሁኔታዎች እ ያመቻቸ ይገኛል',\n", - " 'tr_440_tr05040': 'ሆድ ሲ ያውቅ ዶሮ ማታ ይ ባል የ ለ',\n", - " 'tr_441_tr05041': 'ሊጋው ን በ ቁንጮ ነት የሚ መራው የ ማዮርካ ቡድን ነው',\n", - " 'tr_442_tr05042': 'ይህም ተጋጣሚው ብዙ ጨዋታዎች ን ያደረገ ና ከፍተኛ ልምድ ና ዝና ያለው ተወዳዳሪ ሮጀር ቶማስ የተባለ ተወዳዳሪ ነው',\n", - " 'tr_443_tr05043': 'አምነስቲ በ እስረኞቹ ዙሪያ ስለሚ ያገኙ ት ህክምና ና ስለሚ ገጥማቸው ቶር ቸር የተሰማ ውን ስጋት ገልጿ ል',\n", - " 'tr_444_tr05044': 'ሻእቢያ በ ተቆጣ ጠራት ኢትዮጵያ ውስጥ ትንሽ ስልጣን መያዝ ብቻ ነው ፍላጐታቸው',\n", - " 'tr_445_tr05045': 'ነገር ግን ሌላ አስተዳዳሪ ተሹሞ ቢመጣ ም በ አቡነ ጳውሎስ የ ተሾመ አስተዳዳሪ ን እንደማይቀበሉ የቤተ ክርስቲያ ኗ ተወካዮች ገልጿ ል',\n", - " 'tr_446_tr05046': 'ጅቡቲ ኤርትራውያን ን እ ያባረረ ች ነው',\n", - " 'tr_447_tr05047': 'የ ተማሪዎች ዲን ሁኔታው ን ለ ትምህርት ቤቱ ያሳውቃ ል',\n", - " 'tr_448_tr05048': 'ከ ሁለቱ ወደቦች ወደ ኢትዮጵያ የሚ ገቡት መንገዶች ጥሩ ይዞታ ያ ላቸው ናቸው',\n", - " 'tr_449_tr05049': 'ኢትዮጵያውያ ን በ ኒውዮርክ የ ተቃውሞ ሰልፍ ያደርጋሉ',\n", - " 'tr_450_tr05050': 'ለ ነዚህ ድርጊቶች ም ኦሮሞዎች ለ እያንዳንዳቸው ስ ም ስ ም አ ሏቸው',\n", - " 'tr_451_tr05051': 'ነገር ግን በውጭ የሚገኙ ኤምባሲዎች ባደረጉ ት ጥረት ፍላጐት ያ ላቸው ሶስት የውጭ ድርጅቶች ተገኝ ተዋል',\n", - " 'tr_452_tr05052': 'ሰሙ ደግሞ አገራዊ ገጽታ ው ነው',\n", - " 'tr_453_tr05053': 'ስደተኛ ተብሎ የ ተመዘገበው ና ያል ተመዘገበው ቁጥር በ እኔ ይሁን ባችሁ ከ ሶስት ሚሊዮን አ ያንስ ም',\n", - " 'tr_454_tr05054': 'እኛ ም ስህተቱ ን ስህተት ለማ ለት እንኳ እንፈራ ለ ን',\n", - " 'tr_455_tr05055': 'እኔ እስከ ማውቀው እንዲ ህ ነበር',\n", - " 'tr_456_tr05056': 'የ ቴክኖሎጂ ልቀት አለ የ ሚባለው ም አንዱ ይኸው ነው',\n", - " 'tr_457_tr05057': 'ሌላው የ ሱዳን ን ጉዳይ ለ ኤርትራ አስቸጋሪ እንዲሆን ያደረገው የ ኢትዮጵያ አቋም መለሳለስ ነው',\n", - " 'tr_458_tr05058': 'ይህ ባለፈው እሁድ በ ቨርጂኒያ ፓቶ ማክ ሚልስ በ ሂይልተን ቤተ ክርስቲያን የተ ከናወነው ዋናው ጸሎተ ፍትሀ ት ና ኦፊሴላዊ የ ፕሮፌሰር አስራት አስከሬ ን አሸኛኘት ፕሮግራም ነው',\n", - " 'tr_459_tr05059': 'በተለይ ብሄራዊ እርቅ ና ተቃዋሚዎች ን የ ፕሬስ ጉዳይ ን የሚ መለከቱት ወሳኝ የ አገራችን ጉዳዮች ናቸው',\n", - " 'tr_460_tr05060': 'በ ደቡብ ሶማሊያ እጅግ ከተ ከ በሩት ሁለት ጐሳዎች አንዱ የ ሆነው ባህጊሪ የ ተወለደው ከ ኦሮሞ እናት ነው',\n", - " 'tr_461_tr05061': 'መንግስት በ ኢንቨስትመንት እንቅስቃሴ ላይ የ ተከሰቱ የ ፖሊሲ ና የ አሰራር ግድፈቶች ን ለ ማስወገድ እርምጃ መውሰዱ ከ ግሉ ኢንቨስትመንት ፍሰት የ ሚገኘው ን ድርሻ እንደሚያ ሻሽለው ም ገለጹ',\n", - " 'tr_462_tr05062': 'እኔ ግን ነፍጠኛ ም መድፈኛ ም እንዳል ሆ ኩኝ ልንገራችሁ ብዬ እንጂ ፖለቲከኛ ሳል ሆን አሽሙረኛ ነኝ ብዬ እናንተ ን ላሳምናችሁ አል ሞክር ም',\n", - " 'tr_463_tr05063': 'ኮለኔል በዛብህ ጴጥሮስ የ አማራጭ ሀይሎች ሊቀመንበር የ ዶክተር በየነ ጴጥሮስ ወንድም መሆናቸው ተያይዞ ተ ገልጿ ል',\n", - " 'tr_464_tr05064': 'የ መስተዳድሩ መግለጫ ከተማዋ ስር ነቀል ለውጥ እንደሚ ያስፈልጋት ገልጾ ህዝቡ በዚህ እንዲ ሳተፍ ቢ ጠይቅ ም ጊዜያዊ መስተዳድሩ የ መዋቅር ለውጡ ን ያስፈጽማል ተብሎ አይጠበቅ ም',\n", - " 'tr_465_tr05065': 'ለወደፊቱ በሚ ዘጋጀው ጉባኤ የ በ ኩሌን ሀሳብ ለ ካድሬው ይዤ አቀርባ ለሁ',\n", - " 'tr_466_tr05066': 'ኤኤፍፒ ከ ሶስት ሺ በላይ የኤርትራ ኩናማ ዎች ወደ ኢትዮጵያ ሸሽተው በ መግባት የኤርትራ ሰራዊት በ ሀይል እየ መለመላቸው ነው ሲሉ ውንጀላ ሰንዝ ረዋል',\n", - " 'tr_467_tr05067': 'ዋናው አላማችን አባላ ቶቻችን ን በ ስፖርቱ ተሳታፊ እንዲሆኑ ና ለ ሀገራችን ስፖርት የ በኩላቸው ን አስተዋጽኦ እንዲ ያበረክቱ እንጂ እንደ አንዳንድ ክለቦች ድርጅት ን ለ ማስተዋወቅ አይደለም',\n", - " 'tr_468_tr05068': 'በ ማጠቃለያ ውም በ እርዳታ አ ሰባሰቡ ወቅት ኢህአዲግ በ በጐ አይ ን የማ ይመለከታቸው ና በ አሸባሪነት ጠርጥሬ ያ ቸዋለሁ የሚ ላቸው ኢትዮጵያውያ ን ን የ ህግ ታራሚዎች ሳይ ቀሩ በ እርዳታው ተሳትፎ ማድረጋቸው ን አስመል ክቷል',\n", - " 'tr_469_tr05069': 'በ አዲስ አበባ ስቴዲዮም መብራት ሀይል ባንኮች ን ሁለት ለ ዜሮ ኒያላ ትራንስ ኢትዮጵያ ን አራት ለ ሶስት አሸንፈ ዋል',\n", - " 'tr_470_tr05070': 'የ አውሮፓ ፓር ሊያ ሜንት በ ኢትዮጵያ ዲሞክራሲያዊ ሂደት ላይ ያለውን ጥርጣሬ ገለጸ',\n", - " 'tr_471_tr05071': 'አሁን ግን እ ዚሁ እ ከተማችን ጠንቋይ ተገኘ',\n", - " 'tr_472_tr05072': 'እንደ ተመስገን ገለጻ ከሆነ በጣም አስገራሚ ው ነገር የ ፖሊሶቹ ነው',\n", - " 'tr_473_tr05073': 'ክተት ሰራዊት ም ታ ነጋሪት በተ ባለ ማግስት አርበኛ ው ተመመ',\n", - " 'tr_474_tr05074': 'በ ሂደት ደሞ እነዚህ ኑ ጥልቅ እያደረገ ና እያሰፋ ተጉ ዟል',\n", - " 'tr_475_tr05075': 'ጉባኤ ያንድ ወገን አመለካከት ብቻ እንዲያ ንጸባርቅ ተደርጐ መዘጋጀት ይችላል',\n", - " 'tr_476_tr05076': 'ደጋፊ ዎቻችን ን ለ ማሳጣት የተደረገ መሆኑን እናውቃለን',\n", - " 'tr_477_tr05077': 'የ ህወሀት ማእከላዊ ኮሚቴ መደበኛ ስብሰባ ትናንትና ተጀመረ',\n", - " 'tr_478_tr05078': 'እንዲያ ደናቅፈ ንም እንደማ ን ፈቅድ ሊያ ደናቅፈ ን ቢ ሞክር ደግሞ ል ና ሸንፍ የምን ችልበት ደረጃ ላይ እየ ደረስ ን ስለሆነ የ ልማቱ ን እንቅስቃሴ እገሌ ያደ ፈረስ ብናል ያስቆ መናል የሚ ል ስጋት የ ለ ንም',\n", - " 'tr_479_tr05079': 'ተማሪዎቹ ባካሄ ዱት ህገ ወጥ እንቅስቃሴ በ ተሽከርካሪዎች ና በ ትምህርት ቤቶች ላይ ጥፋት ደርሷ ል',\n", - " 'tr_480_tr05080': 'በ ኢትዮጵያ የሚገኙ ኤርትራውያን ም ሻእቢያ እ ደርስ ላችኋለሁ በ ማለት ተንፍሶ የነበረው ን እብሪታቸውን እንደ ገና እ ያፋፋመ መሆኑን ም መረዳት ተችሏል',\n", - " 'tr_481_tr05081': 'የ ኢትዮጵያ ሬዲዮ ታሽጓል ብሎ ወሬ ማ ና ፈሱ ፍጹም እንዳሳ ዘናቸው ለ ሪፖርተራችን አስታውቀ ዋል',\n", - " 'tr_482_tr05082': 'ግን ታሪካቸው ተረ ስ ቷል አስታዋ ሽ አጥ ተዋል',\n", - " 'tr_483_tr05083': 'በ ሲዲኒ ኦሎምፒክ አስር ሺ ስምንት መቶ ተወዳዳሪ ዎች እና ሀያ አንድ ሺ ጋዜጠኞች ተገኝ ተዋል',\n", - " 'tr_484_tr05084': 'እና ተስማምተን ነው ል ና ሰልፈው የ ቻልነው ብለዋል',\n", - " 'tr_485_tr05085': 'ቪላ ፓርክ ዛሬ ት ደም ቃለች',\n", - " 'tr_486_tr05086': 'ይህ ትልቁ ምኞቴ ነው',\n", - " 'tr_487_tr05087': 'ምክንያቱ ም እውቀት ያለው ባለሙያ መጥቶ ለ አሰልጣኞቻችን ና ለ ተጫዋቾቻችን ከሚ ያውቀው ቆን ጥሮ ካስተማረ ስህተት ን እንድና ርም ያደርገ ናል',\n", - " 'tr_488_tr05088': 'ግን ስ ሄድ እንደ ትልቅ ቁም ነገር ተይዞ አይደለም',\n", - " 'tr_489_tr05089': 'የ ኢትዮጵያ ና የ አልጀርስ ልኡካን አልጀርስ ገቡ',\n", - " 'tr_490_tr05090': 'ክስ ገና እየ ተፈለገ ነው ያለው',\n", - " 'tr_491_tr05091': 'አርባ ስምንት የመንግስት ኩባንያዎች ኪሳራ ውስጥ ገብ ተዋል',\n", - " 'tr_492_tr05092': 'ችግሩ ን ተንበርካኪ ነትና ውጫዊ ነው ነው የሚሉት',\n", - " 'tr_493_tr05093': 'ጥገኛ ካፒታሊ ስቶች ፓለቲካ ዊ ኢኮኖሚያዊ ና ወታደራዊ ሀይ ላቸው ተዳክ ሟል ጸረ ህዝብ ቢሮክራሲ ያቸው ተደምስ ሷል',\n", - " 'tr_494_tr05094': 'ፕሬዚዳንቱ ለ ኢትዮጵያ አንድነት ለ ዋሉት ውለታ የ ኢትዮጵያ ህዝብ የ እጃቸው ን ይ ስጣቸው ብሎ ከ መመረቅ ሌላ ም ን ማለት ይችላል',\n", - " 'tr_495_tr05095': 'ለ ነገሩ ማ ለሰው መብት ለ መሟገት አይደል እዚያ ያሉት የ ራሳቸው መብት ሲ ዳጥ እንዴት ያስችላቸው ጠበቆች አጃቢ ፖሊሶች ባለ ጉዳዮች እስረኞች ችሎቱ ን ይሞ ሉታል',\n", - " 'tr_496_tr05096': 'ይሁን ና ኢትዮጵያ ፊቷ ን ወደ ልማት ስታ ዞር እስከ አፍንጫ ዬ ያስታጠቀች ኝ ኢትዮጵያ በ ኢኮኖሚው ም ት ደግፈ ኛለች የሚለው ተስፋ ብሩህ ነበር',\n", - " 'tr_497_tr05097': 'ተቃዋሚ ሀይሎች እንደሚ ሉት የ ፕሬዚዳንት ኢሳይያስ መንግስት ወደ አንድ ፓርቲ አገዛዝ በ መንሸራተት አምባገነን ነትን የ ኢኮኖሚ ውድቀት ንና ማሀበራዊ ቀውስ ን እ ያመቻቸ ነው',\n", - " 'tr_498_tr05098': 'ይህን ያል ኩት ያለ ምክንያት አይደለም',\n", - " 'tr_499_tr05099': 'ይህ ማስፈራሪያ በ ሁለት ምክንያቶች መሰረተ ቢስ ነው',\n", - " 'tr_500_tr05100': 'አንድ ለ አንድ ሆነ ን',\n", - " 'tr_501_tr06001': 'ከ ሁሉም የሚያስ ደን ቀኝ የተለያዩ ሙያ ዎች እንደ ሀገሩ ባህል ኢኮኖሚ ና እድገት ይለያ ያል',\n", - " 'tr_502_tr06002': 'ኤርትራ ና ኢትዮጵያ ለ ድንበር ኮሚሽኑ የ ይገባኛል ጥያቄዎቻቸው ንና ማስረጃ ዎቻቸውን የ ያዙ ማመልከቻ ዎች ማቅረባቸው ን የውጭ ጉዳይ ሚኒስትር አስረድ ቷል',\n", - " 'tr_503_tr06003': 'እርዳታ ያላገኙ ወረዳ ዎች መኖር ቸውንም ጠቁ መዋል',\n", - " 'tr_504_tr06004': 'ለ ሉአላዊነት ሲ ባል ነገ ደግሞ ለ መልሶ ማቋቋም እንደ ገና መዋጮ ቶንቦላ ልን ጠየቅ እንደምን ችል ማን ያው ቃል',\n", - " 'tr_505_tr06005': 'ዳግም ፈርኦን በ ኦርቶዶክስ ቤተ ክርስቲያን ተወለደ',\n", - " 'tr_506_tr06006': 'በ ተለያዩ አጋጣሚ ዎች በ እጃቸው የገባ ውን ገንዘብ በ ሳኡዲ ባንክ ማስቀመጣቸው ን በ እርግጠኝ ነት የሚናገሩ ት እነዚሁ ምንጮች አያይዘው እንደ ገለጹት ከ ትግል በኋላ ጥያቄ ው ተነስቶ ነበር',\n", - " 'tr_507_tr06007': 'በሌላ በኩል ግን የ ደረሱት ን ምንጮች እንደሚ ያመለክቱት ከሆነ ጃክሮስ ኢትዮጵያ የ ደንበኞቹ ን ገንዘብ የ መክፈል አቅም እንደሌለ ው ተ ገልጿ ል',\n", - " 'tr_508_tr06008': 'ማህበሩ ን ያቋቋሙ ት በስራ ገበታ ቸው ላይ ሆነው እንደሆነ የ ማህበሩ ን አላማ የሚያ ትተው ጽሁፍ ያስረዳ ል',\n", - " 'tr_509_tr06009': 'ቋንቋዎች ን አዋህ ዶ አንድ መልክ በ ማስያዝ ተማሪዎች በዚህ አዲስ ቋንቋ እንዲ ማሩ እቅድ ይይዛ ል',\n", - " 'tr_510_tr06010': 'ትውውቁ ከ አገር ደረጃ ይልቅ እንደ ግል ትውውቅ የሚ ቆጠር ነው',\n", - " 'tr_511_tr06011': 'በ ኢትዮ ኤርትራ ወሰን የ ኮንትሮባንድ ንግድ በስፋት እየተካሄደ መሆኑ ተገለጸ',\n", - " 'tr_512_tr06012': 'አጀንዳ ችን ም ሀቁ ንና እቅጩን ለ ካድሬው ማሳወቅ ነው',\n", - " 'tr_513_tr06013': 'ወደ ህትመት እስከ ገባ ን ድረስ ስለ ታሰሩበት ምክንያት ማስረጃ ባ ና ገኝም በ ኢትዮጵያ ንግድ ባንክ የስራ ዘመናቸው ወቅት ጋር በ ተዛ መደ ሁኔታ ሳይሆን እንደማይ ቀር ተገምቷል',\n", - " 'tr_514_tr06014': 'ምናልባት የ ዲፕሎማቲክ ኮሚኒቲ ው ታዛቢ ነት ተፈር ቷል ሀያ ስምንት የግል ተወዳዳሪ ዎች አሉ',\n", - " 'tr_515_tr06015': 'ጥሩነሽ ና ወርቅነሽ ከ ማረሚያ ቤቶች ና ከ ባንኮች ስፖርት ክለብ የ ተገኙ አትሌቶች ናቸው',\n", - " 'tr_516_tr06016': 'ወይዘሮ አልማዝ ኢህአዴግ ን እንዲ ከዱ ያስ ቻላቸው ፖለቲካዊ ምክንያት ጓደኞቻቸው አንድ ም ከ ስልጣን መወገዳቸው ሁለት ም ከ ሀገር መውጣታቸው ነው',\n", - " 'tr_517_tr06017': 'ቴሌኮሙኒኬሽን በ መንግስት በ ሞኖፖል ተይዞ እንዲቀጥል የሚያደርግ ና ኢንቨስትመንት ን የሚ ያበረታታ ነው ተ ብሏል',\n", - " 'tr_518_tr06018': 'የኤርትራ መንግስት አብያተ ክርስትያ ን ን ዘጋ',\n", - " 'tr_519_tr06019': 'በ ሺህ ዎች የሚ ቆጠሩ የ መቀሌ ነዋሪዎች በ ኢዴፓ ስብሰባ ተገኙ',\n", - " 'tr_520_tr06020': 'የ ትግል ስል ቶቻቸው ም እንደ ዚሁ የተለያዩ ናቸው',\n", - " 'tr_521_tr06021': 'በ ግንባር ቀደምትነት የ ገቡት ን የኤርትራ ወታደሮች አስክሬን በ ብዛት ተመልክተ ናል በ ማለት የ እማኝነት ዘገባው ን አጠና ቋል',\n", - " 'tr_522_tr06022': 'በ ኢትዮጵያ ና ኬንያ ድንበር በሚገኙ አሸባሪዎች ላይ ኬንያ ጠንካራ እርምጃ ልት ወስድ ነው',\n", - " 'tr_523_tr06023': 'አንድ ኢንጂነር ን ጨምሮ አምስት ሰዎች ተገደሉ',\n", - " 'tr_524_tr06024': 'አስክሬኑ ን የ መለየቱ ስራ ከ ጥርስ ብሩ ሽ ና ከ ማበጠሪያ ላይ በ ተገኙ ናሙና ዎች የሚ ፈጸሙ መሆኑን ባለሙያዎች ይናገራሉ',\n", - " 'tr_525_tr06025': 'ኢትዮጵያ በ ግብጽ ቤተ ክርስቲያን ስር የ ኖረች ና መንፈሳዊ አባቶች ም ከ ዚያው ሲ ሾሙ ላት የ ነበረች ና ት',\n", - " 'tr_526_tr06026': 'የ ሜትሮ ሎጂ ትንበያ ችግር እየፈጠረ ነው',\n", - " 'tr_527_tr06027': 'ኢትዮጵያ ከ ሻእቢያ ጋር መደራደር እንደማት ችል ጀ በሀ አስ ታወቀ',\n", - " 'tr_528_tr06028': 'እቃው ን የሚ ያውቁት ሰው ቤት አ ኑረው ትንሽ ውሀ ለመቀ ማመስ ተስማሙ',\n", - " 'tr_529_tr06029': 'እና ም ዙሪያ ገባው ን መ ገላ መጥ መደበኛ ሙያው ሆነ',\n", - " 'tr_530_tr06030': 'ሊቨርፑል ትልቅ ፕሮፌሽናል ክለብ ነው',\n", - " 'tr_531_tr06031': 'ወቅቱ ገና ትኩስ ጊዜ ነበር',\n", - " 'tr_532_tr06032': 'ኢንሴንቲቭ ማለት ም ን ማለት ነው ዝም ብሎ ኢንሴንቲቭ ኢንሴንቲቭ ማለት ብቻ አይደለም',\n", - " 'tr_533_tr06033': 'ስለ ክሪስ ት ያን ቪዬሪ ም ን ት ላለህ',\n", - " 'tr_534_tr06034': 'ወትሮ ኦዌን በ ትሬይኒንግ ሜዳ ላይ ባለው ትኩረት ና ንቁ ነት አሰልጣኞች ይ ደነቁ በት ነበር',\n", - " 'tr_535_tr06035': 'ሀኪም ቤት ሄጄ ኢንፌክሽን አለ ብህ ተባልኩ',\n", - " 'tr_536_tr06036': 'እግር ኳስ ለዚህ ነው ተወዳጅ ሊሆን የ ቻለው',\n", - " 'tr_537_tr06037': 'የ አዲስ አባ እግር ኳስ ፌዴሬሽን ለ ውድድር ኳስ ማቅረብ ተስኖት በ ራሳቸው ኳስ ነው የሚ ጫወቱ ት',\n", - " 'tr_538_tr06038': 'ባለፈው ሳምንት ቅዳሜ የ አዲስ አባ እግር ኳስ ፌዴሬሽን ጠቅላላ ጉባኤ በ አራት ኪሎ ስፖርት ማእከል ተካሂ ዷል',\n", - " 'tr_539_tr06039': 'ስምምነቶች ንም እንደ ተፈራረመ ከ ዜና ምንጮቻችን ለ መረዳት ች ለናል',\n", - " 'tr_540_tr06040': 'በ በጀት ስለሚ በ ል ጧቸው ትንሹ አሳ በ ትልቁ አሳ መዋጡ ግልጽ ነው',\n", - " 'tr_541_tr06041': 'በሚገባ የተደራጀ ና ጠንካራ ታክቲክ ያለው ቡድን ነው እስከ ማለት ደርሰዋል',\n", - " 'tr_542_tr06042': 'የ ጉና ቡድን ደግሞ ከዛ ንዚባሩ ፖሊስ ጋር ለሚ ያደርገው ግጥሚያ ሀሙስ እ ለት ወደ ስፍራው ሄ ዷል',\n", - " 'tr_543_tr06043': 'ኢትዮጵያ የ ተሰጣት ን የ ቴክኒክ ማብራሪያ እያ ጤነ ችው ነው',\n", - " 'tr_544_tr06044': 'የ ሻእቢያ ስትራቴጂ ም እንደ ፈለጋቸው የሚ ያዙት ና የ ነሱ ጥገኛ የሆነ መንግስት ኢትዮጵያ ውስጥ ማስቀመጥ ነው',\n", - " 'tr_545_tr06045': 'የሚያገኙ ት የ ወር ደመወዝ ፈጽሞ ኪሳቸው እንደማይገባ ና ቤተ ክርስቲያ ኗን በ ነጻ ለሚ ያገለግሉ ሰዎች ና ለ ነዳያን ይ ከፋፈል እንደ ነበር ለማወቅ ች ለናል',\n", - " 'tr_546_tr06046': 'ለዚህ የ አሸባሪዎች እንቅስቃሴ ም ኤርትራውያን ን በ ግንባር ቀደምትነት ስለ ተጠራጠረ ች እንደሆነ ዘገባው ገልጿ ል',\n", - " 'tr_547_tr06047': 'ይህ ች ላ ባይነት ነው ዛሬ ተማሪዎች ትምህርታቸው ን አቁመው ለ ስቃይ እንዲ ዳረጉ የጋበዛቸው',\n", - " 'tr_548_tr06048': 'የ ጣልያን ና የ ኢትዮጵያ ግንኙነት እ የተበላሸ ነው',\n", - " 'tr_549_tr06049': 'በዚህ እ ለት በ ብዙ ሺህ የሚ ቆጠሩ ኢትዮጵያዊያ ን ኒውዮርክ በ ሚገኘው የ ተባበሩት መንግስታት ድርጅት ጽፈት ቤት ፊት ለፊት ይሰበሰባሉ ና ተቃውሞ ያሰማ ሉ',\n", - " 'tr_550_tr06050': 'እነዚህ ኢንቬስተ ሮች ደግሞ ኦሮሞዎች አይደሉም',\n", - " 'tr_551_tr06051': 'ድርጅቶቹ በ ተጨማሪ በዛ ያሉ የ ዲዛይን የ ታሪክ ና የ ፎቶ ሰነዶች ን እንዲ ላክ ላቸው ጥያቄ ማቅረባቸው ንም አቶ ጌታቸው ጨምረው ገልጸዋል',\n", - " 'tr_552_tr06052': 'አገራዊ አንድምታ ውን ስን መለከት ሁለት ተጻራሪ የሆኑ ክስተቶች ን ያዘ ለ ሂደት ሆኖ እና የ ዋለን',\n", - " 'tr_553_tr06053': 'ይኸ ጣጣ ነው ሁላችን ንም ያስቸገረ ን',\n", - " 'tr_554_tr06054': 'ም ን ማለት ነው አንድ ነገር ላይ ብቻ እንስማ ማለን',\n", - " 'tr_555_tr06055': 'ዶክተር ፍቅሬ መኢሶን ነበር',\n", - " 'tr_556_tr06056': 'እነዚህ የ ጦር ወንጀለኞች ተብለው በ እስር የሚ ማቅቁ ፓይለ ቶቻችን የማን እስረኞች ናቸው የሚለው የ ህዝብ ጥያቄ ግን ዛሬ ም እንዳለ ነው',\n", - " 'tr_557_tr06057': 'ሬውተር እንደ ዘገበው ማስጠንቀቅ ያውን ለ ኤርትራ መንግስት የ ላከው የ የመን የውጭ ጉዳይ ሚኒስቴር ነው',\n", - " 'tr_558_tr06058': 'አንዱ ና ዋነኛው ምክንያት መንግስት በ ተለያዩ መንገዶች በ ማህበሩ ላይ ሲፈ ጥራቸው የ ነበሩት ጫና ዎች ናቸው',\n", - " 'tr_559_tr06059': 'መንግስት በውጭ በሚ ኖሩ ኢትዮጵያውያ ን ዘንድ ሙሉ ድጋፍ እንዳለው ሊ ያሳየን ፈልጓል',\n", - " 'tr_560_tr06060': 'ኢ ሳቅ የ ተባለው ሌላው የ ሶማሌ ጐሳ ምንጭ ኢ ሳቅ ኢ ብን አህመድ የተባለ ሶማሌ ና ኢትዮጵያዊ ት እናት ናቸው',\n", - " 'tr_561_tr06061': 'መንግስት በ ኢንቨስትመንት እንቅስቃሴ ላይ የ ተከሰቱ የ ፖሊሲ ና የ አሰራር ግድፈቶች ን ለ ማስወገድ ርምጃ መውሰዱ ከ ግሉ ኢንቨስትመንት ፍሰት የ ሚገኘው ን ድርሻ እንደሚያ ሻሽለው ም ገለጹ',\n", - " 'tr_562_tr06062': 'እኔ ግን ነፍጠኛ ም መድፈኛ ም እንዳል ሆ ኩኝ ል ነግራችሁ ብዬ እንጂ ፖለቲከኛ ሳል ሆን አሽሙረኛ ነኝ ብዬ እናንተ ን ላሳምናችሁ አል ሞክር ም',\n", - " 'tr_563_tr06063': 'ኮሎኔል በዛብህ ጴጥሮስ የ አማራጭ ሀይሎች ሊቀመንበር ዶክተር በየነ ጴጥሮስ ወንድም መሆናቸው ተያይዞ ተ ገልጿ ል',\n", - " 'tr_564_tr06064': 'የ መስተዳድሩ መግለጫ ከተማዋ ስር ነቀል ለውጥ እንደሚ ያስፈልጋት ገልጾ ህዝቡ በዚህ እንዲ ሳተፍ ቢ ጠይቅ ም ጊዜያዊ መስተዳድሩ የ መዋቅር ለውጡ ን ያስፈጽማል ተብሎ አይጠበቅ ም',\n", - " 'tr_565_tr06065': 'ለወደፊቱ በሚ ዘጋጀው ጉባኤ የ በ ኩሌን ሀሳብ ለ ካድሬው ይዤ አቀርባ ለሁ',\n", - " 'tr_566_tr06066': 'ኤኤፍፒ ከ ሶስት ሺ በላይ የኤርትራ ኩናማ ዎች ወደ ኢትዮጵያ ሸሽተው በ መግባት የኤርትራ ሰራዊት በ ሀይል እየ መለመላቸው ነው ሲሉ ውንጀላ ሰንዝ ረዋል',\n", - " 'tr_567_tr06067': 'ዋናው አላማችን አባላ ቶቻችን ን በ ስፖርቱ ተሳታፊ እንዲሆኑ ና ለ ሀገራችን ስፖርት የ በኩላቸው ን አስተዋጽኦ እንዲ ያበረክቱ እንጂ እንደ አንዳንድ ክለቦች ድርጅት ን ለ ማስተዋወቅ አይደለም',\n", - " 'tr_568_tr06068': 'በ ማጠቃለያ ውም በ እርዳታ አ ሰባሰቡ ወቅት ኢህአዲግ በ በጐ አይ ን የማ ይመለከታቸው ና በ አሸባሪነት ጠርጥሬ ያ ቸዋለሁ የሚ ላቸው ኢትዮጵያውያ ን የ ህግ ታራሚዎች ሳይ ቀሩ በ እርዳታው ተሳትፎ ማድረጋቸው ን አመልክ ቷል',\n", - " 'tr_569_tr06069': 'የ ኢትዮጵያ ን የ ተፈጥሮ ሀብት ለ ማስተዋወቅ የ ሚያስችል የ መረጃ ስርአት ሊ ዘረጋ ነው ተ ባለ',\n", - " 'tr_570_tr06070': 'ይሁን እንጂ የ ፕሬሱ ን እድገት ለ ማሽመድመድ ብዙዎቹ እንዲ ቀጥሉ አልተደረገ ም ሲሉ ነጻው ፕሬስ ለ ዲሞክራሲያዊ ስርአት ግንባታ የሚያደርገው ን ሚና አሳቅ ለዋል',\n", - " 'tr_571_tr06071': 'ይህንን ም ያደረገ መንግስቱ ን መውደዱ በዚህ ያስታው ቃል',\n", - " 'tr_572_tr06072': 'ቀጥሎ ሙሉው ን መልእ ከ ት እንደሚ ከተለው እና ቀር ባለ ን',\n", - " 'tr_573_tr06073': 'ጆሮ ያለው ይስማ አእምሮ ያለው ም ያስተውል',\n", - " 'tr_574_tr06074': 'እንዴት እንሂድ በት መድረኩ ን እንዴት እን ሻገር በ ሚለው መጭው ጉዟችን ን በሚያ ቅደው ጉዳይ ም ሶስት ጽሁፎች ቀርበዋል',\n", - " 'tr_575_tr06075': 'ከ ጉባኤ ቀጥሎ የሚ መጣው ማእከላዊ ተቋም ማአከላዊ ኮሚቴ ነው',\n", - " 'tr_576_tr06076': 'ምክንያቱ ም እነርሱ ኮሚኒስቶች እኛ ዲሞክራ ቶች ነን',\n", - " 'tr_577_tr06077': 'የ ናይል ተፋሰስ የ ትብብር ሂደት አባላት ኢትዮጵያ ሱዳን ኬንያ ግብጽ ታንዛኒያ ሩዋንዳ ኮንጐ ኡጋንዳ ና ቡሩንዲ ሲ ሆኑ ኤርትራ በ ታዘ ቢ ነት ትሳተፋ ለች',\n", - " 'tr_578_tr06078': 'ፎረሙ ለ ሁለተኛ ጊዜ የሚ ሰጠው ን ሽልማት ለ አላሙዲ ን የሚያ በረክተው ዛሬ በ ዋሽንግተን ዲሲ ከተማ ነው',\n", - " 'tr_579_tr06079': 'የ ኦሮሚያ ተማሪዎች እንቅስቃሴ ና ተቃውሞ ከ ኦነግ ጋር የ ተያያዘ ነው ያሉት አቶ ጁነዲ ን ኦነግ ወጣቱ ን መጠቀሚያ እያደረገ ው ነው ሲሉ ም ውንጀላ አ ሰምተዋል',\n", - " 'tr_580_tr06080': 'ከ መንገድ የ ተመለሱ ኢትዮጵያውያ ን በ አስመራ ዩኒቨርስቲ ተጠልለው እንደሚገኙ ም የ ጀርመን ድምጽ ሬድዮ ከ ትናንት በስቲያ ዘግ ቧል',\n", - " 'tr_581_tr06081': 'የሚ ሞቱ ላትን ማግኘት ደግሞ እድለኛ ነት ነው',\n", - " 'tr_582_tr06082': 'መስጊዱ ዛሬ ጫካ ውስጥ ነው ያለው',\n", - " 'tr_583_tr06083': 'የ አለም ታዋቂ ስፖርት ሙያተኞች ፊታቸው ን ወደ እኛ ለ ማዞር ተገ ደዋል',\n", - " 'tr_584_tr06084': 'ሮናልዶ ም ቢሆን ናይክ ኩባንያ ሌሎች የ ቡድኑ ቴክኒክ ኮሚቴ አባላት ዛጋሎ ም ሆኑ ዚኮ ማ ንም እንድ ጫወት አላስ ገደዱ ኝም ብሏል',\n", - " 'tr_585_tr06085': 'አሰልጣኝ ጆን ግሮ ጐሪ በማ እ ዳቸው ዝና ካ ላቸው ክለቦች መካከል ሊቨርፑል ብቻ ነው ያስተናገዱት',\n", - " 'tr_586_tr06086': 'በ ዝግ ስታዲየም ጨዋታዎች ከተ ከናውነው ያውቃሉ ለተ ወዳጆቹ ኢን ተሮች እንደ ተለመደው በ ቅድሚያ ሰላምታ ዬን እ ያቀረብኩ እ ጀምራ ለሁ',\n", - " 'tr_587_tr06087': 'ሙሉ ስማቸው ዣን ሚ ሼል ቤኔዜ ይባላል',\n", - " 'tr_588_tr06088': 'እንደሚ ገባኝ የ ም ኖረው የዛሬ ን በ ማሰብ ነው',\n", - " 'tr_589_tr06089': 'የ ሶማሊያ ስደተኞች ወደ ኢትዮጵያ እየ ጐረፉ ነው',\n", - " 'tr_590_tr06090': 'በ ህገ መንግስታችን ላይ እንደ ሰፈረው ማንኛውም ሰው ዋስትና የ ማግኘት መብት አለ ው',\n", - " 'tr_591_tr06091': 'ሌሎች ተጨማሪ ሶስት መቶ የ ጣ ና ገበያ ሰራተኞች ም እንዲ ሁ ተመሳሳይ አደጋ አንዣብቦ በ ቸዋል',\n", - " 'tr_592_tr06092': 'የ ኢትዮጵያ መንግስት የ ማስፈጸም አቅሙ ሊ ጠነክር ና ሊ ጐለብት ይችላል',\n", - " 'tr_593_tr06093': 'ዛሬ ደግሞ ያ እ ርእዮት ተናጋ',\n", - " 'tr_594_tr06094': 'ሰዎቹ አእምሮ ውስጥ ዘወትር ያለው ም ጠመንጃ ነው',\n", - " 'tr_595_tr06095': 'መደማመጥ እጅግ አስቸጋሪ ነው',\n", - " 'tr_596_tr06096': 'እኒህ ኢትዮጵያዊ ከ ዚያች ቀን ጀምሮ በ ጠላትነት የ ተፈረጁ ና ዛሬ ም በ አዛውንት እድሜ አቸው በ ደካማ ጤናቸው በ እስር የሚ ማቅቁ ት ፕሮፌሰር አስራት ወልደየስ ናቸው',\n", - " 'tr_597_tr06097': 'አንዳንድ ታዛቢዎች እንደሚ ሉት አቶ ኢሳይያስ የ ደጋው ክርስቲያን ህዝብ ተወካይ ተብለው ተ ፈርጀ ዋል',\n", - " 'tr_598_tr06098': 'ለዚህ ም ሶስት ምክንያቶች ን አቅርበ ዋል',\n", - " 'tr_599_tr06099': 'የ መንገደኞች አውሮፕላን ለ መጥለፍ የ ተደረገው ሙከራ ከሸፈ',\n", - " 'tr_600_tr06100': 'ምክንያቱ ም ስኮትላንዶች ያገቡ ትን ጐል በ ዝግታ ያስተላልፍ ነበር ይላል የዛሬ ተ ጋባዣችን ማይክል ኦ ይ ን',\n", - " 'tr_601_tr07001': 'ስራው ንም አያገኝ ም ምክንያቱ ም እነሱ ባላቸው ደረጃ ና ዲስፒሊን የተወሰነ ብቃት ሊ ኖረው ይገባል',\n", - " 'tr_602_tr07002': 'የ ኢትዮጵያ ብሄራዊ ቡድን ጊኒ ን በ ማሸነፍ ደረጃው ን አ ሻሻለ',\n", - " 'tr_603_tr07003': 'ግንባሩ ና አባል ድርጅቶቹ ከ ኢህአዴግ ጉባኤ በኋላ በ የ ደረጃው የሚገኙ አባላት ዘንድ የ ተሀድሶ ውን አስተሳሰብ ለ ማስረጽ ና ለ ማጐልበት የሚያስችሉ እንቅስቃሴ ዎች ማካሄዳቸው ን አስ ታውቋል',\n", - " 'tr_604_tr07004': 'ግን አዲስ የ ተሾሙ አምባሳደሮች ም ሆኑ ተሰናባ ቾቹ አምባሳደሮች ለ ፕሬዝዳንት ነጋሶ ኤርትራውያን ከ ሀገር እንዲ ባረሩ የ ተደረገበት እርምጃ ን መንግስት ሊ መረምረው ይገባል ብለዋ ቸዋል',\n", - " 'tr_605_tr07005': 'የ ኢትዮጵያ ኦርቶዶክስ ተዋህዶ ቤተ ክርስቲያን ካህናት ና ምእመናን መከራ የ ገጠማቸው በ ሀገራቸው በ ቤታቸው ነው',\n", - " 'tr_606_tr07006': 'ጥያቄ ውን ያነሱት ስለ ጉዳዩ በሚገባ የሚያውቁ የ ጦር መኮንኖች ናቸው',\n", - " 'tr_607_tr07007': 'የ ኢሳያስ አስተዳደር ለ ኢትዮጵያዊያ ን ህጻናት የ ዝመቱ ጥሪ ማቅረቡ ተጋለጠ',\n", - " 'tr_608_tr07008': 'ክርስቶስ ከ ሙታን እንደ ተነሳ በ ሀዋርያት ተ ጽፏል',\n", - " 'tr_609_tr07009': 'አንዳንድ የ ን አካባቢው ምንጮች እንደ ገለጹት ከሆነ ከዚህ ቀደም ቋንቋው ን በ መቃወማቸው ታስረው የነበሩ ሰዎች ን እስከ ማስፈታት ደረጃ ተደረሰ',\n", - " 'tr_610_tr07010': 'ስዊዘርላንድ ከ ኢትዮጵያ ይልቅ ወደ ኤርትራ ስት ን ሸራተት የምት ታይ አገር ነች',\n", - " 'tr_611_tr07011': 'ሁሴን አይዲድ በ ተሸናፊ ነት አዲስ አበባ ናቸው',\n", - " 'tr_612_tr07012': 'ቅድሚያ እድሉ ን እንዲ ሰጠን እየ ጠየቅ ን ነው',\n", - " 'tr_613_tr07013': 'ኢትዮ ፕስ አርት ወደ ጃፓን ሄደ',\n", - " 'tr_614_tr07014': 'በዚህ ላይ እጩዎች ን ለ ማስተዋወቅ ብዙ መድረኮች አሉት',\n", - " 'tr_615_tr07015': 'ዘመናዊ ስታዲየም እን ገነባ ለ ን ብለው ነበር ፕሬዚዳንት መንግስቱ ሀይለ ማርያም',\n", - " 'tr_616_tr07016': 'ም ንም እንኳ ን ኢህአዴግ በ ፌዴሬሽን ምክር ቤት ውስጥ አለ ኝ ብሎ የሚመካ ባቸው ቢሆን ም ውሎ አድሮ ሊፈ ነቅ ላቸው እንደሚ ችል ገም ተዋል',\n", - " 'tr_617_tr07017': 'ኢትዮጵያውያ ን ታጣቂዎች በ ሰላም አስከባሪ ዎች ላይ ተኩ ሰዋል',\n", - " 'tr_618_tr07018': 'የኤርትራ መንግስት ከ ኦርቶዶክስ ተዋህዶ ሮማን ካቶሊክ ና ከ ወንጌላዊ ት መካነ ኢ የሱስ ቤተ ክርስቲያና ት በስተቀር ሌሎች አብያተ ክርስትያናት ን መዝጋቱ ታወቀ',\n", - " 'tr_619_tr07019': 'የ ተናገሩት እኛ እየ ለመን ን ነበር',\n", - " 'tr_620_tr07020': 'ለ አለም ዋንጫ ማጣሪያ በ መጀመሪያ ው ዙር ኢትዮጵያ ቡርኪናፋሶ ን አሸነፈ ች',\n", - " 'tr_621_tr07021': 'የ ኦጋዴን ነጻ አውጪ ግምባር በ ምስራቅ ኢትዮጵያ ሽምቅ ውጊያ ከፈት ኩ አለ',\n", - " 'tr_622_tr07022': 'ካናቢስ ተጠቅ መዋል የተባሉ ኢትዮጵያዊ ገበሬ ና አንድ አሜሪካዊ ተያዙ',\n", - " 'tr_623_tr07023': 'ለ ኢትዮጵያ ወደብ ይገባ ታል ባለ ማለቴ ተጠያቂ ነኝ አሉ ገብሩ አስራት በ ለንደን',\n", - " 'tr_624_tr07024': 'በ ጀርመን ለምን ገኝ ኢትዮጵያውያ ን ስደተኞች በሚል የ ተላለፈው ሪፖርት ከ ስደተኝነት መብት አኳያ የ ሚከተለው ን መብት ይ ዟል',\n", - " 'tr_625_tr07025': 'ኤርትራ ወራሪ ና ት',\n", - " 'tr_626_tr07026': 'ኢትዮጵያውያኑ ኤርትራውያኑ ን እንደሚ ቀጡ ያ ም ና ሉ',\n", - " 'tr_627_tr07027': 'በ ሶስት ስትራቴጂ ያዊ ወታደራዊ ቀጠና ዎች ሀያ ሺ የ ኢሮብ ነዋሪ ተገዶ ወደ ማጐሪያ ካምፕ ተከማች ቷል',\n", - " 'tr_628_tr07028': 'ንዴት ከ አረቄ ው ጋር ተባብሮ ቢያ ነደው ም እቃው ን ተሸክሞ ጉዞ ጀመረ',\n", - " 'tr_629_tr07029': 'እንደ ገላመጣት አልቀረ ም ቆሎ ዋን ሸጣ ወደ ቤቷ ስት ኳት ን ከ ዙፋኑ ተነስቶ ተ ከተ ላት',\n", - " 'tr_630_tr07030': 'በዚያ ክለብ ውስጥ የሚ ሰሩት በ ሙሉ ስራቸው ን ያውቁ ታል',\n", - " 'tr_631_tr07031': 'ስለዚህ ብዙ ያስተዋል ኳቸው ነገሮች የ ሉም',\n", - " 'tr_632_tr07032': 'እስከሚ ገባ ን ኢንሴንቲቭ ና ቦነስ ይለያ ያሉ',\n", - " 'tr_633_tr07033': 'እርሱ ድንቅ ነው',\n", - " 'tr_634_tr07034': 'ይህን አይነት ክትትል ነው ኦዌን የሚ ያስፈልገው እየተ ባለ ነው',\n", - " 'tr_635_tr07035': 'ግን ከዚያ በኋላ እንዴት ልት ቀንስ ቻልክ',\n", - " 'tr_636_tr07036': 'በሚ ሰጣቸው ፕሮግራም ና እረፍት ይ እራሳቸው ን አዝና ን ተው ይ መጣሉ',\n", - " 'tr_637_tr07037': 'ነገሩ ግን አስገራሚ ሆኗል',\n", - " 'tr_638_tr07038': 'ሻምበል ማሞ ወልዴ እንደ ማንኛውም ኢትዮጵያዊ በ ህግ ይዳ ኛል',\n", - " 'tr_639_tr07039': 'አዲዳስ ደግሞ የ ጀርመን ነው',\n", - " 'tr_640_tr07040': 'ስለዚህ ይህን አውቀ ን ባይሆን ክ ለ ክልሎች ስፖርት እድገት የሚ ጠቅመው ን እንስራ',\n", - " 'tr_641_tr07041': 'እንዲያ ውም የ ሪያል ማድሪድ ክለብ እየጐተጐተ ው መሆኑን በ ስፔን የሚ ና ፈሱ ወሬ ዎች አሉ',\n", - " 'tr_642_tr07042': 'ቡድኑ አስራ ስምንት ተጨዋቾች ን ይዞ ነው የሚ ሄደው',\n", - " 'tr_643_tr07043': 'ሌላኛው ም የ ኢትዮጵያ መሰረታዊ ጥያቄ በ ግጭቱ ስፍራ የ ኢትዮጵያ ሲቪላ ዊ አስተዳደር እና የ ፖሊስ ተቋማት እንዲ ቋቋሙ ያቀረበች ውን አቋሟ ን እስከ አሁን ድረስ አል ለወጠች ውም',\n", - " 'tr_644_tr07044': 'ታዛቢዎች እንደሚ ሉት ደግሞ እህል ከ ኢትዮጵያ ወደ ኤርትራ በ ጅቡቲ በኩል እንደሚ ሄድ ይናገራሉ',\n", - " 'tr_645_tr07045': 'ዶክተር ነጋሶ ማን ናቸው ከ እርስዎ በላይ የሚ ቀርባቸው ሰው የ ለ ም',\n", - " 'tr_646_tr07046': 'ዶክተር በየነ ጴጥሮስ በ ተወዳደሩ ባቸው ዞኖች ውጤቱ እንዳይ ነገር ታገደ',\n", - " 'tr_647_tr07047': 'ነገር ግን ተዘዋው ሬ እንደ ተመለከትኩ ት ህመሙ የ ጠና ባቸው ና በልዩ ስፍራ ተ ከልለው አይ ሶሌ ሽን የ ተገኙት ተማሪዎች ብዛት ወደ አራት መቶ ይጠ ጋል',\n", - " 'tr_648_tr07048': 'በ ጉዳዩ ዙሪያ አስተያየታቸው ን የ ጠየቅናቸው ታዛቢዎች እንዳሉት ከሆነ ጣሊያን ና ኢትዮጵያ በ ኢትዮ ኤርትራ ጦርነት ጊዜ ና በ ሱማሊያ ጉዳይ ዙሪያ አለመግባባቶች አ ሏቸው',\n", - " 'tr_649_tr07049': 'በ ዋሽንግተን ና አካባቢ ዋ የሚኖሩ ኢትዮጵያውያ ን አስራ ሁለት አውቶቡሶች የ ተከራዩ ሲሆን በ እለቱ ወደ ኒውዮርክ ከተማ ተቃውሟቸው ን ለ ማሰማት ይገሰግ ሳሉ',\n", - " 'tr_650_tr07050': 'የ ነጻው ፕሬስ ህልውና አስጊ ሆኗል',\n", - " 'tr_651_tr07051': 'የ ትልማ ፕሬዚዳንት በ አቶ ገብሩ ምክንያት ወረዱ',\n", - " 'tr_652_tr07052': 'ይህ እንግዲህ የ ፖሊሲው አንደኛው ገጽታ ነው',\n", - " 'tr_653_tr07053': 'ፕሮፌሰር አክሊሉ የ ኢትዮጵያ መንግስት ልዩ አማካሪ በ ነበሩ ጊዜ ም የ ኢትዮጵያ የ ሳይንስ ና የ ቴክኖሎጂ ኮሚሽን እንዲ ቋቋም አድርገዋል',\n", - " 'tr_654_tr07054': 'ቋንቋ አዳጊ ስለሆነ የ ስ የ ስ ነገሩ ገብቶ ናል ብለን ልናል ፈው እንችላ ለ ን',\n", - " 'tr_655_tr07055': 'ለኔ ሞት ሞት ነው',\n", - " 'tr_656_tr07056': 'ኤርትራ የ ታጠቀ ችው ሚግ ሀያ ዘጠኝ በ ሩሲያ ውስጥ ካሉ ት ምጡቅ የ ኤሮ ኖ ቲክስ ቴክኖሎጂ ውጤት አንዱ ነው',\n", - " 'tr_657_tr07057': 'በሚ ሆን መንገድ እልባት ካላገኘ ይህ የ ታሪክ እንቆቅልሽ ሊ ቀጥል እንደሚ ችል መገመት ም አ ያስቸግር ም',\n", - " 'tr_658_tr07058': 'አስራ ሶስት ሺ ያህል ተፈናቅ ለዋል',\n", - " 'tr_659_tr07059': 'ህዝብ ና የ መረጣቸው ወኪሎቹ የማያውቋቸው ተግባሮች በ መንግስት ባለስልጣናት በ ጓዳ እንዳይ ፈጸሙ ይፈልጋል',\n", - " 'tr_660_tr07060': 'እስረኞቹ ም እንዲ ለቀቁ የ ሚመለከታቸው ኢትዮጵያውያ ን እና ተቃዋሚ ቡድኖች ጠንካራ ዘመቻ እያ ካሄዱ ናቸው',\n", - " 'tr_661_tr07061': 'መንግስት በ ኢንቨስትመንት እንቅስቃሴ ላይ የ ተከሰቱ የ ፖሊሲ ና የ አሰራር ግድፈቶች ን ለ ማስወገድ እርምጃ መውሰዱ ከ ግሉ ኢንቨስትመንት ፍሰት የ ሚገኘው ን ድርሻ እንደሚያ ሻሽለው ም ገለጹ',\n", - " 'tr_662_tr07062': 'እኔ ግን ነፍጠኛ ም መድፈኛ ም እንዳል ሆ ኩኝ ልንገራችሁ ብዬ እንጂ ፖለቲከኛ ሳል ሆን አሽሙረኛ ነኝ ብዬ እናንተ ን ላሳምናችሁ አል ሞክር ም',\n", - " 'tr_663_tr07063': 'ኮ ኖሬ ል በዛብህ ጴጥሮስ የ አማራጭ ሀይሎች ሊቀመንበር የ ዶክተር በየነ ጴጥሮስ ወንድም መሆናቸው ተያይዞ ተ ገልጿ ል',\n", - " 'tr_664_tr07064': 'የ መስተዳድሩ መግለጫ ከተማዋ ስር ነቀል ለውጥ እንደሚ ያስፈልጋት ገልጾ ህዝቡ በዚህ እንዲ ሳተፍ ቢ ጠይቅ ም ጊዜያዊ መስተዳድሩ የ መዋቅር ለውጡ ን ያስፈጽማል ተብሎ አይጠበቅ ም',\n", - " 'tr_665_tr07065': 'ለወደፊቱ በሚ ዘጋጀው ጉባኤ የ በ ኩሌን ሀሳብ ለ ካድሬው ይዤ እ ቀር ባለሁ',\n", - " 'tr_666_tr07066': 'ኤኤፍፒ ከ ሶስት ሺ በላይ የኤርትራ ኩናማ ዎች ወደ ኢትዮጵያ ሸሽተው በ መግባት የኤርትራ ሰራዊት በ ሀይል እየ መለመላቸው ነው ሲሉ ውንጀላ ሰንዝ ረዋል',\n", - " 'tr_667_tr07067': 'ዋናው አላማችን አባላ ቶቻችን በ ስፖርቱ ተሳታፊ እንዲሆኑ ና ለ ሀገራችን ስፖርት የ በኩላቸው ን አስተዋጽኦ እንዲ ያበረክቱ እንጂ እንደ አንዳንድ ክለቦች ድርጅት ን ለ ማስተዋወቅ አይደለም',\n", - " 'tr_668_tr07068': 'በ ማጠቃለያ ውም በ እርዳታ አ ሰባሰቡ ወቅት ኢህአዲግ በ በጐ አይ ን የማ ይመለከታቸው ና በ አሸባሪነት ጠርጥሬ ያ ቸዋለሁ የሚ ላቸው ኢትዮጵያውያ ን የ ህግ ታራሚዎች ሳይ ቀሩ በ እርዳታው ተሳትፎ ማድረጋቸው ን አመልክ ቷል',\n", - " 'tr_669_tr07069': 'በ ኢትዮጵያ የ ተከሰተው የ ምግብ እጥረት ወደ ተባባሰ ደረጃ ሊ ሸጋገር እንደሚ ችል ስጋት መኖሩ ተነገረ',\n", - " 'tr_670_tr07070': 'ፕሮፌሰር አስራት ሆስፒታል እንደ ተኙ ነው',\n", - " 'tr_671_tr07071': 'አንተ ግን ውስጥ ለ ውስጥ መሸጥ ህን ና መግዛት ህን የማት ተው ሆንክ',\n", - " 'tr_672_tr07072': 'የ ሚከተለው ም እምነት ክርስትና ነው',\n", - " 'tr_673_tr07073': 'እንዲሁም ሀብታሙ ሰው ሞተ ና ተቀበረ',\n", - " 'tr_674_tr07074': 'ጥያቄዎች አንስተ ን የመሰለ ን ን አቋም እንወስ ዳለን',\n", - " 'tr_675_tr07075': 'አባላቱ በ ጉባኤ የ ተመረጡ ናቸው',\n", - " 'tr_676_tr07076': 'በ አዲስ አበባ ዩኒቨርስቲ የሚማሩ ተማሪዎች መሰባሰብ ጀምረ ዋል',\n", - " 'tr_677_tr07077': 'ኢትዮጵያ በ አብዛኛው የ ኢኮኖሚ ነጻነት ያል ሰፈነ ባት አገር ተባለች',\n", - " 'tr_678_tr07078': 'ፎረሙ ሁለተኛው ን ስብሰባው ን ትላንት በዚያ ችው ከተማ ጀም ሯል',\n", - " 'tr_679_tr07079': 'ዛሬ ወገኖቻችን በ ማዳበሪያ ና በ ግብር እዳ እየተ ሰቃዩ ነው',\n", - " 'tr_680_tr07080': 'በ ስደት የሚገኙ ተማሪዎች ን ለ መመለስ በ መንግስት የተላከ ው ስምንት አባላት ያለው ቡድን ያለ ውጤት ተመለሰ',\n", - " 'tr_681_tr07081': 'ከ ሀያ የሚበልጡ ት ደግሞ ተ ሰደዋል',\n", - " 'tr_682_tr07082': 'ታዲያ ይህ ታላቅ የ ታሪክ ቅርስ እንደምን እንዲ ህ ተረስቶ ና ተዳፍ ኖ የቀረ የሚ ል ሊ በዛ ነው የሚ ከጀለ ው ዛሬ',\n", - " 'tr_683_tr07083': 'ገዛ ኸኝ አባራ በ ማራቶን ባሸነፈ ማግስት ሁለት ሺ ማራቶን ማ ጂክ በሚል ርእስ ሰፊ ዘገባ ቀርቧል',\n", - " 'tr_684_tr07084': 'ከዚህ ሌላ የ ሀገሪቱ ፕሬዚዳንት ፌርናንዶ ሄን ሪኬ ካርዶ ዞ ኤርፖርት ተገኝተው የ እንኳ ን ደህ ና መጣችሁ አበባ አበርክ ተው ላቸዋል',\n", - " 'tr_685_tr07085': 'ወደ ጣልያን ስ ና መራ ባለፈው እሁድ መሪው ፊዮሬንቲና ወደ ባሪ ተ ጉዞ ሁለት ነጥብ ጥሎ እና ገኘ ዋለን',\n", - " 'tr_686_tr07086': 'እና ም አንተ የዚህ ሰለባ እንደ ሆንክ ነው የሚ ሰማኝ',\n", - " 'tr_687_tr07087': 'አንዳንዴ ም እስከ ሶስት ጨዋታ ለ መመልከት ች ያለሁ',\n", - " 'tr_688_tr07088': 'እንዲያ ውም ያ ወቅት ብዙ አልቆ የ ም',\n", - " 'tr_689_tr07089': 'የ ሶማሊያ ስደተኞች ሊ ሰደዱ የ በቁት ድርቅ ደቡባዊ ሶማሊያ ን ክፉ ኛ ስለ መታው እንደሆነ ተመልክ ቷል',\n", - " 'tr_690_tr07090': 'ምክንያት ሲ ያጡ እኔን በ እስር ቤት ለ ማቆየት ብቻ ምክንያት እየ ፈጠሩ ብኝ ነው',\n", - " 'tr_691_tr07091': 'ጉዳዮች ውድቅ እንደሚ ያደረጉ እኔ ና ሌሎቹ ተከሳሾች አስቀድመ ን አ ም ተ ን ነበር',\n", - " 'tr_692_tr07092': 'አላማችን ን እንስ ታለን የሚ ል ሀሳብ ነው ያ ላቸው',\n", - " 'tr_693_tr07093': 'የ ኛ ም መንገዳችን ያው ይመ ስላል',\n", - " 'tr_694_tr07094': 'ይህ ሁሉ ከ አባቶቻችን ና ከ እናቶቻችን የ ወረስ ነው ነው',\n", - " 'tr_695_tr07095': 'ወደ እስር ቤታቸው ተመለሱ',\n", - " 'tr_696_tr07096': 'ምናልባት ይሄን ን እናንተ ም ሳት ሰሙት የ ቀራ ችሁት አይመስ ለ ንም',\n", - " 'tr_697_tr07097': 'ሌላው የ አሜሪካኖች ን ትኩረት የ ሳበው የ ተቃዋሚዎች ን እንቅስቃሴ ነው',\n", - " 'tr_698_tr07098': 'የ ፕሮፌሰር መስፍን ህመም መንስኤ የ ሳምባ ም ች ኒሞኒያ እንደሆነ ለማወቅ ተችሏል',\n", - " 'tr_699_tr07099': 'የ አክሱም ሀውልት እንዲ መለስ ኢትዮጵያ ያቀረበች ው ረቂቅ ውሳኔ አአድ አ ጸደቀው',\n", - " 'tr_700_tr07100': 'ምክንያቱ ም ባለ ኝ ኳሊቲ ዎች እ ተማ መ ና ለሁ',\n", - " 'tr_701_tr08001': 'ያን ን ለ ሟሟላት ትምህርት መቅሰም ና የተለያዩ ፈተና ዎችን ማለፍ ይገባ ዋል',\n", - " 'tr_702_tr08002': 'በ ሱዳን የ ተጀመረው ን የ ሰላም ሂደት ተግባራዊ ለማድረግ መንግስት ና ተቃዋሚ ድርጅቶች የ ተኩስ አቁም እንዲያደርጉ ና ህዝቡ ን ከ ስቃይ ለማዳ ን እንዲ ጥሩ አሳስቧ ል',\n", - " 'tr_703_tr08003': 'ልዩ የ ንግድ ስምምነቱ የ ኢትዮ ሱዳን ን ኢኮኖሚያዊ ና ፖለቲካዊ ትስስር ወደ ላቀ ደረጃ የሚ ያሸጋግር ነው',\n", - " 'tr_704_tr08004': 'ተግባባን አሉ ብሎ አንዱ ነገረኝ',\n", - " 'tr_705_tr08005': 'እስራኤላውያን መከራው ሲ ጸና ባቸው ከ ተሰደዱ በት አገር በ ስንት መከራ ወደ አገራቸው ተመለሱ',\n", - " 'tr_706_tr08006': 'አብዛኞቹ ቃኘው ግቢ ውስጥ የሚገኙ ሲሆን ለ እያንዳንዳቸው ስድስት ሺ ብር ሰጥቶ ሸኝቷ ቸዋል',\n", - " 'tr_707_tr08007': 'ሁሴን አይዲድ በ ኢትዮጵያ ላይ ጦርነት ለሚያ ውጅ ማንኛውም አሸባሪ አገራቸው ምሽግ እንደማት ሆን ቃል ገቡ',\n", - " 'tr_708_tr08008': 'ሽብርተኞች ና ወንጀለኞች ም ሊ ያውቁት የሚገባው ይሄን ን ነው',\n", - " 'tr_709_tr08009': 'የ አካባቢው ነዋሪዎች ቢ ያንስ ሶስት ሰው እንደ ሞተ ነው የሚናገሩ ት',\n", - " 'tr_710_tr08010': 'እስከ አሁን ከ ኢትዮጵያ አንጻር የ ቆመው ሀቅ ብቻ ነው',\n", - " 'tr_711_tr08011': 'እንደ ምንጮቻችን ገለጻ ሁሴን አይዲድ ከውጭ ጉዳይ ሚኒስቴር ጋር እንደ ተነጋገሩ ግምት አሳድ ሯል',\n", - " 'tr_712_tr08012': 'ምክንያቱ ም ስለ ስብሰባው አስተያየት ሊ ኖረን ይችላል',\n", - " 'tr_713_tr08013': 'አስራ አምስት አርቲስቶች ን ያካተተ ው የ ኢትዮ ፕስ አርት ባህላዊ የ ሙዚቃ ቡድን ከ ጃፓን በ ተደረገ ለት ጥሪ መሰረት ጃፓን ገብቷል',\n", - " 'tr_714_tr08014': 'ላቁ አ ተ አንድ ለቆ ራሽ ራቁ አ ተ ይላሉ ቆራ ሽ እሳቸው ናቸው',\n", - " 'tr_715_tr08015': 'ከ ሽግግሩ መንግስት ማግስት ጀምሮ ክቡር ጠቅላይ ሚኒስትር ፕሬዚዳንት እንደ ነበሩ መለስ ዜናዊ ዛሬ ም ብዙ ሰዎች የሚ ያነሱት ና የሚ ያስታውሱ ት ነው',\n", - " 'tr_716_tr08016': 'የ ትግል ተሳትፎ የ አገልግሎት ሪቫ ን ሜዳይ ካገኙ ት ጄኔራሎች መሀከል ባለ አምስት ሪቫ ን በ ማግኘት ቅድሚያ የ ያዙት ብርጋዴር ጄኔራል ካሳ ደሜ ናቸው',\n", - " 'tr_717_tr08017': 'የ ጠቅላይ ሚኒስትሩ ወቀሳ ተ ተቸ',\n", - " 'tr_718_tr08018': 'መንግስት ለ ኢትዮጵያውያ ን ስደተኞች የሚ ጠቅም አሰራር እንዲ ዘረጋ ተጠየቀ',\n", - " 'tr_719_tr08019': 'የ ተጠቀሙ ት ወያኔ ና ጥቂት ካድሬዎች ብቻ ናቸው',\n", - " 'tr_720_tr08020': 'የ ኢትዮጵያ ንግድ ባንክ እነዚህ እጥረት ላለ ባቸው ባንኮች በ ሁለት አመት ውስጥ ሀያ ሚሊዮን ብር ብድር እንደ ሰጣቸው ም የ ውስጥ አዋቂ ምንጮቹ ገልጸዋል',\n", - " 'tr_721_tr08021': 'በተለይ ወታደራዊ ክንፋ ችንን እያ ጠናከር ን እንገ ኛለን',\n", - " 'tr_722_tr08022': 'አቶ ሀሰን በ ሪፖርታቸው እንደ ገለጹት ወደ አረብ ሀገሮች በ ህገ ወጥ መንገድ የሚ ሰደዱ ኢትዮጵያውያ ን ን ለ መርዳት በ ዮርዳኖስ የ ኢትዮጵያ ቆንስላ ጽፈት ቤት ተከፍ ቷል',\n", - " 'tr_723_tr08023': 'የኤርትራ ተቃዋሚ መሪ ኢሳያስ ን ዘለፉ',\n", - " 'tr_724_tr08024': 'በ ሀዲያ ትምህርት ቤቶች ተ ዘግ ተዋል የ ሰራተኞች ም ደሞዝ ተቋር ጧል',\n", - " 'tr_725_tr08025': 'ዛሬ ዩጐዝላቪያ በ ና ቶ የ ጦር ጀቶች እየ ተደበደበ ች ነው',\n", - " 'tr_726_tr08026': 'ይሁን ና የ ፈለገ ነገር ቢ ያጡ ና መስዋእት ነቱ ቢ ከፋ ም ኢትዮጵያውያኑ ኤርትራውያኑ ን እንደሚ ቀጡ ና እንደሚ ያሸንፉ ሙሉ በ ሙሉ እ ርግጠ ኞች ናቸው',\n", - " 'tr_727_tr08027': 'ኢትዮጵያ በ አንቶኖቭ ጀት ተጠቅ ማለች ሲል ም የኤርትራ መንግስት ክስ አቅርቧ ል',\n", - " 'tr_728_tr08028': 'አምሮ ባቸው እንደ ወጡ ፍጻሜ ያቸው ተበላሽቶ ዛሬ ባል ፍርዱ ን እየ ጠበቀ ነው',\n", - " 'tr_729_tr08029': 'ጨለማ ቦታ ስት ስ ደርስ ጩቤ ውን አውጥቶ አስፈራራ ት',\n", - " 'tr_730_tr08030': 'ያን እ ለት እንደማ ልጫወት ሲ ነግረኝ ተናድጄ ነበር',\n", - " 'tr_731_tr08031': 'በ አብዛኛው ጥሩ እውቀት ያ ላቸው ናቸው',\n", - " 'tr_732_tr08032': 'ኢንሴንቲቭ እ ኮ የሚ ታሰበው በ የ ጨዋታው ነው',\n", - " 'tr_733_tr08033': 'እስካሁን ሀያ ስድስት ደር ሻለሁ',\n", - " 'tr_734_tr08034': 'አሰልጣኝ ጋሪ ፍራን ሲ ስ ስፐርስ እያሉ ተጫዋቾች ን ብዙ ኪሎ ሜትሮ ች እያስ ሮጡ ከባድ የ ፊትነስ ትሬይኒንጐ ችን የሚያ ሰሩት በ ማክሰኞ ቀን ነበር',\n", - " 'tr_735_tr08035': 'እኔ እ ኮ ጥሩ እንዳል ሆንኩ አውቀ ዋለሁ',\n", - " 'tr_736_tr08036': 'ቡድናችን በ ተሸነፈ ቁጥር ተጫዋቾች ን ከ ዲስፕሊን ጋር በ ማገናኘት ተጠያቂ ማድረጉ ተገቢ አ ይመስለኝ ም',\n", - " 'tr_737_tr08037': 'ሎንስ በዚህ በ ቻምፒየንስ ሊግ ጨዋታ ላይ በ የ ጨዋታው ድል ካደረገ እያንዳንዱ ተጫዋች ሀያ አምስት ሺ ብር እንደሚ ያገኝ ታውቋል',\n", - " 'tr_738_tr08038': 'ውሳኔው ን ማግኘት የሚ ችለው ከ ህግ ፊት ነው',\n", - " 'tr_739_tr08039': 'በ አፍሪካ የ አዳዲስ ትጥቆች የሚመረቱ ባቸው ሀገሮች ሞሮኮ ና ቱኒዚያ ናቸው',\n", - " 'tr_740_tr08040': 'ሌሎቹ ግን እንደ ወትሮው አልነበሩ ም',\n", - " 'tr_741_tr08041': 'እስካሁን መሪው ፊዮሬንቲና ደረጃው ን ይዞ ጉዞው ን ተያይዞ ታል',\n", - " 'tr_742_tr08042': 'ቅዱስ ጊዮርጊስ በ አዳማ ሶስት ለ ዜሮ ተሸን ፎ በ አራተኛው ቀን ደግሞ መቀሌ ላይ ትራንስ ን ሶስት ለ አንድ ረ ቷል',\n", - " 'tr_743_tr08043': 'ስለ እኚህ ኢጣሊያ ዊ ዲፕሎማት ጀርባ ም ሆነ ስለ ሽምግልናው በ ኢትዮጵያ መንግስት በኩል እስከ አሁን ድረስ አስተያየት አልተሰጠ በት ም',\n", - " 'tr_744_tr08044': 'ስለሆነ ም የ ከተማው አስተዳደር ና ህዝብ ከተማው ን በምን አቅጣጫ እንደሚያ ደሙት እያወ ቁም ነበር',\n", - " 'tr_745_tr08045': 'ዶክተር ነጋሶ ማን እንደሆኑ ይግለጹ ሉን ተብሎ ለ ቀረበላቸው ጥያቄ ነጋሶ የኦሮሞ ባህላዊ ሀይማኖት የ ፕሮቴስታንት እምነት ተጽእኖ ዎች ያሳደሩ በት ሰው ነው በ ማለት መልሰዋል',\n", - " 'tr_746_tr08046': 'በሌላ በኩል ፕሬዚዳንት ኢሳያስ በ አሜሪካ ቆይታቸው ከ ፕሬዚዳንት ክሊንተን ጋር ለ መገናኘት ያደረጉት ጥያቄ ውድቅ እንደሆነ ባቸው ተ ገልጿ ል',\n", - " 'tr_747_tr08047': 'ጩኸታቸው በ ሆስፒታል የ ተኙ ትን ሌሎች ህሙማን ያስ በ ረግ ጋል',\n", - " 'tr_748_tr08048': 'በ ኢትዮጵያዊ ነታቸው የሚ ኮሩ ና በ ኢትዮጵያ አንድነት የሚያምኑ ነበሩ',\n", - " 'tr_749_tr08049': 'ለንደን ና ኒውዮርክ በ ኢትዮጵያዊያ ን ተቃዋሚ ሰልፈኞች ተጥለቀለቁ',\n", - " 'tr_750_tr08050': 'አንተነህ አላምረው በ ፕሮፌሽናል ነት በ መጫወት በ ታሪክ የመጀመሪያ ው ኢትዮጵያዊ ተጫዋች ሆነ',\n", - " 'tr_751_tr08051': 'ኢትዮጵያ ሰባ ሺህ ወታደሮ ቿን አሰናብ ታለች',\n", - " 'tr_752_tr08052': 'በ ኤርትራ የተለየ መንግስት ተቋቋመ',\n", - " 'tr_753_tr08053': 'ጥያቄ ው የዛሬ ሰላሳ አመት ገደማ ለጋ የ ኢትዮጵያ ተማሪዎች እንቅስቃሴ ን አ ና ቆረ አ ና ከሰ አ ራኮተ',\n", - " 'tr_754_tr08054': 'ያለ አንዳች ጥያቄ ከተ ባለ ደግሞ ያከራ ክራል',\n", - " 'tr_755_tr08055': 'እርምጃ ተወስዶ ባቸዋል ነበር የ ሚባለው',\n", - " 'tr_756_tr08056': 'ይህ ለምን እንደሆነ እንደሚ ከተለው እን የ ው',\n", - " 'tr_757_tr08057': 'ሻእቢያ ግን የኤርትራ ሀብት ለ ኤርትራውያን ብቻ የ ኢትዮጵያ ን ሀብት ግን ፖሊሲ ሳያ ግደን እን ጠቀም በት ባይ ነው',\n", - " 'tr_758_tr08058': 'ኤርትራ ነጻ አገር ና ት ተባለች',\n", - " 'tr_759_tr08059': 'ሀቁ ን ግን ታሳሪዎቹ ም እኛ ም እናውቀ ዋለን',\n", - " 'tr_760_tr08060': 'እንዲሁም ተገቢ የ ገንዘብ ድጋፍ እንዲ ያገኙ በ ብዙሀን መገናኛ ዎች ያለምን ም ገደብ እንዲ ጠቀሙ ና ከ ህዝብ ጋር እንዲ ገናኙ አድርጉ',\n", - " 'tr_761_tr08061': 'መንግስት በ ኢንቨስትመንት እንቅስቃሴ ላይ የ ተከሰቱ የ ፖሊሲ ና የ አሰራር ግድፈቶች ን ለ ማስወገድ ርምጃ መውሰዱ ከ ግሉ ኢንቨስትመንት ፍሰት የ ሚገኘው ን ድርሻ እንደሚያ ሻሽለው ም ገለጹ',\n", - " 'tr_762_tr08062': 'እኔ ግን ነፍጠኛ ም መድፈኛ ም እንዳል ሆ ኩኝ ል ነገራችሁ ብዬ እንጂ ፖለቲከኛ ሳል ሆን አሽሙረኛ ነኝ ብዬ እናንተ ን ላሳምናችሁ አል ሞክር ም',\n", - " 'tr_763_tr08063': 'ኮሎኔል በዛብህ ጴጥሮስ የ አማራጭ ሀይሎች ሊቀመንበር የ ዶክተር በየነ ጴጥሮስ ወንድም መሆናቸው ተያይዞ ተ ገልጿ ል',\n", - " 'tr_764_tr08064': 'የ መስተዳድሩ መግለጫ ከተማዋ ስር ነቀል ለውጥ እንደሚ ያስፈልጋት ገልጾ ህዝቡ በዚህ እንዲ ሳተፍ ቢ ጠይቅ ም ጊዜያዊ መስተዳድሩ የ መዋቅር ለውጡ ን ያስፈጽማል ተብሎ አይጠበቅ ም',\n", - " 'tr_765_tr08065': 'ለወደፊቱ በሚ ዘጋጀው ጉባኤ የ በ ኩሌን ሀሳብ ለ ካድሬው ይዤ አቀርባ ለሁ',\n", - " 'tr_766_tr08066': 'ኤኤፍፒ ከ ሶስት ሺ በላይ የኤርትራ ኩናማ ዎች ወደ ኢትዮጵያ ሸሽተው በ መግባት የኤርትራ ሰራዊት በ ሀይል እየ መለመላቸው ነው ሲሉ ውንጀላ ሰንዝ ረዋል',\n", - " 'tr_767_tr08067': 'ዋናው አላማችን አባላ ቶቻችን ን በ ስፖርቱ ተሳታፊ እንዲሆኑ ና ለ ሀገራችን ስፖርት የ በኩላቸው ን አስተዋጽኦ እንዲ ያበረክቱ እንጂ እንደ አንዳንድ ክለቦች ድርጅት ን ለ ማስተዋወቅ አይደለም',\n", - " 'tr_768_tr08068': 'በ ማጠቃለያ ውም በ እርዳታ አ ሰባሰቡ ወቅት ኢህአዲግ በ በጐ አይ ን የማ ይመለከታቸው ና በ አሸባሪነት ጠርጥሬ ያ ቸዋለሁ የሚ ላቸው ኢትዮጵያውያ ን የ ህግ ታራሚዎች ሳይ ቀሩ በ እርዳታው ተሳትፎ ማድረጋቸው ን አመልክ ቷል',\n", - " 'tr_769_tr08069': 'የ ኦክስፋም ኢንተርናሽናል ልኡካን ቡድን ን በ መወከል የ ካናዳ ኦክስፋም ዳይሬክተር ሚስ ጆ አን እንደ ተናገሩት አባል ድርጅቶች ችግሩ ን በ ቅንጅት ለ መቅረፍ የ ተቻላቸውን ጥረት ያደርጋሉ',\n", - " 'tr_770_tr08070': 'በ ተለያዩ የ ሀገራችን ክፍሎች ውስጥ እንግልት ድብደባ ግድያ ና እስራት ተፈጸመባቸው ያ ላቸውን የ አማራው ተወላጆች ን ስ ም ዝርዝር አውጥ ቷል',\n", - " 'tr_771_tr08071': 'በ አደባባይ ም ባሪያዬ ነው እያ ልክ አት ሟገት',\n", - " 'tr_772_tr08072': 'የ ውጪ ጋዜጠኞች ወደ ውጊያ ግንባር እንዲ ሄዱ ተፈቀደ',\n", - " 'tr_773_tr08073': 'አባቶቻችን እንደሚ ተርቱ ት የ እንጨት ምንቸት እራሱ አይድ ን በ ውስጡ ም ያለውን አ ያድኑ ብለዋል',\n", - " 'tr_774_tr08074': 'እራሳቸው ን ወደ ገዢ መደብ ያ ሸጋገሩ ስለሆነ ለዚህ አዲስ መደባዊ ጥቅማቸው ሲሉ ነው',\n", - " 'tr_775_tr08075': 'በ ድርጅት ማእከላዊ ኮሚቴ ውስጥ ምልአተ ጉባኤ በሚ ታጣበት ጊዜ መ ኬድ ያለበት ወደ ኦዲት ኮሚሽን ነው',\n", - " 'tr_776_tr08076': 'የ ጦማር ዘጋቢ ትናትና ተዘዋው ሮ የ ተመለከታቸው ን ሁኔታዎች እንደሚ ከተለው ገልጿ ል',\n", - " 'tr_777_tr08077': 'ጋዜጦቹ በተለይ በውጭ አገር ያሉ ኢትዮጵያውያ ን ን በ ማስተባበር በኩል ትልቅ ሚና ተጫውተ ዋል',\n", - " 'tr_778_tr08078': 'ፎረሙ በ ዋሽንግተን ለ ስድስት ቀናት በሚ ያደርገው ሁለተኛ ስብሰባ ላይ ሀያ ኢትዮጵያውያ ን ተ ጋብዘው በ መካፈል ላይ ናቸው',\n", - " 'tr_779_tr08079': 'ሰብ ላቸው ረክ ሶ የሚ ገዛቸው እያ ጡ ነው በ ማለት ከ ገለጹ በኋላ እኛ ጥያቄ ያችን ና ተቃውሟችን የ ደህንነት ና የ ዋስትና ጥያቄ ነው',\n", - " 'tr_780_tr08080': 'በ ስደት ያሉት ተማሪዎች መምህራኖ ቻቸውን አድር ባዮች ሲሉ መኮነናቸው ንም መረዳት ተችሏል',\n", - " 'tr_781_tr08081': 'ምርጥ የ ኢትዮጵያ ልጆች ተሰኙ',\n", - " 'tr_782_tr08082': 'የ ኢትዮጵያ የ ታሪክ ጥበቃ ክፍል ና የ ኢትዮጵያ ቱሪስት ኮሚሽን ለዚህ ጥንታዊ ና ታሪካዊ ቦታ ና መስጊድ ትኩረት ሊሰጥ እንደሚ ገባ ለማስታወስ እንወዳ ለ ን',\n", - " 'tr_783_tr08083': 'በ ማእረጉ ማግኘት የሚ ገባቸው ን የ ደሞዝ ጭማሪ እና እድገት አግኝተ ዋል',\n", - " 'tr_784_tr08084': 'የ ተጫዋቹ ጤንነት ሙሉ ለ ሙሉ ጥሩ እንደሆነ ዶክተሩ ገልጸው ላቸው ለ ሮናልዶ ም ከ እንግዲህ ጥሩ እረፍት እንደሚ ያስፈልገው ይ ነገረ ዋል',\n", - " 'tr_785_tr08085': 'ቦሎኛ ባለፈው ሳምንት ጁቬንትስ ን ሶስት ለ ዜሮ በሆነ ሰፊ ውጤት አሸን ፏል',\n", - " 'tr_786_tr08086': 'ይህን አስተያየት የሚሰጡ ወገኖች ስለ ሙያው ም ንም እውቀት ና ግንዛቤ የ ሌላቸው ናቸው',\n", - " 'tr_787_tr08087': 'ሁለተኛው ከ ስፖርት ሚኒስቴሩ ፕሮጀክት ጋር በ እግር ኳስ እድገት ላይ ያደረግ ነው ስራ ነው',\n", - " 'tr_788_tr08088': 'ወዲያ ው ጣልያኖች ፔናልቲ ሊ ስቱ ችለዋል ና',\n", - " 'tr_789_tr08089': 'እስካሁን ኢትዮጵያ ወደ አንድ መቶ ሺ የሚሆኑ የ ሶማሊያ ስደተኞች ን በ ማስተናገድ ላይ ትገኛ ለች',\n", - " 'tr_790_tr08090': 'ከ ሞት የተ ረፍ ን አራት ወንድማማቾች ታፍ ነናል እስከ ሚቀጥለው ቀጠሮ ላንደር ስ እንችላ ለ ን ልን ሞት እንችላ ለ ን',\n", - " 'tr_791_tr08091': 'ግም ታችን ግን ትክክል ሆኗል',\n", - " 'tr_792_tr08092': 'ያኛው ቡድን ትራዲሽና ሊስት ነው',\n", - " 'tr_793_tr08093': 'እንግዲህ ደደቢቶች አብዮታዊ ዲሞክራሲ ን አንግ በ ው ብሄርተኝ ነትን አ ራምደው ኢምፔሪያሊዝም ን ሸውደው እጣ ፋንታ ቸው አስራ ሰባት አመት የ ዳ ከርን በትን ርእዮት በ ኦሞ ከ ማጽዳት አያልፍ ም',\n", - " 'tr_794_tr08094': 'ምክንያቱ ም የምን ጋራ ቸውን ግቦች የምናከብራቸው ን ብሄራዊ እ ሴቶች ተገንዝበ ን ተገንዝበ ው ለ ተፈጻሚ ነታቸው ፈቃደኞች መሆናችን ን እስካሁን አላ ረጋገጥ ንም',\n", - " 'tr_795_tr08095': 'ብቻ ሰዎቹ ን አስሮ ማቆየት ፈልጓል',\n", - " 'tr_796_tr08096': 'ኤርትራ የ አድኑ ኝ ጩኸት እያስ ተጋባች ነው',\n", - " 'tr_797_tr08097': 'ዜናው አክሎ እንደ ገለጸው የኤርትራ ተወላጆች የ ተጠቀሱት ን ንብረቶች ና እንስሳት እንዳያ ሸጋግሩ ቢ ታገዱ ም ንብረታቸው ን ሸጠው በ ገንዘብ መልክ ይዘው ለ መውጣት ግን አልተ ከለከሉ ም',\n", - " 'tr_798_tr08098': 'ሲፒጄ ዘንድሮ ም መለስ ዜናዊ ን የ ፕሬስ ጠላት አ ላቸው',\n", - " 'tr_799_tr08099': 'በ ኢትዮጵያ ያለው የ ሀይማኖ ቶች መቻቻል እንደ ምሳሌነት እንደሚ ጠቀስ ተጠቆመ',\n", - " 'tr_800_tr08100': 'ማ ንም እንደሚ ያውቀው ሮናልዶ አለ',\n", - " 'tr_801_tr09001': 'ነገር ግን በ ሁሉም መስክ ተቀባይነት ያለው የ ኮምፒውተር ቴክኖሎጂ ነው',\n", - " 'tr_802_tr09002': 'በ አሜሪካ ዋሽንግተን ና ኒውዮርክ በ ኬንያ ናይሮቢ ና በ ታንዛኒያ ዳሬሰላም በ ሽብርተኝነት የተ ፈጸሙት ን ጥቃቶች ም እንደሚ ያወግዙ ት መሪዎቹ ባሳለፉ ት ውሳኔ አመልክ ተዋል',\n", - " 'tr_803_tr09003': 'በ ሚስተር ኬን ዞ ኦ ሾማ የተ መራው የ ተመድ የ ልኡካን ቡድን አዲስ አባ ገባ',\n", - " 'tr_804_tr09004': 'በ ጅቡቲ ኢትዮጵያውያ ን ሹፌሮች ግልምጫ ና ቁጣ እንዳይደርስ ባቸው በ ፈገግታ ና በ እንግዳ ተቀባይነት ጸባይ ተ ቀበሏቸው ሲሉ ኢትዮጵያውያ ን ባለስልጣናት ጅቡቲ ያውያን ባለስልጣናት ን አ ሳሰቡ አሉ',\n", - " 'tr_805_tr09005': 'ዳንኤል ና ስለ ስቱ ደቂቅ ደግሞ በ ጾም ትምህርት ን ጥበብ ን እውቀት ን ማስተዋል ን አግኝተ ዋል',\n", - " 'tr_806_tr09006': 'ሶስቱ ሊቃነ ጳጳሳት በ ሲኖዶሱ ጉባኤ እንዳይ ቀመጡ እየተ ዶ ለተ መሆኑ ተነገረ',\n", - " 'tr_807_tr09007': 'በ አፍሪካ አንድነት ድርጅት አደራዳሪ ነት የ ተዘጋጀው የ ስምምነት ማእቀፍ በ ኢትዮጵያ ና በ ኤርትራ ተቀባይነት ማግኘቱ እንደሚ ደገፍ ፕሬዚደንት ክሊንተን አስ ታወቁ',\n", - " 'tr_808_tr09008': 'ጠንክረን ስለምን ታገ ላችው ም የ ጥቃታቸው ን ኢላማ እንደሆ ን ን እናውቃለን',\n", - " 'tr_809_tr09009': 'አመት አልፎ አመት በ ተተካ ቁጥር ፓትርያርኩ ና ተቃውሞ ተለያይ ተው አያውቁ ም',\n", - " 'tr_810_tr09010': 'ምክንያቱ ም ኢሳያስ የ ኢትዮጵያ ን ምድር ለቀው እንዲ ወጡ ከ መጨነቅ ይልቅ ሱዳን ገብተው አልቱራቢ ን እንዴት ሊ ያጠፉ ላቸው እንደሚ ችሉ ነው የሚያ ልሙት',\n", - " 'tr_811_tr09011': 'ሁለት ኢትዮጵያውያ ን አርቲስቶች የ ዩኤስ ፌሎው ሺፕ አሸናፊ ሆኑ',\n", - " 'tr_812_tr09012': 'አቶ ተወልደ እኔ ትናንት ስላል ነበርኩ ኦዲት ኮሚሽን ትናንት ያቀረበ ው ሀሳብ ም ን እንደሆነ እንዲ ገለጽ ልኝ እፈልጋ ለሁ አሉ',\n", - " 'tr_813_tr09013': 'ተመላሽ ኢትዮጵያውያ ን ስለሚያ ስገቧቸው ቁሳቁስ የ ተሻሻለ መመሪያ ወጣ',\n", - " 'tr_814_tr09014': 'ሁለተኛው ላቁኦተ ለ አደላዳይ ራቁኦ ተ ይላሉ አደላዳይ እሳቸው ናቸው',\n", - " 'tr_815_tr09015': 'የ ኢትዮጵያ ብሄራዊ የ እግር ኳስ ቡድን ን እንዲ ያሰለጥኑ የተመረጡት ሚስተር ስኮቺቭ ባለፈው ቅዳሜ አዲስ አበባ ገብ ተዋል',\n", - " 'tr_816_tr09016': 'ለ ሜዳይ ና ሪቫ ን ኮሚቴ ቅርብ ከ ሆኑ ወገኖች የተገኘው መረጃ እንደሚ ያስረዳ ው አንድ የ አገልግሎት ሪቫ ን ማለት አምስት የ አገልግሎት አመታት ን ይወ ክላል',\n", - " 'tr_817_tr09017': 'እኛ በ ፓርላማው የተቀ መጥነው እ ኮ ተቃዋሚዎች ን ወክለ ን እንጂ የ ኢህአዴግ እጩዎች ሆነ ን አደለ ም',\n", - " 'tr_818_tr09018': 'የ ኢትዮጵያ መንግስት ብሄራዊ ፓሊሲ ዎቹን ህግ ና የ ስደተኞች ስራ አመራር መዋቅሮቹ ን እንደ ገና በ መፈተሽ ና በ ማሻሻል ለ ኢትዮጵያ ስደተኞች የሚ ጠቅም አሰራር እንዲ ዘረጋ ተጠየቀ',\n", - " 'tr_819_tr09019': 'ይህን እኛ አንስተው ም ሀ ዜብ ዛሬ እንደ ፈለገች የምታ ሽክረ ክረው ድርጅት ና ክልል እንዳገኘ ች ማለት ነው',\n", - " 'tr_820_tr09020': 'ባንኩ ይህን ብድር ለግል ባንኮቹ የ ሰጠው የ ጥሬ ገንዘብ ችግራቸው ን እንዲ ቋቋሙ ለ መርዳት ነው',\n", - " 'tr_821_tr09021': 'ከ ኢትዮጵያ ወታደሮች ጋር እንዋጋ ለ ን',\n", - " 'tr_822_tr09022': 'ሱዳን ይኖሩ የነበሩ አራት መቶ ሰባ አምስት ኢትዮጵያውያ ን ስደተኞች ጐንደር ገቡ',\n", - " 'tr_823_tr09023': 'ኤም ቢ ሲ የ ሚባለው ና ከ ለንደን የሚ ተላለፈው ቴሌቪዥን ጣቢያ ባለፈው ቅዳሜ አል ከ ሊድ መጽሄት ን ጠቅሶ እንደ ዘገበው የኤርትራ ተቃዋሚዎች በ ፕሮፖጋንዳ ብቻ የተ ገደቡ አይ ሆኑ ም',\n", - " 'tr_824_tr09024': 'የተገኘው ዜና እንደሚ ያስረዳ ው የ ወረዳው ፖሊሶች ወደ ተጠቃሹ ቦታ እንዲ መጡ ህዝቡ አስቀድሞ መረጃ ደርሶ ት ነበር',\n", - " 'tr_825_tr09025': 'የ ኢትዮጵያ ን አንድነት እንደ ገና መመለስ ይቻላል',\n", - " 'tr_826_tr09026': 'እነሱ ኢትዮጵያውያ ን መንግስቱ ን በ ጦር ወንጀለኛ ነት ማየት ይችላሉ',\n", - " 'tr_827_tr09027': 'በ ባህሬን የ ሀያ አመት ኢትዮጵያዊ ት ላይ የ ሞት ፍርድ ተፈረደ ሁለቱ ም ኢትዮጵያዊ ድምጹ ን ሊያ ሰማ ይገባል',\n", - " 'tr_828_tr09028': 'ምክንያቱ ስውር ቢሆን ም ተማጽ ኗቸው ን በ ቅን መንፈስ ለ መመለስ ሳይ ስማሙ ቀሩ',\n", - " 'tr_829_tr09029': 'ጸጥ እንድት ል አስ ጠንቅቆ አስገድዶ ደፈራት',\n", - " 'tr_830_tr09030': 'ግን ዘንድሮ ራሱ ስንት እንዳ ገባሁ አላ ቀውም',\n", - " 'tr_831_tr09031': 'በ እውነት ነው የ ም ልህ እሱ እውነተኛ ፕሮፌሽናል ስራው ን አክባሪ ነው',\n", - " 'tr_832_tr09032': 'እንዲያ ውም እኛ ስህተት አድርገ ናል',\n", - " 'tr_833_tr09033': 'ረጅም መንገድ እንዲ ጓዝ የሚ ያስችለው ችሎታ አለ ው',\n", - " 'tr_834_tr09034': 'በ ሊቢያ ው መሪ ስ ም ማለት ነው',\n", - " 'tr_835_tr09035': 'ቦታው እ ኮ ከባድ ነው',\n", - " 'tr_836_tr09036': 'አቶ ጸሀዬ ከ ችሎታቸው ና ከ እ ው ጥቀ ታቸው በላይ የ ተሰጣቸው ን ሀላፊነት እንዲ ወጡ ውክልናው ን የ ሰጠው የ ትግራይ ስፖርት ኮሚሽን ነው',\n", - " 'tr_837_tr09037': 'በተለይ ረዳት አርቢትሮች የሚፈጽሟቸው ስህተቶች የ ጨዋታው ው በት እንዳ በላሹት በ ተመልካቹ አንደ በት ሲ ነገር ተደም ጧል',\n", - " 'tr_838_tr09038': 'የ ኢትዮጵያ መንግስት በ ነጻ ቢያሰ ና ብተው ወንጀል የ ተፈጸመባቸው ቤተሰቦች ተቃውሟቸው ን ሊ ያቀርቡ ይችላሉ',\n", - " 'tr_839_tr09039': 'ለ መስሪያ ቤታቸው ይህን ምክንያት ያቅርቡ እንጂ ዳግመኛ ወደ ኢትዮጵያ እንደማይ መለሱ ለሚ ያቀርቧቸው ወገኖች በ ሚስጥር ገልጸው ነበር',\n", - " 'tr_840_tr09040': 'ግብ ጠባቂ ው የሚ ደነቅ ነው',\n", - " 'tr_841_tr09041': 'ኤሲ ሚላን ሀያ አምስት ኢንተር ሚላን ሀያ አራት ሮማ ላዚዮ ሀያ ሰባት ቦሎኛ ና ጆ ቪ ሀያ አንድ ነጥብ አ ላቸው',\n", - " 'tr_842_tr09042': 'የመጀመሪያ ውን ጐል በረኛው ሲ ተፋ ደርሶ ያገባ ሲሆን ሁለተኛ ዋን ግን ተከላካዮቹ ን አብዶ ሰርቶ ነው ያገባ ው',\n", - " 'tr_843_tr09043': 'የ ኢትዮጵያ ጦር ማክሰኞ እ ለት የ ሶማሊያ ሁለት ከተሞች ን ያዘ',\n", - " 'tr_844_tr09044': 'ኬንያ ወደ ኢትዮጵያ ድንበር ሰራዊቷ ን ላከች',\n", - " 'tr_845_tr09045': 'አባቱ የ ፕሮቴስታንት እምነት ቄስ ነበሩ',\n", - " 'tr_846_tr09046': 'አሜሪካ ዲፕሎማቶ ቿ ወደ ኢትዮጵያ እንዲመለሱ ወሰነች',\n", - " 'tr_847_tr09047': 'ተማሪዎቹ እንደሚ ናገሩት ምግብ በ ሰአቱ አይ ሰጣቸው ም',\n", - " 'tr_848_tr09048': 'እነሱ በ ባዶ እግራቸው መጥተው ዛሬ ባለ ማርቸዲስ ናቸው በ ቁምጣ መጥተው ዛሬ ሚሊ የ ነሮች ናቸው',\n", - " 'tr_849_tr09049': 'ሶማሊያ በ ኢትዮጵያ ላይ ማእቀብ እንዲ ጣል ጠየቀች',\n", - " 'tr_850_tr09050': 'ባ ሁኑ ወቅት አቶ ሰ ዬ ከ ታሰሩበት ክፍል ማ ንም ሰው እንደማያ ያቸው ምንጮቻችን አክለው ገልጸዋል',\n", - " 'tr_851_tr09051': 'ኢትዮጵያ ና ኤርትራ የ ሰራዊት ቅነሳ ለማድረግ እንቅስቃሴ እንደ ጀመሩ በ መንግስታቱ ድርጅት የ ኢትዮ ኤርትራ ልዩ ልኡክ አስ ታወቁ',\n", - " 'tr_852_tr09052': 'ዛሬ ያ መልካም ጉርብትና ና ትስስር ታሪክ ሆነ',\n", - " 'tr_853_tr09053': 'ዛሬ ም ልክ እንደ ትናንቱ እያ ና ቆረ እያ ና ከሰ እያ ራኮተ ነው',\n", - " 'tr_854_tr09054': 'አንድ ኢትዮጵያዊ ልጅ ዎ ሊ ጠይቅ ዎት መጥቶ ነበር',\n", - " 'tr_855_tr09055': 'ኢህአፓ ዎች ሊ ገደሉ ሲ ሄዱ እየ ዘመሩ እንደ ሄዱ ነገሩኝ',\n", - " 'tr_856_tr09056': 'ያረፈ በት ምክንያት ከ ወዲያ ከ ኤርትራ ሚጐች ወጥ ተዋል ተብሎ ነው',\n", - " 'tr_857_tr09057': 'በ ትግራይ ውስጥ ከ ባድመ ጀምሮ ደደቢት ን ጓል ደደቢት ን ሸራሮ ን ወሀ ደን በ ሙሉ እስከ መ ንጠባጠብ ያለውን ይይዛ ል',\n", - " 'tr_858_tr09058': 'ሰዎች ና ድርጅቶች ከ እነሱ ም ጋር የ ተያያዙ ፖሊሲዎች አላፊ ዎች ናቸው',\n", - " 'tr_859_tr09059': 'አዘጋጅ ኮሚቴው ለ ሪፖርተራችን እንደ ገለጸው ዝግጅቱ ን ከ ተለያዩ የ አሜሪካ ግዛቶች የሚ መጡ ኢትዮጵያውያ ን ይ ስተናገዱ በታል',\n", - " 'tr_860_tr09060': 'የ ሀገራችን ቁስል ም እንዲ ሽር ያደርጋሉ',\n", - " 'tr_861_tr09061': 'መንግስት በ ኢንቨስትመንት እንቅስቃሴ ላይ የ ተከሰቱ የ ፖሊሲ ና የ አሰራር ግድፈቶች ን ለ ማስወገድ ርምጃ መውሰዱ ከ ግሉ ኢንቨስትመንት ፍሰት የ ሚገኘው ን ድርሻ እንደሚያ ሻሽለው ም ገለጹ',\n", - " 'tr_862_tr09062': 'እኔ ግን ነፍጠኛ ም መድፈኛ ም እንዳል ሆ ኩኝ ልንገራችሁ ብዬ እንጂ ፖለቲከኛ ሳል ሆን አሽሙረኛ ነኝ ብዬ እናንተ ን አ ላሳምናችሁ አል ሞክር ም',\n", - " 'tr_863_tr09063': 'ኮሎኔል በዛብህ ጴጥሮስ የ አማራጭ ሀይሎች ሊቀመንበር የ ዶክተር በየነ ጴጥሮስ ወንድም መሆናቸው ተያይዞ ተ ገልጿ ል',\n", - " 'tr_864_tr09064': 'የ መስተዳድሩ መግለጫ ከተማዋ ስር ነቀል ለውጥ እንደሚ ያስፈልጋት ገልጾ ህዝቡ በዚህ እንዲ ሳተፍ ቢ ጠይቅ ም ጊዜያዊ መስተዳድሩ የ መዋቅር ለውጡ ን ያስፈጽማል ተብሎ አይጠበቅ ም',\n", - " 'tr_865_tr09065': 'ለወደፊቱ በሚ ዘጋጀው ጉባኤ የ በ ኩሌን ሀሳብ ለ ካድሬው ይዤ እ ቀር ባለሁ',\n", - " 'tr_866_tr09066': 'ኤኤፍፒ ከ ሶስት ሺ በላይ የኤርትራ ኩናማ ዎች ወደ ኢትዮጵያ ሸሽተው በ መግባት የኤርትራ ሰራዊት በ ሀይል እየ መለመላቸው ነው ሲሉ ውንጀላ ሰንዝ ረዋል',\n", - " 'tr_867_tr09067': 'ዋናው አላማችን አባላ ቶቻችን በ ስፖርቱ ተሳታፊ እንዲሆኑ ና ለ ሀገራችን ስፖርት የ በኩላቸው ን አስተዋጽኦ እንዲ ያበረክቱ እንጂ እንደ አንዳንድ ክለቦች ድርጅት ን ለ ማስተዋወቅ አይደለም',\n", - " 'tr_868_tr09068': 'በ ማጠቃለያ ውም በ እርዳታ አ ሰባሰቡ ወቅት ኢህአዲግ በ በጐ አይ ን የማ ይመለከታቸው ና በ አሸባሪነት ጠርጥሬ ያ ቸዋለሁ የሚ ላቸው ኢትዮጵያ ን የ ህግ ታራሚዎች ሳይ ቀሩ በ እርዳታው ተሳትፎ ማድረጋቸው ን አመልክ ተዋል',\n", - " 'tr_869_tr09069': 'በ የመን ግዛቶች ውስጥ ም ሀያ ቅርንጫፍ ጽህፈት ቤቶች ማቋቋሙ ን ተናግረ ዋል',\n", - " 'tr_870_tr09070': 'ስልጣን ኦጋዴን ን ለማስ ገንጠል ለሚ ሹ ወገኖች ሊሰጥ ነው',\n", - " 'tr_871_tr09071': 'እኔ ና እናንተ መገናኛ የ ለ ንም',\n", - " 'tr_872_tr09072': 'የቤተ ክርስቲያን ሀብት እንዳይ ባክን ስልት ተ ቀየሰ',\n", - " 'tr_873_tr09073': 'ስለዚህ በ አር እስቴ እንደ ገለጽኩ ት ሰሚ ጆሮ ያለው ይስማ አስተዋይ አእምሮ ያለው ም ያስተውል እ ላለሁ',\n", - " 'tr_874_tr09074': 'ካድሬው እነዚህ ን ውይይቶች ሊ ወያይ ባቸው ይገባል',\n", - " 'tr_875_tr09075': 'ካለ ፍርድ ቤት ውሳኔ መስሪያ ቤቶቻችን ን ለ መፈተሽ ና ለ ማሸግ ፖሊስ ና ደህንነት ን አሰማር ተዋል',\n", - " 'tr_876_tr09076': 'ሪፖርተራችን ያ ነጋገራቸው ተማሪዎች እንደ ገለጹት ወደ ሰንዳፋ ፖሊስ ማሰልጠኛ ስን ገባ በ ፖሊሶች ላይ የሚ ታየው እልክ ና ቁጭት ነበር',\n", - " 'tr_877_tr09077': 'የ ትግራይ ነዋሪ ቁጣው ን እየ ገለጸ ነው',\n", - " 'tr_878_tr09078': 'አረጋሽ የ ባንክ አካውንት እንዲ ያስረክቡ ተጠየቁ',\n", - " 'tr_879_tr09079': 'የ ተማሪዎቹ ተወካዮች ከ ኦሮሚያ ባለስልጣናት ጋር አምስት ሰአት የፈጀ ውይይት ማድረጋቸው ታውቋል',\n", - " 'tr_880_tr09080': 'ወይዘሮዋ ም በ አምባሳደር ነት ሊ ሾሙ ነው የሚ ል ፍንጮች ም እየ ተደመጡ ነው',\n", - " 'tr_881_tr09081': 'ዶክተር ታዬ ወልደሰማያት አውሮፓ እያሉ ጽፈት ቤትዎ እየ ተፈተሸ ነው',\n", - " 'tr_882_tr09082': 'ወንዶች ና ሴቶች እኩል ሳይ ሆኑ ተደጋጋፊ ዎች ናቸው',\n", - " 'tr_883_tr09083': 'አንዳንዶቹ ም የ ብሄራዊ ውትድርና ስልጠና የ ወሰዱ ናቸው',\n", - " 'tr_884_tr09084': 'አሰልጣኙ ም በ ጉዳዩ ማብራሪያ ሲሰጡ ዋናው ትኩረ ቴ የ ሮናልዶ ን ተክለ ሰውነት ማስተካከል ነው ብለዋል',\n", - " 'tr_885_tr09085': 'ላዚዮ እንዲ ሁ ፕሮቲ ን ን በ ው ሰት ለ ሬጂ ያ ና ክለብ ሰጥ ቷል',\n", - " 'tr_886_tr09086': 'ማሸነፍ ንና መሸነፍ ጠንቅ ቄ አውቀ ዋለሁ',\n", - " 'tr_887_tr09087': 'ሶስተኛው በ ታዳጊ ፕሮጀክቶች ላይ ያተኮረ ነበር',\n", - " 'tr_888_tr09088': 'ፈረንሳይ ውስጥ የሚ ጫወተው የ ኮትዲቭዋር ኢብራሂም ባካዮኮ ያለው ፐርፎርማንስ ከ እ ለት ወደ እ ለት ልዩ እየ ሆነ ይገኛል',\n", - " 'tr_889_tr09089': 'በ እለቱ ተጋባዥ ተናጋሪዎች ዶክተር ማሞ ሙጬ ና ዶክተር ግርማ ይ ስለ ኤርትራ ና ኢትዮጵያ የፖለቲካ ና የ ኢኮኖሚ ውስብስብ ችግሮች በስፋት አብራር ተዋል',\n", - " 'tr_890_tr09090': 'ፖሊስ የተለያዩ ክሶች ን ሊያመጣ ይችላል',\n", - " 'tr_891_tr09091': 'የ ዴር ሱልጣን ገዳም የ ባለቤትነት ጥያቄ ግብጽ ን ኢትዮጵያ ንና እስራኤል ን እያ ነታረ ከ ነው',\n", - " 'tr_892_tr09092': 'ምክንያቱ ም እነሱ ም እራሳቸው እንቅ ሳቄ ሳችን ተገድ ቧል ግንኙነታችን ተዳክ ሟል እያሉ ነው',\n", - " 'tr_893_tr09093': 'ገንዘብ ሲ ያዋጡ እጅ ከፍ ን ጅ የተያዙ ና በ ስለላ ስራ የተሰማሩ የኤርትራ ዜጐች እየ ተያዙ ወደ ሀገራቸው ሊ ባረሩ ነው',\n", - " 'tr_894_tr09094': 'ከዚህ በኋላ ነው እነዚህ ትሮትስኪ ን ያጠፉ ለትን አብዮተኞች በሌላ ስልት የ ዞረ ባቸው',\n", - " 'tr_895_tr09095': 'ታሳሪዎቹ ም ወደ ምርመራ ማስተባበሪያ እስር ቤት ተመለሱ',\n", - " 'tr_896_tr09096': 'ከርሞ ጥጃ አድሮ ቃሪያ ነን',\n", - " 'tr_897_tr09097': 'ከ ኢትዮጵያ የተለያዩ ሸቀጦች ጭነው ወደ ኤርትራ ይጓዙ የነበሩ በመቶ ዎች የሚ ቆጠሩ ካሚዮኖች በ ራማ ና ዛላንበሳ በሮች እንደ ተ ኮለኮሉ ናቸው',\n", - " 'tr_898_tr09098': 'ለ ኛ የ ጥንት የ ጠዋቱ የ አባቶቻችን ባንዲራ ያለው የ ቃል ኪዳን አርማ ችን ነው',\n", - " 'tr_899_tr09099': 'በ ኢትዮጵያ ና በ ቻይና መካ ካል ያለውን ወዳጅነት የሚ ያጠናክር ስምምነት ተፈረመ',\n", - " 'tr_900_tr09100': 'ኤቨርተን ደግሞ እኔ የ ም ወደው ክለብ ነው',\n", - " 'tr_901_tr10001': 'ብዙ ነገሮች ን ማገናዘብ ይፈልጋል',\n", - " 'tr_902_tr10002': 'ተሳታፊ ዎቹ በ ውይይቱ ላይ እንደ ተናገሩት እንደ ማንኛውም አገር ሁሉ በ ኢትዮጵያ ለ ባለስልጣናት የሚ ከፈለው ክፍያ ከ ገበያ ዝቅ ያለ ነው',\n", - " 'tr_903_tr10003': 'የ ፖሊዮ ቫይረስ እንዳለ ባቸው በ ታወቁ በ እነዚህ አካባቢዎች የ ጤና ባለሙያዎች የ ቤት ለ ቤት ክትባት ለ መስጠት ለ ሚያደርጉት እንቅስቃሴ እንደሚ ያግዝ ገልጸዋል',\n", - " 'tr_904_tr10004': 'ም ነው አሽሙረኛ ው ስለ ሽያጭ ና ስለ ዱቤ ማውጋት አበዛ',\n", - " 'tr_905_tr10005': 'እንዲሁም የ ቀደሙ ነገስታት ና መኳንንት አገር የሚ ያስተዳድሩ በት ህሊናቸው ማስተዋል ን ጥበብ ን እንዳ ያጣ በ ጾመ ፍልሰታ ወደ እመቤታችን ቀርበው የሚ ማጸኑ በት ነው',\n", - " 'tr_906_tr10006': 'ሀሰን አልቱራቢ ወደ ስራቸው እንዲመለሱ የ ሱዳን ፓርላማ ማስ ገደዱ ታወቀ',\n", - " 'tr_907_tr10008': 'የበለጠ የ ጥ ፈት መልእክተኞች ን ለ ማጥፋት እንድን ተጋ ያደርገ ናል',\n", - " 'tr_908_tr10009': 'የ ኢትዮጵያ ተዋጊ አውሮፕላኖች አብራሪዎች ራሺያ ኖች ነበሩ',\n", - " 'tr_909_tr10010': 'ኤርትራ ን አውግዘ ው ኢትዮጵያ ን ከ ደገፉ አገሮች ም ጋር ተደ ባለቁ',\n", - " 'tr_910_tr10011': 'ሱዳን የ ኢትዮጵያ ዲፕሎማሲ ያዊ ውክልና ወደ አምባሳደር ደረጃ እንዲ ያድግ ጠየቀች',\n", - " 'tr_911_tr10012': 'ስለዚህ ትናንት የተባለ ውን ማወቅ እ ፈለጋ ለሁ',\n", - " 'tr_912_tr10013': 'በውጭ አገር እንዳሉ የሚ ሞቱ ኢትዮጵያውያ ን ህጋዊ ወራሾች ም የሟቾ ቹ መብቶች እንዲ ጠበቅ ላቸው መመሪያው ያዛል',\n", - " 'tr_913_tr10014': 'ሶስተኛው ላቁኦተ ለ እኔ ራቁኦ ተ ይላሉ እሳቸው እሳቸው ናቸው',\n", - " 'tr_914_tr10015': 'ኢትዮጵያ ቡና በ ብርሀን ና ሰላም ሶስት ለ አንድ ተረ ቷል',\n", - " 'tr_915_tr10016': 'እነ ኩማ ደመቅሳ ስ ልኮ ቻቸውን ተነጠቁ',\n", - " 'tr_916_tr10017': 'ጄኔራሎች በ ጠክለይ ሚንስትር ቢሮ ተሰብስ በዋል',\n", - " 'tr_917_tr10018': 'ቢል ጌት ስ ለ ኢትዮጵያ ሰባት ሚሊዮን ዶላር ለገሱ',\n", - " 'tr_918_tr10019': 'በ አንዱ ክስ ሰባት ተከሳሾች ያሉበት ነው',\n", - " 'tr_919_tr10020': 'መለስ ዜናዊ የ ሚኒስትሮች ሹም ሽር ሊያደርጉ ነው',\n", - " 'tr_920_tr10021': 'ስለሆነ ም ኤርትራውያን ወዳጆቻችን ናቸው',\n", - " 'tr_921_tr10022': 'ይህንኑ የ ገንዘብ ሽልማት በ ስጦታ ያበረከቱ ት የ ኢትዮጵያ ፈዴራላዊ ዴሞክራሲያዊ ሪፐብሊክ ፕሬዝ ደን ት ዶክተር ነጋሶ ጊዳዳ ናቸው',\n", - " 'tr_922_tr10023': 'የ አረብ ሊግ ኢትዮጵያ ን አወ ገዘ',\n", - " 'tr_923_tr10024': 'የ ሌሎች መንግስታዊ መስሪያ ቤቶች እንቅስቃሴ ም ተዳክ ሟል',\n", - " 'tr_924_tr10025': 'የ ሻእቢያ እብሪተኛ ቡድን የ ኢትዮጵያ ን ግዛት ዘልቆ ገብቷል',\n", - " 'tr_925_tr10026': 'ኤርትራ የ ማባረር ዘመቻ እንደምት ጀምር ገለጸች',\n", - " 'tr_926_tr10027': 'ከውጭ የ መጡ ስልሳ ኢትዮጵያውያ ን መለስ ን ሊያናግሩ ነው',\n", - " 'tr_927_tr10028': 'አባት ደግሞ አባት ናቸው ና ከ ሀገር ሽማግሌ ጋር መክረው ልጅቱ ን እንዲያ ገባት ተማመኑ',\n", - " 'tr_928_tr10029': 'ረዳት ቧንቧ ጠጋ ኝ ነው',\n", - " 'tr_929_tr10030': 'ገና ብዙ ጐል እንደማ ገባም አውቀ ዋለሁ',\n", - " 'tr_930_tr10031': 'እንደሚ ታወቀው ስብስቡ ከ ተለያየ የ ትውልድ ቦታ የተገኘ ነው',\n", - " 'tr_931_tr10032': 'እንዴ ም ን እያሉ ነው ኢንሴንቲቭ እ ኮ የሚ ታሰብ ላቸው በ የ ጨዋታው ና ባ ሸነፉ ቁጥር ነው',\n", - " 'tr_932_tr10033': 'ም ን እንደሚ ሰማው በ ደንብ አውቀ ዋለሁ',\n", - " 'tr_933_tr10034': 'በ መጀመሪያ ዎቹ አስራ ስድስት ጨዋታዎች ሶስት ብቻ ነው ያሸነፉ ት',\n", - " 'tr_934_tr10035': 'አሁን ትንሽ ከ እ ለት ወደ እ ለት እየ ተሻለኝ ነው',\n", - " 'tr_935_tr10036': 'ስለ እኚሁ የ ኢትዮጵያ ፉትቦል ፌዴሬሽን ምክትል ፕሬዚደንት የ ሁለት አመት የ ስልጣን ዘመን ብዙ ብዙ ተ ብሏል',\n", - " 'tr_936_tr10037': 'ፖሊሲው ን ተግባራዊ ለማድረግ እንዲ ያስችል የ ስፖርት ኮሚሽን ሙያተኞች ወደ ተለያዩ ክልሎች በ መዘዋወር መግለጫ ሰጥተዋል',\n", - " 'tr_937_tr10038': 'በ ወር ሶስት መቶ ዶ ራል ለ ሻምበል ማሞ ወልዴ ባለቤት ለ ወይዘሮ አበራሽ ኢንተርናሽናል ኦሎምፒክ ኮሚቴው እንደሚ ልክ ባገኘ ነው መረጃ ለማወቅ ች ለናል',\n", - " 'tr_938_tr10039': 'ባለፈው እትማችን ላይ የ ኢትዮጵያ አትሌቲክስ ፌዴሬሽን የ ፋይናንስ ና የ አስተዳደር ሀላፊ የሆኑት ወይዘሮ ፍቃደ ተገኝ ለ እረፍት ወደ አውሮፓ መጓዛቸው ን መግለጻ ችን አይ ዘነጋ ም',\n", - " 'tr_939_tr10040': 'ቀደም ሲል የ ፈጸማቸው ን ስህተቶች እንዳይ ደግም ና እርም ት እንዲያደርግ የሚ ገስጸው ሀይል ካልተገኘ ወደፊት ም በ ማወቅ ወይም ባለ ማወቅ ከ ስህተት የ ጸዳ ሊሆን አይችልም',\n", - " 'tr_940_tr10041': 'ጉዞው ን እንደ ያዘ ይቀጥላል ማለት ነው',\n", - " 'tr_941_tr10042': 'ሶስተኛ ዋ ኳስ ትራንሶ ች ኦፍሳይድ ብለው ሲ ወጡ ቴዎድሮስ አምልጦ በ መሄድ ያገኘው ን ኳስ መትቶ በ ማስቆጠር ሶስት ለ አንድ አሸንፈ ዋል',\n", - " 'tr_942_tr10043': 'የ ኢትዮጵያ የ መከላከያ ሰራዊት በ ቅርቡ የ ገብረ ሀሬ እና ቡርዳሀቦ ከተሞች ን በ ሶማሊያ ብሄራዊ ግንባር ስር የሚገኙት የ ጌዶ ከተሞች ን እንደሚ ያጠቃቸው ስጋቱ አለ',\n", - " 'tr_943_tr10044': 'አንዳንድ ለጋሾች የ ጦርነቱ ን ውጤት እየተ ጠባበቁ ናቸው',\n", - " 'tr_944_tr10045': 'ኢትዮጵያዊያ ን ን በ ብሄር ና በ ሀይማኖት ሳይ ለያይ ይወዳ ቸዋል',\n", - " 'tr_945_tr10046': 'ትምህርታቸው ን እየ ተዉ ለወጡት ተማሪዎች እልባት ባል ተበጀለት በዚህ ወቅት በ ዩኒቨርስቲ ው ለሚገኙ ተማሪዎች የሚ ሰጠው ትምህርት እንዲ ቀል ነው',\n", - " 'tr_946_tr10047': 'ዛሬ ጓደኛው ን ሲያስ ታ ም ም የ ዋ ለ በ ማግስቱ ተኝቶ ያቃስ ታል',\n", - " 'tr_947_tr10048': 'ሌሎቹ ም ያው የምና ያቸው ናቸው',\n", - " 'tr_948_tr10049': 'የ ፊታችን ቅዳሜ የ ቦስተን ነዋሪ ኢትዮጵያውያ ን ታላቅ ስብሰባ ያ ካሄዳ ሉ',\n", - " 'tr_949_tr10050': 'የ ሉ ሲ ቅሪት አሜሪካ ተወስዶ እንደሚ ጐበኝ ተገለጸ',\n", - " 'tr_950_tr10051': 'ሀያ አራት ክትትል ደህንነቶች እርስ በርስ ተገማግመው ከስራ ገበታ ቸው ተነሱ',\n", - " 'tr_951_tr10052': 'ይህ ሁኔታ በ ኮንጐ ዴሞክራቲክ ሪፐብሊክ የተፈጠረ ውን ችግር ሊ ያወሳስበው እንደሚ ችል ብዙዎቹ ገም ተዋል',\n", - " 'tr_952_tr10053': 'ሌኒን እንዳስ ተማረው ደግሞ ቲዮሪ ደብ ዛዛ ና ት',\n", - " 'tr_953_tr10054': 'ማ ንም ቤተሰብ እንደሚ ገናኘው እኔ ም ከ ቅርብ ቤተሰብ ጋር ለ መገናኘት ይህን ያህል አስቸጋሪ ሆኖ እንዴት እንደ ታያቸው አላውቅ ም',\n", - " 'tr_954_tr10055': 'የ ውስጥ ጭን ቄ ን ባይ ረዱ ልኝ ነው',\n", - " 'tr_955_tr10056': 'ይህም ማለት የ ስንቅ ና ትጥቅ አቅርቦቱ ን ማቋረጥ ና ደጀን ማሳጣት ነው',\n", - " 'tr_956_tr10057': 'እነዚህ በ ሽሬ አውራጃ የሚገኙ ወረዳ ዎች ናቸው',\n", - " 'tr_957_tr10058': 'ኢንፎርሜሽ ንና እውነት በ ገዥው ፓርቲ በ ሞ ኖፓል ተ ይ ዟል',\n", - " 'tr_958_tr10059': 'በዚህ ታላቅ ሰልፍ ላይ አገር ወዳድ ኢትዮጵያውያ ን ሁሉ ተገኝተው አንድ ነታቸውን እንደሚያ ስ መሰክሩ ና ድምጻቸው ን በ አንድነት እንደሚ ያሰሙ ታውቋል',\n", - " 'tr_959_tr10060': 'ጊዜው ወደ ሶስት ሳምንት እየ ተጠጋ ነው',\n", - " 'tr_960_tr10061': 'መንግስት በ ኢንቨስትመንት እንቅስቃሴ ላይ የ ተከሰቱ ም የ ፖሊሲ ና የ አሰራር ግድፈቶች ን ለ ማስወገድ እርምጃ መውሰዱ ከ ግሉ ኢንቨስትመንት ፍሰት የ ሚገኘው ን ድርሻ እንደሚያ ሻሽለው ም ገለጹ',\n", - " 'tr_961_tr10062': 'እኔ ግን ነፍጠኛ ም መድፈኛ ም እንዳል ሆ ኩኝ ልንገራችሁ ብዬ እንጂ ፖለቲከኛ ሳል ሆን አሽሙረኛ ነኝ ብዬ እናንተ ን ላሳምናችሁ አል ሞክር ም',\n", - " 'tr_962_tr10063': 'ኮሎኔል በዛብህ ጴጥሮስ የ አማራጭ ሀይሎች ሊቀመንበር የ ዶክተር በየነ ጴጥሮስ ወንድም መሆናቸው ተያይዞ ተ ገልጿ ል',\n", - " 'tr_963_tr10064': 'የ መስተዳድሩ መግለጫ ከተማዋ ስር ነቀል ለውጥ እንደሚ ያስፈልጋት ገልጾ ህዝቡ በዚህ እንዲ ሳተፍ ቢ ጠይቅ ም ጊዜያዊ መስተዳድሩ የ መዋቅር ለውጡ ን ያስፈጽማል ተብሎ አይጠበቅ ም',\n", - " 'tr_964_tr10065': 'ለወደፊቱ በሚ ዘጋጀው ጉባኤ የ በ ኩሌን ሀሳብ ለ ካድሬው ይዤ አቀርባ ለሁ',\n", - " 'tr_965_tr10066': 'ኤኤፍፒ ከ ሶስት ሺ በላይ የኤርትራ ኩናማ ዎች ወደ ኢትዮጵያ ሸሽተው በ መግባት የኤርትራ ሰራዊት በ ሀይል እየ መለመላቸው ነው ሲሉ ውንጀላ ሰንዝ ረዋል',\n", - " 'tr_966_tr10067': 'ዋናው አላማችን አባላ ቶቻችን በ ስፖርቱ ተሳታፊ እንዲሆኑ ና ለ ሀገራችን ስፖርት የ በኩላቸው ን አስተዋጽኦ እንዲ ያበረክቱ እንጂ እንደ አንዳንድ ክለቦች ድርጅት ን ለ ማስተዋወቅ አይደለም',\n", - " 'tr_967_tr10068': 'በ ማጠቃለያ ውም በ እርዳታ አ ሰባሰቡ ወቅት ኢህአዲግ በ በጐ አይ ን የማ ይመለከታቸው ና በ አሸባሪነት ጠርጥሬ ያ ቸዋለሁ የሚ ላቸው ኢትዮጵያውያ ን የ ህግ ታራሚዎች ሳይ ቀሩ በ እርዳታው ተሳትፎ ማድረጋቸው ን አመልክ ቷል',\n", - " 'tr_968_tr10069': 'ምክትል ዳይሬክተሩ ትናንት አዲስ አበባ ሲ ገቡ የ ኢትዮጵያ ዜና አገልግሎት ድርጅት የስራ ሀ ላፈ ዎች ቦሌ አለም አቀፍ አውሮፕላን ጣቢያ ተገኝተው ተቀብለ ዋቸዋል',\n", - " 'tr_969_tr10070': 'የ ኦጋዴን ነጻ አውጪ ግንባር ን እንቅስቃሴ ለ ማምከን ኢህአዴግ ተደጋጋሚ ጥረቶች ን አካሂ ዷል',\n", - " 'tr_970_tr10071': 'አያ ይሄን ን ደብዳቤ በ ዋዛ እንዳ ያዩት ዋዛ አይደለም',\n", - " 'tr_971_tr10072': 'የ ኦርቶዶክስ ና የ ፕሮቴስታንት እምነቶች ልዩነት የሚያስ ገነዝብ ትምህርት ተ ጀም ሯል',\n", - " 'tr_972_tr10073': 'ቢነግሩ ት ለማ ይሰማ ጆሮ የተባለ ውን እንመልከት',\n", - " 'tr_973_tr10074': 'አብዮታችን ወዴት ና እንዴት እ የተጓዘ እንደሚ ገኝ የነ ጠረ ስእል መያዝ የ ድርጅታችን መታደስ አንደኛው ና ቁልፉ እርምጃ ነው',\n", - " 'tr_974_tr10075': 'ህግ ን የ መጣስ ተግባር ሊ ያስከትል የሚ ችለው ን ጦስ የ ኢትዮጵያ ህዝብ በ ጥሞ ና ሊያ ሰላ ስለው ይገባል ባዮች ነን',\n", - " 'tr_975_tr10076': 'ተበታት ነን ያለ ን ስለሆነ እነማን እንዳሉ ና እነማን እንዳል መጡ ለማወቅ አልተቻለ ም',\n", - " 'tr_976_tr10077': 'በ ክልሉ ፍትህ ና ርትእ እንዳይኖር ያደረጉት መስተዳ ድ ሮቹ ናቸው ሲሉ ተ ሰብሳቢዎቹ ገልጸዋል',\n", - " 'tr_977_tr10078': 'ኮሚሽነሩ ግን የ ውሀ ሽ ታ ሆኑ',\n", - " 'tr_978_tr10079': 'ስንዴ ቢ ሰፍሩ ልን ም ቢር በ ንም ኩሩ ና በራሱ የሚ ተማመን ህዝብ እንዳለ ን ሊ ያውቁ ይገባል',\n", - " 'tr_979_tr10080': 'የ ኢትዮ ኤርትራ ን ግጭት በ ተመለከተ ግብጽ ለ ሁለቱ ም ወገን በማ ያደላ መልኩ የ ገለልተኝነት ሚና እንደምት ጫወት በ ሆስኒ ሙባረክ እንደ ተነገራቸው ገልጸዋል',\n", - " 'tr_980_tr10081': 'ተግባ ሬ ግልጽ አቋሜ ም ከ ኢትዮጵያውያ ን ፍላጐት ውጪ ያልሆነ ነው',\n", - " 'tr_981_tr10082': 'ዛሬ ወንድ ና ሴቶች እኩል ናቸው ብለው የሚናገሩ በ ሂሳብ ትምህርት የ ወደቁ ወይም ያልተማሩ ቢ ሰኙ አ ያስገርም ም',\n", - " 'tr_982_tr10083': 'ብሄራዊ ቡድናችን ዝግጅቱ ን እንደማ ያቋርጥ ተ ገልጿ ል',\n", - " 'tr_983_tr10084': 'በ እለቱ ኢንተር አንድ ለ ዜሮ አሸን ፏል',\n", - " 'tr_984_tr10085': 'እና ፊዮሬንቲና ና ቦሎኛ ነገ አይ ላቀቁ ም',\n", - " 'tr_985_tr10086': 'ሌሎች ድርጅቶች ክለብ ሲያ ቋቁሙ ስራ አስኪያጅ ኮሚቴ ይኖራ ቸዋል',\n", - " 'tr_986_tr10087': 'የ ኢትዮጵያ ፉትቦል ደረጃ ን እንዴት አ ዩት',\n", - " 'tr_987_tr10088': 'ለ ልኡል አልቤር ክለብ ኤሪክ ካን ቶ ና ተሰልፎ ተጫው ቷል',\n", - " 'tr_988_tr10089': 'እንደ ምክትል ፕሬዚዳንት ዋ ና ጸሀፊው አባባል በ ኢትዮጵያ ውስጥ በ አሁኑ ወቅት አስራ አምስት ሚሊዮን ህጻናት የ ትምህርት እድል ያላገኙ ናቸው',\n", - " 'tr_989_tr10090': 'ታዛቢዎች እንደሚ ሉት በ ስኳር ና በ ዱቄት ፋብሪካ ሀላፊዎች ክስ መቅረቡ የ ሙስናው ን ዘመቻ ነጻ ና የ ተሟላ አ ያደርገው ም',\n", - " 'tr_990_tr10091': 'በ እየሩሳሌም በ ሚገኘው ና ለ ክርስቲያኖች ቅዱስ ተብሎ በሚ ጠራው ቦታ ላይ ኢትዮጵያዊያ ንና የ ግብጽ መነኩሴ ዎች በ ፈጠሩ ት ግጭት ከፍተኛ ጉዳት መድረሱ ተገለጸ',\n", - " 'tr_991_tr10092': 'በ ጂቡቲ ወህኒ ቤት ኢትዮጵያውያ ን እየ ተንገላቱ ነው',\n", - " 'tr_992_tr10093': 'ይሁን እንጂ ሀብት ና ንብረታቸው እንደማይ ነካ ባቸው ና በ ወኪሎ ቻቸው አማካይ ነት ሊጠበቅ ላቸው እንደሚ ችል ታውቋል',\n", - " 'tr_993_tr10094': 'ለ ኢትዮጵያ ና ለ ኢትዮጵያውያ ን የምናውቅ ላቸው እኛ ወይም እኔ ብቻ ነኝ የሚ ል በሽታ አሁን ም አለ ብን',\n", - " 'tr_994_tr10095': 'ጸሀፊ ዎቹ ቅዳሜ ና እሁድ ገብተው ይፈልጋሉ ተ ባለ',\n", - " 'tr_995_tr10096': 'ጠላት ና ወገን ተባባሪ ባላንጣ ሲ ሆኑ ደግሞ ስለ አንዳች አዲስ ተስፋ ማውሳት ያስቸግራ ል',\n", - " 'tr_996_tr10097': 'የ ዚያ ን ያህል ባይ ሆኑ ም ጨው ና ሌሎች ንም በ ምጽዋ ወደብ የተ ራገፉ እቃዎች ን የ ጫኑ ተሽከርካሪዎች ደግሞ ወደ ኢትዮጵያ እንዳይ ገቡ ተ ከልክለው መቆማቸው ታውቋል',\n", - " 'tr_997_tr10098': 'ባለሞያ ው ለዚህ ሶስት ምክንያቶች ን ሰጥተዋል',\n", - " 'tr_998_tr10099': 'ስምምነቱ ን የፈረሙት የ ንግድ ና ኢንዱስትሪ ሚኒስትር አቶ ግርማ ብሩ ና የ ጅቡቲ የ ገንዘብ የ ኢኮኖሚ ና ፕላን ሚኒስትር ያሲን አልሚ ቦ ህ ናቸው',\n", - " 'tr_999_tr10100': 'ሌላው ቀርቶ የ ኤቨርተን ደጋፊዎች እንኳ ን ከ ራሴ አንስቶ ራሽ ን በ ሞዴልነት እን ወስደው ነበር',\n", - " 'tr_1000_tr11001': 'ያ ኮምፒ ተር ለ ተጠቃሚው በ ትክክል የሚ ፈለገው ን ነገር እንዲ ያሟላ ማድረግ ነው',\n", - " ...}" + "5000" ] }, "metadata": {}, @@ -1123,517 +212,36 @@ } ], "source": [ - "display(translation_obj)" + "display(len(audio_obj))" ] }, { "cell_type": "code", - "execution_count": 13, + "execution_count": 28, + "id": "d2af6021", "metadata": {}, "outputs": [ { "data": { "text/plain": [ - "{'tr_10000_tr097082': (array([-0.11535194, -0.13088593, -0.11130099, ..., -0.12260991,\n", - " -0.14306018, -0.09356608], dtype=float32),\n", - " 9.088,\n", - " 1,\n", - " 22000),\n", - " 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'tr_10084_tr098046': (array([-0.11715524, -0.1325513 , -0.11178781, ..., -0.12611179,\n", - " -0.14726259, -0.09626137], dtype=float32),\n", - " 4.096,\n", - " 1,\n", - " 22000),\n", - " 'tr_10085_tr098047': (array([-0.12009558, -0.13593714, -0.1147755 , ..., -0.12684384,\n", - " -0.14713311, -0.09567105], dtype=float32),\n", - " 3.2,\n", - " 1,\n", - " 22000),\n", - " 'tr_10086_tr098048': (array([-0.12661912, -0.14280415, -0.12063462, ..., -0.12124718,\n", - " -0.14029978, -0.09175819], dtype=float32),\n", - " 4.096,\n", - " 1,\n", - " 22000),\n", - " 'tr_10087_tr098049': (array([-0.11118729, -0.12678559, -0.10747544, ..., -0.1269342 ,\n", - " -0.14780396, -0.09676003], dtype=float32),\n", - " 5.12,\n", - " 1,\n", - " 22000),\n", - " 'tr_10088_tr098050': (array([-0.1212725 , -0.13772127, -0.11666689, ..., -0.12715375,\n", - " -0.1461284 , -0.09472588], dtype=float32),\n", - " 5.248,\n", - " 1,\n", - " 22000),\n", - " 'tr_10089_tr098051': (array([-0.12368317, -0.14043643, -0.11887812, ..., -0.12213954,\n", - " -0.14189196, -0.09261528], dtype=float32),\n", - " 6.912,\n", - " 1,\n", - " 22000),\n", - " 'tr_1008_tr11009': (array([-0.01907633, -0.02169414, -0.01808988, ..., -0.02907302,\n", - " -0.03371771, -0.02193047], dtype=float32),\n", - " 6.016,\n", - " 1,\n", - " 22000),\n", - " 'tr_10090_tr098052': (array([-0.11293647, -0.1282733 , -0.108813 , ..., -0.12874217,\n", - " -0.14914206, -0.09698306], dtype=float32),\n", - " 5.12,\n", - " 1,\n", - " 22000)}" + "'የ ሰርጉ ወጥ ኩ ችም ተደርጐ ነው የ ተሰራው'" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "data": { + "text/html": [ + "\n", + " \n", + " " + ], + "text/plain": [ + "" ] }, "metadata": {}, @@ -1641,12 +249,15 @@ } ], "source": [ - "display(audio_obj)" + "sample_label = list(audio_obj.keys())[490]\n", + "display(translation_obj[sample_label])\n", + "display(ipd.Audio(audio_obj[sample_label][0], rate=rate))" ] }, { "cell_type": "code", - "execution_count": 16, + "execution_count": 18, + "id": "4e832d5d", "metadata": { "colab": { "base_uri": "https://localhost:8080/", @@ -1690,7 +301,7 @@ " የተለያዩ የ ትግራይ አውራጃ ተወላጆች ገንዘባቸው ን አዋጥ ተው የ ልማት ...\n", " tr_10000_tr097082\n", " 1\n", - " 22000\n", + " 8000\n", " 9.088\n", " \n", " \n", @@ -1698,7 +309,7 @@ " የ ጠመንጃ ተኩስ ተከፈተ ና አራት የኤርትራ ወታደሮች ተገደሉ\n", " tr_10001_tr097083\n", " 1\n", - " 22000\n", + " 8000\n", " 5.632\n", " \n", " \n", @@ -1706,7 +317,7 @@ " ላነሷቸው ጥያቄዎች የ ሰጡት ን መልስ አቅርበ ነዋል\n", " tr_10002_tr097084\n", " 1\n", - " 22000\n", + " 8000\n", " 6.144\n", " \n", " \n", @@ -1714,7 +325,7 @@ " እ ብዱ አስፋልቱ ላይ የ ኰለኰ ለ ው ድንጋይ መኪና አላ ሳልፍ አለ\n", " tr_10003_tr097085\n", " 1\n", - " 22000\n", + " 8000\n", " 5.760\n", " \n", " \n", @@ -1722,7 +333,7 @@ " ጠጁ ን ኰ መኰ መ ኰ መኰ መ ና ሚስቱ ን ሲ ያሰቃ ያት አደረ\n", " tr_10004_tr097086\n", " 1\n", - " 22000\n", + " 8000\n", " 5.376\n", " \n", " \n", @@ -1734,81 +345,81 @@ " ...\n", " \n", " \n", - " 95\n", - " በ እለቱ ጥቁር ማሊያ አድርገው የ ገቡት ዩናይት ዶች ልክ እንደ ማሊያው ...\n", - " tr_10087_tr098049\n", + " 4995\n", + " እነ አቶ ተወልደ ካድሬው የሚ ያግዛቸው መስሏቸው ተስፋ አድርገው እንደ ነ...\n", + " tr_4709_tr48010\n", " 1\n", - " 22000\n", - " 5.120\n", + " 8000\n", + " 7.936\n", " \n", " \n", - " 96\n", - " ከ የክልሉ ጥሩ ጥሩ ተጨዋቾች ናቸው ብለው ያመኑ ባቸውን አሰባ ስበዋል\n", - " tr_10088_tr098050\n", + " 4996\n", + " የ አውሮፓ ፓር ሊያ ሜንት በ ኢትዮጵያ ዲሞክራሲያዊ ሂደት ላይ ያለውን ጥ...\n", + " tr_470_tr05070\n", " 1\n", - " 22000\n", - " 5.248\n", + " 8000\n", + " 6.272\n", " \n", " \n", - " 97\n", - " አቶ ደምስ ማ ንም እንደሚ ያውቀው በ ኢትዮጵያ ፉትቦል ፌዴሬሽን ና በ ክ...\n", - " tr_10089_tr098051\n", + " 4997\n", + " አንቺ ቆንጆ የምት ያቸው እንዴት ያሉት ን ሴቶች ነው ለስላሳ ሳቅ በ አዳ...\n", + " tr_4710_tr48011\n", " 1\n", - " 22000\n", - " 6.912\n", + " 8000\n", + " 5.632\n", " \n", " \n", - " 98\n", - " የ ኮሪያ ወታደራዊ ጠበብ ት ኢትዮጵያ ን ን እየ ረዱ ነው\n", - " tr_1008_tr11009\n", + " 4998\n", + " በ አይ ኤም ኤፍ የ ዋሽንግተን ስብሰባ የ ኢትዮጵያ ልኡክ ሊ ሄድ ነው\n", + " tr_4711_tr48012\n", " 1\n", - " 22000\n", - " 6.016\n", + " 8000\n", + " 4.480\n", " \n", " \n", - " 99\n", - " የ ኢትዮጵያ ኦሎምፒክ ኮሚቴ ጽፈት ቤት ጉዳዩ ን አስመልክቶ በ የ አድራሻ...\n", - " tr_10090_tr098052\n", + " 4999\n", + " ምናልባት ከ ኢትዮጵያ ሄዶ ይሆናል\n", + " tr_4712_tr48013\n", " 1\n", - " 22000\n", - " 5.120\n", + " 8000\n", + " 3.328\n", " \n", " \n", "\n", - "

100 rows × 5 columns

\n", + "

5000 rows × 5 columns

\n", "" ], "text/plain": [ - " translation label \\\n", - "0 የተለያዩ የ ትግራይ አውራጃ ተወላጆች ገንዘባቸው ን አዋጥ ተው የ ልማት ... tr_10000_tr097082 \n", - "1 የ ጠመንጃ ተኩስ ተከፈተ ና አራት የኤርትራ ወታደሮች ተገደሉ tr_10001_tr097083 \n", - "2 ላነሷቸው ጥያቄዎች የ ሰጡት ን መልስ አቅርበ ነዋል tr_10002_tr097084 \n", - "3 እ ብዱ አስፋልቱ ላይ የ ኰለኰ ለ ው ድንጋይ መኪና አላ ሳልፍ አለ tr_10003_tr097085 \n", - "4 ጠጁ ን ኰ መኰ መ ኰ መኰ መ ና ሚስቱ ን ሲ ያሰቃ ያት አደረ tr_10004_tr097086 \n", - ".. ... ... \n", - "95 በ እለቱ ጥቁር ማሊያ አድርገው የ ገቡት ዩናይት ዶች ልክ እንደ ማሊያው ... tr_10087_tr098049 \n", - "96 ከ የክልሉ ጥሩ ጥሩ ተጨዋቾች ናቸው ብለው ያመኑ ባቸውን አሰባ ስበዋል tr_10088_tr098050 \n", - "97 አቶ ደምስ ማ ንም እንደሚ ያውቀው በ ኢትዮጵያ ፉትቦል ፌዴሬሽን ና በ ክ... tr_10089_tr098051 \n", - "98 የ ኮሪያ ወታደራዊ ጠበብ ት ኢትዮጵያ ን ን እየ ረዱ ነው tr_1008_tr11009 \n", - "99 የ ኢትዮጵያ ኦሎምፒክ ኮሚቴ ጽፈት ቤት ጉዳዩ ን አስመልክቶ በ የ አድራሻ... tr_10090_tr098052 \n", + " translation label \\\n", + "0 የተለያዩ የ ትግራይ አውራጃ ተወላጆች ገንዘባቸው ን አዋጥ ተው የ ልማት ... tr_10000_tr097082 \n", + "1 የ ጠመንጃ ተኩስ ተከፈተ ና አራት የኤርትራ ወታደሮች ተገደሉ tr_10001_tr097083 \n", + "2 ላነሷቸው ጥያቄዎች የ ሰጡት ን መልስ አቅርበ ነዋል tr_10002_tr097084 \n", + "3 እ ብዱ አስፋልቱ ላይ የ ኰለኰ ለ ው ድንጋይ መኪና አላ ሳልፍ አለ tr_10003_tr097085 \n", + "4 ጠጁ ን ኰ መኰ መ ኰ መኰ መ ና ሚስቱ ን ሲ ያሰቃ ያት አደረ tr_10004_tr097086 \n", + "... ... ... \n", + "4995 እነ አቶ ተወልደ ካድሬው የሚ ያግዛቸው መስሏቸው ተስፋ አድርገው እንደ ነ... tr_4709_tr48010 \n", + "4996 የ አውሮፓ ፓር ሊያ ሜንት በ ኢትዮጵያ ዲሞክራሲያዊ ሂደት ላይ ያለውን ጥ... tr_470_tr05070 \n", + "4997 አንቺ ቆንጆ የምት ያቸው እንዴት ያሉት ን ሴቶች ነው ለስላሳ ሳቅ በ አዳ... tr_4710_tr48011 \n", + "4998 በ አይ ኤም ኤፍ የ ዋሽንግተን ስብሰባ የ ኢትዮጵያ ልኡክ ሊ ሄድ ነው tr_4711_tr48012 \n", + "4999 ምናልባት ከ ኢትዮጵያ ሄዶ ይሆናል tr_4712_tr48013 \n", "\n", - " channel sample_rate duration \n", - "0 1 22000 9.088 \n", - "1 1 22000 5.632 \n", - "2 1 22000 6.144 \n", - "3 1 22000 5.760 \n", - "4 1 22000 5.376 \n", - ".. ... ... ... \n", - "95 1 22000 5.120 \n", - "96 1 22000 5.248 \n", - "97 1 22000 6.912 \n", - "98 1 22000 6.016 \n", - "99 1 22000 5.120 \n", + " channel sample_rate duration \n", + "0 1 8000 9.088 \n", + "1 1 8000 5.632 \n", + "2 1 8000 6.144 \n", + "3 1 8000 5.760 \n", + "4 1 8000 5.376 \n", + "... ... ... ... \n", + "4995 1 8000 7.936 \n", + "4996 1 8000 6.272 \n", + "4997 1 8000 5.632 \n", + "4998 1 8000 4.480 \n", + "4999 1 8000 3.328 \n", "\n", - "[100 rows x 5 columns]" + "[5000 rows x 5 columns]" ] }, - "execution_count": 16, + "execution_count": 18, "metadata": {}, "output_type": "execute_result" } @@ -1819,7 +430,8 @@ }, { "cell_type": "code", - "execution_count": 17, + "execution_count": 19, + "id": "3d5f8486", "metadata": { "colab": { "base_uri": "https://localhost:8080/", @@ -1870,7 +482,7 @@ " የተለያዩ የ ትግራይ አውራጃ ተወላጆች ገንዘባቸው ን አዋጥ ተው የ ልማት ...\n", " tr_10000_tr097082\n", " 1\n", - " 22000\n", + " 8000\n", " 9.088\n", " \n", " \n", @@ -1878,7 +490,7 @@ " የ ጠመንጃ ተኩስ ተከፈተ ና አራት የኤርትራ ወታደሮች ተገደሉ\n", " tr_10001_tr097083\n", " 1\n", - " 22000\n", + " 8000\n", " 5.632\n", " \n", " \n", @@ -1886,7 +498,7 @@ " ላነሷቸው ጥያቄዎች የ ሰጡት ን መልስ አቅርበ ነዋል\n", " tr_10002_tr097084\n", " 1\n", - " 22000\n", + " 8000\n", " 6.144\n", " \n", " \n", @@ -1894,7 +506,7 @@ " እ ብዱ አስፋልቱ ላይ የ ኰለኰ ለ ው ድንጋይ መኪና አላ ሳልፍ አለ\n", " tr_10003_tr097085\n", " 1\n", - " 22000\n", + " 8000\n", " 5.760\n", " \n", " \n", @@ -1902,7 +514,7 @@ " ጠጁ ን ኰ መኰ መ ኰ መኰ መ ና ሚስቱ ን ሲ ያሰቃ ያት አደረ\n", " tr_10004_tr097086\n", " 1\n", - " 22000\n", + " 8000\n", " 5.376\n", " \n", " \n", @@ -1914,81 +526,81 @@ " ...\n", " \n", " \n", - " 95\n", - " በ እለቱ ጥቁር ማሊያ አድርገው የ ገቡት ዩናይት ዶች ልክ እንደ ማሊያው ...\n", - " tr_10087_tr098049\n", + " 4995\n", + " እነ አቶ ተወልደ ካድሬው የሚ ያግዛቸው መስሏቸው ተስፋ አድርገው እንደ ነ...\n", + " tr_4709_tr48010\n", " 1\n", - " 22000\n", - " 5.120\n", + " 8000\n", + " 7.936\n", " \n", " \n", - " 96\n", - " ከ የክልሉ ጥሩ ጥሩ ተጨዋቾች ናቸው ብለው ያመኑ ባቸውን አሰባ ስበዋል\n", - " tr_10088_tr098050\n", + " 4996\n", + " የ አውሮፓ ፓር ሊያ ሜንት በ ኢትዮጵያ ዲሞክራሲያዊ ሂደት ላይ ያለውን ጥ...\n", + " tr_470_tr05070\n", " 1\n", - " 22000\n", - " 5.248\n", + " 8000\n", + " 6.272\n", " \n", " \n", - " 97\n", - " አቶ ደምስ ማ ንም እንደሚ ያውቀው በ ኢትዮጵያ ፉትቦል ፌዴሬሽን ና በ ክ...\n", - " tr_10089_tr098051\n", + " 4997\n", + " አንቺ ቆንጆ የምት ያቸው እንዴት ያሉት ን ሴቶች ነው ለስላሳ ሳቅ በ አዳ...\n", + " tr_4710_tr48011\n", " 1\n", - " 22000\n", - " 6.912\n", + " 8000\n", + " 5.632\n", " \n", " \n", - " 98\n", - " የ ኮሪያ ወታደራዊ ጠበብ ት ኢትዮጵያ ን ን እየ ረዱ ነው\n", - " tr_1008_tr11009\n", + " 4998\n", + " በ አይ ኤም ኤፍ የ ዋሽንግተን ስብሰባ የ ኢትዮጵያ ልኡክ ሊ ሄድ ነው\n", + " tr_4711_tr48012\n", " 1\n", - " 22000\n", - " 6.016\n", + " 8000\n", + " 4.480\n", " \n", " \n", - " 99\n", - " የ ኢትዮጵያ ኦሎምፒክ ኮሚቴ ጽፈት ቤት ጉዳዩ ን አስመልክቶ በ የ አድራሻ...\n", - " tr_10090_tr098052\n", + " 4999\n", + " ምናልባት ከ ኢትዮጵያ ሄዶ ይሆናል\n", + " tr_4712_tr48013\n", " 1\n", - " 22000\n", - " 5.120\n", + " 8000\n", + " 3.328\n", " \n", " \n", "\n", - "

100 rows × 5 columns

\n", + "

5000 rows × 5 columns

\n", "" ], "text/plain": [ - " translation label \\\n", - "0 የተለያዩ የ ትግራይ አውራጃ ተወላጆች ገንዘባቸው ን አዋጥ ተው የ ልማት ... tr_10000_tr097082 \n", - "1 የ ጠመንጃ ተኩስ ተከፈተ ና አራት የኤርትራ ወታደሮች ተገደሉ tr_10001_tr097083 \n", - "2 ላነሷቸው ጥያቄዎች የ ሰጡት ን መልስ አቅርበ ነዋል tr_10002_tr097084 \n", - "3 እ ብዱ አስፋልቱ ላይ የ ኰለኰ ለ ው ድንጋይ መኪና አላ ሳልፍ አለ tr_10003_tr097085 \n", - "4 ጠጁ ን ኰ መኰ መ ኰ መኰ መ ና ሚስቱ ን ሲ ያሰቃ ያት አደረ tr_10004_tr097086 \n", - ".. ... ... \n", - "95 በ እለቱ ጥቁር ማሊያ አድርገው የ ገቡት ዩናይት ዶች ልክ እንደ ማሊያው ... tr_10087_tr098049 \n", - "96 ከ የክልሉ ጥሩ ጥሩ ተጨዋቾች ናቸው ብለው ያመኑ ባቸውን አሰባ ስበዋል tr_10088_tr098050 \n", - "97 አቶ ደምስ ማ ንም እንደሚ ያውቀው በ ኢትዮጵያ ፉትቦል ፌዴሬሽን ና በ ክ... tr_10089_tr098051 \n", - "98 የ ኮሪያ ወታደራዊ ጠበብ ት ኢትዮጵያ ን ን እየ ረዱ ነው tr_1008_tr11009 \n", - "99 የ ኢትዮጵያ ኦሎምፒክ ኮሚቴ ጽፈት ቤት ጉዳዩ ን አስመልክቶ በ የ አድራሻ... tr_10090_tr098052 \n", + " translation label \\\n", + "0 የተለያዩ የ ትግራይ አውራጃ ተወላጆች ገንዘባቸው ን አዋጥ ተው የ ልማት ... tr_10000_tr097082 \n", + "1 የ ጠመንጃ ተኩስ ተከፈተ ና አራት የኤርትራ ወታደሮች ተገደሉ tr_10001_tr097083 \n", + "2 ላነሷቸው ጥያቄዎች የ ሰጡት ን መልስ አቅርበ ነዋል tr_10002_tr097084 \n", + "3 እ ብዱ አስፋልቱ ላይ የ ኰለኰ ለ ው ድንጋይ መኪና አላ ሳልፍ አለ tr_10003_tr097085 \n", + "4 ጠጁ ን ኰ መኰ መ ኰ መኰ መ ና ሚስቱ ን ሲ ያሰቃ ያት አደረ tr_10004_tr097086 \n", + "... ... ... \n", + "4995 እነ አቶ ተወልደ ካድሬው የሚ ያግዛቸው መስሏቸው ተስፋ አድርገው እንደ ነ... tr_4709_tr48010 \n", + "4996 የ አውሮፓ ፓር ሊያ ሜንት በ ኢትዮጵያ ዲሞክራሲያዊ ሂደት ላይ ያለውን ጥ... tr_470_tr05070 \n", + "4997 አንቺ ቆንጆ የምት ያቸው እንዴት ያሉት ን ሴቶች ነው ለስላሳ ሳቅ በ አዳ... tr_4710_tr48011 \n", + "4998 በ አይ ኤም ኤፍ የ ዋሽንግተን ስብሰባ የ ኢትዮጵያ ልኡክ ሊ ሄድ ነው tr_4711_tr48012 \n", + "4999 ምናልባት ከ ኢትዮጵያ ሄዶ ይሆናል tr_4712_tr48013 \n", "\n", - " channel sample_rate duration \n", - "0 1 22000 9.088 \n", - "1 1 22000 5.632 \n", - "2 1 22000 6.144 \n", - "3 1 22000 5.760 \n", - "4 1 22000 5.376 \n", - ".. ... ... ... \n", - "95 1 22000 5.120 \n", - "96 1 22000 5.248 \n", - "97 1 22000 6.912 \n", - "98 1 22000 6.016 \n", - "99 1 22000 5.120 \n", + " channel sample_rate duration \n", + "0 1 8000 9.088 \n", + "1 1 8000 5.632 \n", + "2 1 8000 6.144 \n", + "3 1 8000 5.760 \n", + "4 1 8000 5.376 \n", + "... ... ... ... \n", + "4995 1 8000 7.936 \n", + "4996 1 8000 6.272 \n", + "4997 1 8000 5.632 \n", + "4998 1 8000 4.480 \n", + "4999 1 8000 3.328 \n", "\n", - "[100 rows x 5 columns]" + "[5000 rows x 5 columns]" ] }, - "execution_count": 17, + "execution_count": 19, "metadata": {}, "output_type": "execute_result" } @@ -1999,7 +611,8 @@ }, { "cell_type": "code", - "execution_count": 18, + "execution_count": 20, + "id": "d6c2fa46", "metadata": {}, "outputs": [], "source": [ @@ -2010,7 +623,8 @@ }, { "cell_type": "code", - "execution_count": 19, + "execution_count": 21, + "id": "7dda976a", "metadata": {}, "outputs": [], "source": [ @@ -2019,6 +633,7 @@ }, { "cell_type": "markdown", + "id": "7e592b9d", "metadata": {}, "source": [ "### Data Agumentation, adding noise" @@ -2026,12 +641,13 @@ }, { "cell_type": "code", - "execution_count": 20, + "execution_count": 22, + "id": "6b243702", "metadata": {}, "outputs": [ { "data": { - "image/png": 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\n", 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\n", 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\n", + "image/png": 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\n", 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" ] @@ -2075,7 +691,7 @@ "text/html": [ "\n", " \n", " " @@ -2084,7 +700,7 @@ "" ] }, - "execution_count": 20, + "execution_count": 22, "metadata": {}, "output_type": "execute_result" } @@ -2108,6 +724,7 @@ }, { "cell_type": "markdown", + "id": "f7e6bd25", "metadata": {}, "source": [ "### Shiffiting to left and right" @@ -2116,11 +733,12 @@ { "cell_type": "code", "execution_count": 21, + "id": "01e32d0b", "metadata": {}, "outputs": [ { "data": { - "image/png": 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\n", 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", 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\n", 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", 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\n", + "image/png": 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", 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" ] @@ -2234,6 +852,7 @@ }, { "cell_type": "markdown", + "id": "48300879", "metadata": {}, "source": [ "### pitch" @@ -2242,11 +861,12 @@ { "cell_type": "code", "execution_count": 22, + "id": "5ac69211", "metadata": {}, "outputs": [ { "data": { - "image/png": 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\n", 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", 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" ] @@ -2286,6 +906,7 @@ }, { "cell_type": "markdown", + "id": "b69bd78f", "metadata": {}, "source": [ "### Speed" @@ -2294,11 +915,12 @@ { "cell_type": "code", "execution_count": 23, + "id": "fed7bb58", "metadata": {}, "outputs": [ { "data": { - "image/png": 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\n", + "image/png": 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", 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" ] @@ -2336,9 +958,18 @@ "display(ipd.Audio(speed_man, rate=rate))\n" ] }, + { + "cell_type": "markdown", + "id": "a1c58fe6", + "metadata": {}, + "source": [ + "### MFCC" + ] + }, { "cell_type": "code", "execution_count": 24, + "id": "cbdc41f2", "metadata": {}, "outputs": [], "source": [ @@ -2366,44 +997,870 @@ }, { "cell_type": "code", - "execution_count": 25, + "execution_count": 28, + "id": "b0da4dd4", + "metadata": {}, + "outputs": [], + "source": [ + "audios = {}\n", + "\n", + "for label in audio_obj:\n", + " audios[label] = audio_obj[label][0]\n", + " \n", + "mfcc_features = extract_features(audios, sample_rate)\n" + ] + }, + { + "cell_type": "markdown", + "id": "58ffcc76", + "metadata": {}, + "source": [ + "### Plot MFCC" + ] + }, + { + "cell_type": "code", + "execution_count": 30, + "id": "4e23c300", "metadata": {}, "outputs": [ { - "ename": "TypeError", - "evalue": "only integer scalar arrays can be converted to a scalar index", - "output_type": "error", - "traceback": [ - "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m", - "\u001b[0;31mTypeError\u001b[0m Traceback (most recent call last)", - "\u001b[0;32m\u001b[0m in \u001b[0;36m\u001b[0;34m\u001b[0m\n\u001b[1;32m 1\u001b[0m \u001b[0maudios\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0;34m[\u001b[0m\u001b[0maudio_obj\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0mlabel\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;36m0\u001b[0m\u001b[0;34m]\u001b[0m \u001b[0;32mfor\u001b[0m \u001b[0mlabel\u001b[0m \u001b[0;32min\u001b[0m \u001b[0maudio_obj\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m----> 2\u001b[0;31m \u001b[0mmfcc_features\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mextract_features\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0maudios\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0msample_rate\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m", - "\u001b[0;32m\u001b[0m in \u001b[0;36mextract_features\u001b[0;34m(audios, sample_rate)\u001b[0m\n\u001b[1;32m 16\u001b[0m \u001b[0mmfcc_features\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0;34m{\u001b[0m\u001b[0;34m}\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 17\u001b[0m \u001b[0;32mfor\u001b[0m \u001b[0maudio\u001b[0m \u001b[0;32min\u001b[0m \u001b[0maudios\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m---> 18\u001b[0;31m \u001b[0mmfcc_features\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0maudio\u001b[0m\u001b[0;34m]\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mlibrosa\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mfeature\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mmfcc\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0maudios\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0maudio\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0msr\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0msample_rate\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 19\u001b[0m \u001b[0;32mreturn\u001b[0m \u001b[0mmfcc_features\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 20\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n", - "\u001b[0;31mTypeError\u001b[0m: only integer scalar arrays can be converted to a scalar index" + "name": "stdout", + "output_type": "stream", + "text": [ + "(20, 160)\n" ] + }, + { + "data": { + "text/plain": [ + "" + ] + }, + "execution_count": 30, + "metadata": {}, + "output_type": "execute_result" + }, + { + "data": { + "image/png": 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", + "text/plain": [ + "
" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" } ], "source": [ - "audios = {}\n", + "# MFCC\n", + "fig, ax = plt.subplots()\n", + "ax = plt.Axes(fig, [0., 0., 1., 1.])\n", + "ax.set_axis_off()\n", + "fig.add_axes(ax)\n", + "mfccs = mfcc_features[list(mfcc_features.keys())[88]]\n", + "print(mfccs.shape)\n", + "librosa.display.specshow(mfccs, sr=44100, x_axis='time')" + ] + }, + { + "cell_type": "markdown", + "id": "f4984639", + "metadata": {}, + "source": [ + "### Tokenizer" + ] + }, + { + "cell_type": "code", + "execution_count": 5, + "id": "05d75818", + "metadata": {}, + "outputs": [], + "source": [ + "class Tokenizer:\n", + " \n", + " def __init__(self, translations):\n", + " self.translations = translations\n", + " self.unk = -1\n", + " \n", + " def build_dict(self):\n", + " text = ''\n", + " for t in self.translations:\n", + " text += t\n", + " \n", + " char_counts = Counter(text)\n", + " sorted_vocab = sorted(char_counts, key=char_counts.get, reverse=True)\n", + " int_to_char = {ii: word for ii, word in enumerate(sorted_vocab, 1)}\n", + "\n", + " char_to_int = {word: ii for ii, word in int_to_char.items()}\n", + " \n", + " return int_to_char, char_to_int\n", + " \n", + " def encode(self, sent, char_to_int):\n", + " \n", + " encoded = []\n", + " char_list = list(sent)\n", + " for c in char_list:\n", + " try:\n", + " encoded.append(char_to_int[c])\n", + " \n", + " except KeyError:\n", + " encoded.append(self.unk)\n", + " return encoded\n", + " \n", + " def decode_text(self, encoded_chars, int_to_char):\n", + " \n", + " decoded = ''\n", + " for e in encoded_chars:\n", + " try:\n", + " decoded += e\n", + " \n", + " except KeyError:\n", + " decoded += ''\n", + " \n", + " return decoded\n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + "\n", + " " + ] + }, + { + "cell_type": "markdown", + "id": "18f482fc", + "metadata": {}, + "source": [ + "### Data Generator" + ] + }, + { + "cell_type": "code", + "execution_count": 6, + "id": "6c40adbf", + "metadata": {}, + "outputs": [], + "source": [ + "class DataGenerator(tf.keras.utils.Sequence):\n", + " def __init__(self, translations, audios, batch_size=32, shuffle=True):\n", + " self.audios = audios\n", + " self.labels = translations\n", + " self.batch_size = batch_size\n", + " self.len = int(np.floor(len(self.labels) / self.batch_size))\n", + " self.shuffle = shuffle\n", + " self.on_epoch_end()\n", + " \n", + " self.tokenizer = Tokenizer(translations)\n", + " self.int_to_char, self.char_to_int = tokenizer.build_dict()\n", + " \n", + " self.cur_index = 0\n", + "\n", + " def __len__(self):\n", + " return self.len\n", + " \n", + " def encode_text(self, translations):\n", + " encoded_trans = []\n", + " \n", + " for t in translations:\n", + " encoded = self.tokenizer.encode(t, self.char_to_int)\n", + " encoded_trans.append(encoded)\n", + " \n", + " return encoded_trans\n", + " \n", + " def get_max_len(self, items):\n", + " maximum = 0\n", + " for i in items:\n", + " if len(i) > maximum:\n", + " maximum = len(i)\n", + " \n", + " return maximum\n", + "\n", + " \n", + " def __data_generation(self, batch_translations, batch_audios):\n", + " \n", + " self.cur_index = 0\n", + " encoded_trans = self.encode_text(batch_translations)\n", + " \n", + " maximum_trans_len = self.get_max_len(encoded_trans)\n", + " maximum_audio_len = self.get_max_len(batch_audios)\n", + " \n", + " \n", + " encoded_trans_np = np.zeros((len(encoded_trans), maximum_trans_len), dtype=\"int64\")\n", + " padded_audios_np = np.zeros((len(batch_audios), maximum_audio_len), dtype=\"float32\")\n", + " \n", + " label_length = np.zeros(padded_audios_np.shape[0], dtype=\"int64\")\n", + " input_length = np.zeros(encoded_trans_np.shape[0], dtype=\"int64\")\n", + " \n", + " \n", + " ind = 0\n", + " for trans, audio in zip(encoded_trans, batch_audios):\n", + " encoded_trans_np[ind,0:len(trans)] = trans\n", + " label_length[ind] = len(trans)\n", + " \n", + " padded_audio = np.pad(audio, (0, maximum_audio_len - len(audio)), mode = 'constant', constant_values=0)\n", + " \n", + " padded_audios_np[ind, ] = padded_audio\n", + " input_length[ind] = len(audio)\n", + " \n", + " ind += 1\n", + " \n", + " outputs = {'ctc': np.zeros([self.batch_size])}\n", + " inputs = {'the_input': tf.convert_to_tensor(padded_audios_np), \n", + " 'the_labels': tf.convert_to_tensor(encoded_trans_np), \n", + " 'input_length': tf.convert_to_tensor(input_length), \n", + " 'label_length': tf.convert_to_tensor(label_length) \n", + " }\n", + " \n", + " return (inputs, outputs)\n", + " \n", + " def on_epoch_end(self):\n", + " \n", + " self.indexes = np.arange(self.len*self.batch_size)\n", + "\n", + " if self.shuffle == True:\n", + "\n", + " self.indexes = self.indexes.reshape(int(self.len), int(self.batch_size))\n", + " np.random.shuffle(self.indexes)\n", + "\n", + " for i in range(self.len):\n", + " np.random.shuffle(self.indexes[i])\n", + "\n", + " self.indexes = self.indexes.reshape(int(self.len*self.batch_size))\n", + "\n", + "\n", + " def __getitem__(self, index):\n", + " indexes = self.indexes[int(index*self.batch_size):int((index+1)*self.batch_size)]\n", + " \n", + " self.cur_index += self.batch_size\n", + " \n", + " if self.cur_index >= len(self.labels):\n", + " self.cur_index = 0\n", + "\n", + " batch_labels = [self.labels[int(k)] for k in indexes]\n", + " batch_audios = [self.audios[int(k)] for k in indexes]\n", + " \n", + " batch_labels = self.labels[self.cur_index: self.cur_index + self.batch_size]\n", + " batch_audios = self.audios[ self.cur_index: self.cur_index + self.batch_size]\n", + " \n", + " \n", + " return self.__data_generation(batch_labels, batch_audios)" + ] + }, + { + "cell_type": "markdown", + "id": "5bc28e25", + "metadata": {}, + "source": [ + "### Custome LogMelSpectrogram Layer" + ] + }, + { + "cell_type": "code", + "execution_count": 7, + "id": "da5b50ac", + "metadata": {}, + "outputs": [], + "source": [ + "class LogMelSpectrogram(tf.keras.layers.Layer):\n", + " \"\"\"Compute log-magnitude mel-scaled spectrograms.\"\"\"\n", + "\n", + " def __init__(self, sample_rate, fft_size, hop_size, n_mels,\n", + " f_min=0.0, f_max=None, **kwargs):\n", + " super(LogMelSpectrogram, self).__init__(**kwargs)\n", + " self.sample_rate = sample_rate\n", + " self.fft_size = fft_size\n", + " self.hop_size = hop_size\n", + " self.n_mels = n_mels\n", + " self.f_min = f_min\n", + " self.f_max = f_max if f_max else sample_rate / 2\n", + " self.mel_filterbank = tf.signal.linear_to_mel_weight_matrix(\n", + " num_mel_bins=self.n_mels,\n", + " num_spectrogram_bins=fft_size // 2 + 1,\n", + " sample_rate=self.sample_rate,\n", + " lower_edge_hertz=self.f_min,\n", + " upper_edge_hertz=self.f_max)\n", + "\n", + " def build(self, input_shape):\n", + " self.non_trainable_weights.append(self.mel_filterbank)\n", + " super(LogMelSpectrogram, self).build(input_shape)\n", + "\n", + " def call(self, waveforms):\n", + " \"\"\"Forward pass.\n", + " Parameters\n", + " ----------\n", + " waveforms : tf.Tensor, shape = (None, n_samples)\n", + " A Batch of mono waveforms.\n", + " Returns\n", + " -------\n", + " log_mel_spectrograms : (tf.Tensor), shape = (None, time, freq, ch)\n", + " The corresponding batch of log-mel-spectrograms\n", + " \"\"\"\n", + " def _tf_log10(x):\n", + " numerator = tf.math.log(x)\n", + " denominator = tf.math.log(tf.constant(10, dtype=numerator.dtype))\n", + " return numerator / denominator\n", + "\n", + " def power_to_db(magnitude, amin=1e-16, top_db=80.0):\n", + " \"\"\"\n", + " https://librosa.github.io/librosa/generated/librosa.core.power_to_db.html\n", + " \"\"\"\n", + " ref_value = tf.reduce_max(magnitude)\n", + " log_spec = 10.0 * _tf_log10(tf.maximum(amin, magnitude))\n", + " log_spec -= 10.0 * _tf_log10(tf.maximum(amin, ref_value))\n", + " log_spec = tf.maximum(log_spec, tf.reduce_max(log_spec) - top_db)\n", + "\n", + " return log_spec\n", + "\n", + " spectrograms = tf.signal.stft(waveforms,\n", + " frame_length=self.fft_size,\n", + " frame_step=self.hop_size,\n", + " pad_end=False)\n", + "\n", + " magnitude_spectrograms = tf.abs(spectrograms)\n", + "\n", + " mel_spectrograms = tf.matmul(tf.square(magnitude_spectrograms),\n", + " self.mel_filterbank)\n", + "\n", + " log_mel_spectrograms = power_to_db(mel_spectrograms)\n", + "\n", + " # add channel dimension\n", + " log_mel_spectrograms = tf.expand_dims(log_mel_spectrograms, 3)\n", + "\n", + " return log_mel_spectrograms\n", + "\n", + " def get_config(self):\n", + " config = {\n", + " 'fft_size': self.fft_size,\n", + " 'hop_size': self.hop_size,\n", + " 'n_mels': self.n_mels,\n", + " 'sample_rate': self.sample_rate,\n", + " 'f_min': self.f_min,\n", + " 'f_max': self.f_max,\n", + " }\n", + " config.update(super(LogMelSpectrogram, self).get_config())\n", + "\n", + " return config" + ] + }, + { + "cell_type": "markdown", + "id": "cd87e420", + "metadata": {}, + "source": [ + "### Model for logspectorgram generation" + ] + }, + { + "cell_type": "code", + "execution_count": 8, + "id": "7880e388", + "metadata": {}, + "outputs": [], + "source": [ + "def preprocessin_model(sample_rate, fft_size, frame_step, n_mels, mfcc=False):\n", + "\n", + " input_data = Input(name='input', shape=(None,), dtype=\"float32\")\n", + " featLayer = LogMelSpectrogram(\n", + " fft_size=fft_size,\n", + " hop_size=frame_step,\n", + " n_mels=n_mels,\n", + " \n", + " sample_rate=sample_rate,\n", + " f_min=0.0,\n", + " \n", + " f_max=int(sample_rate / 2)\n", + " )(input_data)\n", + " \n", + " x = BatchNormalization()(featLayer)\n", + " model = Model(inputs=input_data, outputs=x, name=\"preprocessin_model\")\n", + "\n", + " return model" + ] + }, + { + "cell_type": "code", + "execution_count": 9, + "id": "a13c9798", + "metadata": {}, + "outputs": [], + "source": [ + "def BidirectionalRNN(input_dim, batch_size, sample_rate=22000,\n", + " rnn_layers=2, units=400, drop_out=0.5, act='tanh', output_dim=224):\n", + "\n", + " input_data = Input(name='the_input', shape=(\n", + " None, input_dim), batch_size=batch_size)\n", + " \n", + "\n", + "\n", + " \n", + " x = Bidirectional(LSTM(units, activation=act,\n", + " return_sequences=True, implementation=2))(input_data)\n", + " \n", + " x = BatchNormalization()(x)\n", + " x = Dropout(drop_out)(x)\n", + "\n", + " for i in range(rnn_layers - 2):\n", + " x = Bidirectional(\n", + " LSTM(units, activation=act, return_sequences=True))(x)\n", + " x = BatchNormalization()(x)\n", + " x = Dropout(drop_out)(x)\n", + "\n", + " x = Bidirectional(LSTM(units, activation=act,\n", + " return_sequences=True, implementation=2))(x)\n", + " x = BatchNormalization()(x)\n", + " x = Dropout(drop_out)(x)\n", + "\n", + " time_dense = TimeDistributed(Dense(output_dim))(x)\n", + "\n", + " y_pred = Activation('softmax', name='softmax')(time_dense)\n", + "\n", + " model = Model(inputs=input_data, outputs=y_pred, name=\"BidirectionalRNN\")\n", + "\n", + " return model" + ] + }, + { + "cell_type": "code", + "execution_count": 24, + "id": "5bc2f669", + "metadata": {}, + "outputs": [], + "source": [ + "def simple_rnn_model(input_dim, output_dim=224):\n", + "\n", + " input_data = Input(name='the_input', shape=(None, input_dim))\n", + " simp_rnn = GRU(output_dim, return_sequences=True,\n", + " implementation=2, name='rnn')(input_data)\n", + " y_pred = Activation('softmax', name='softmax')(simp_rnn)\n", + " model = Model(inputs=input_data, outputs=y_pred, name=\"simple_rnn_model\")\n", + " model.output_length = lambda x: x\n", + " return model\n" + ] + }, + { + "cell_type": "code", + "execution_count": 25, + "id": "0d55f68c", + "metadata": {}, + "outputs": [], + "source": [ + "def ctc_lambda_func(args):\n", + " y_pred, labels, input_length, label_length = args\n", + " return K.ctc_batch_cost(labels, y_pred, input_length, label_length)" + ] + }, + { + "cell_type": "code", + "execution_count": 26, + "id": "a7810465", + "metadata": {}, + "outputs": [], + "source": [ + "def input_lengths_lambda_func(args):\n", + " hop_size = frame_step\n", + " input_length = args\n", + " return tf.cast(tf.math.ceil(input_length/hop_size)-1, dtype=\"float32\")" + ] + }, + { + "cell_type": "code", + "execution_count": 27, + "id": "0cd84d9b", + "metadata": {}, + "outputs": [], + "source": [ + "def add_ctc_loss(model_builder):\n", + " the_labels = Input(name='the_labels', shape=(None,), dtype='float32')\n", + " input_lengths = Input(name='input_length', shape=(1,), dtype='float32')\n", + " label_lengths = Input(name='label_length', shape=(1,), dtype='float32')\n", + "\n", + " input_lengths2 = Lambda(input_lengths_lambda_func)(input_lengths)\n", + " if model_builder.output_length:\n", + " output_lengths = Lambda(model_builder.output_length)(input_lengths2) - 1\n", + " else:\n", + " output_lengths = input_lengths2\n", + " \n", + " # CTC loss is implemented in a lambda layer\n", + " loss_out = Lambda(ctc_lambda_func, output_shape=(1,), name='ctc')([model_builder.output, the_labels, output_lengths, label_lengths])\n", + " model = Model( inputs=[model_builder.input, the_labels, input_lengths, label_lengths], outputs=loss_out)\n", + " return model\n" + ] + }, + { + "cell_type": "code", + "execution_count": 29, + "id": "c8dfb93e", + "metadata": {}, + "outputs": [], + "source": [ + "from tensorflow.keras.models import Model, Sequential\n", + "from tensorflow.keras.layers import * \n", + "from tensorflow.keras.preprocessing.sequence import pad_sequences\n", + "from tensorflow.keras.optimizers import SGD, Adam, RMSprop\n", + "from tensorflow.keras import backend as K" + ] + }, + { + "cell_type": "code", + "execution_count": 30, + "id": "83d4fb3d", + "metadata": {}, + "outputs": [], + "source": [ + "def train(model_builder, \n", + " data_len,\n", + " data_gen,\n", + " batch_size = 25,\n", + " epochs=20, \n", + " verbose=1,\n", + " optimizer=SGD(learning_rate=0.002, decay=1e-6, momentum=0.9, nesterov=True, clipnorm=5),\n", + " ): \n", + " \n", + " model = add_ctc_loss(model_builder)\n", + "\n", + " model.compile(loss={'ctc': lambda y_true, y_pred: y_pred}, optimizer=optimizer)\n", + " print(model.summary())\n", "\n", + "\n", + " hist = model.fit_generator(generator=data_gen,\n", + " epochs=epochs,\n", + " verbose=verbose, \n", + " use_multiprocessing=False)" + ] + }, + { + "cell_type": "markdown", + "id": "760baa7d", + "metadata": {}, + "source": [ + "### Training" + ] + }, + { + "cell_type": "code", + "execution_count": 53, + "id": "a155eb50", + "metadata": {}, + "outputs": [], + "source": [ + "audios = []\n", "for label in audio_obj:\n", - " audios[label] = audio_obj[label][0]\n", + " audios.append(audio_obj[label][0])\n", " \n", - "audios = [audio_obj[label][0] for label in audio_obj]\n", - "mfcc_features = extract_features(audios, sample_rate)\n" + "translations = []\n", + "for label in audio_obj:\n", + " translations.append(translation_obj[label])" ] }, { "cell_type": "code", - "execution_count": null, + "execution_count": 68, + "id": "8f6fcf08", + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "sample snt: የተለያዩ የ ትግራይ አውራጃ ተወላጆች ገንዘባቸው ን አዋጥ ተው የ ልማት ተቋማትን እንዲ መሰርቱ ትልማ አይ ፈቅድ ም\n", + "encoded snt: [8, 10, 13, 7, 111, 1, 8, 1, 3, 40, 23, 21, 1, 6, 4, 23, 98, 1, 10, 32, 28, 124, 16, 1, 17, 2, 75, 27, 31, 4, 1, 2, 1, 6, 41, 42, 1, 10, 4, 1, 8, 1, 11, 29, 3, 1, 10, 87, 29, 3, 2, 1, 19, 2, 50, 1, 12, 25, 14, 51, 1, 3, 11, 29, 1, 6, 21, 1, 76, 57, 30, 1, 18]\n", + "decoed snt: የተለያዩ የ ትግራይ አውራጃ ተወላጆች ገንዘባቸው ን አዋጥ ተው የ ልማት ተቋማትን እንዲ መሰርቱ ትልማ አይ ፈቅድ ም\n" + ] + } + ], + "source": [ + "tokenizer = Tokenizer(translations)\n", + "int_to_char, char_to_int = tokenizer.build_dict()\n", + "sample = translations[0]\n", + "encoded = tokenizer.encode(sample, char_to_int)\n", + "decoded = tokenizer.decode_text(sample, encoded)\n", + "\n", + "print(f\"sample snt: {sample}\")\n", + "print(f\"encoded snt: {encoded}\")\n", + "print(f\"decoed snt: {decoded}\")" + ] + }, + { + "cell_type": "code", + "execution_count": 69, + "id": "a2b66a26", + "metadata": {}, + "outputs": [], + "source": [ + "\n", + "sample_rate = 22000\n", + "fft_size = 1024\n", + "frame_step = 512\n", + "n_mels = 128\n", + "\n", + "batch_size = 100\n", + "epochs = 20\n", + "data_len = len(translations)\n", + "output_dim = len(char_to_int) + 2\n" + ] + }, + { + "cell_type": "code", + "execution_count": 70, + "id": "0e6b2ed2", + "metadata": {}, + "outputs": [], + "source": [ + "dg = DataGenerator(translations, audios, batch_size)\n" + ] + }, + { + "cell_type": "code", + "execution_count": 71, + "id": "dc32da3f", + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Model: \"preprocessin_model\"\n", + "_________________________________________________________________\n", + "Layer (type) Output Shape Param # \n", + "=================================================================\n", + "input (InputLayer) [(None, None)] 0 \n", + "_________________________________________________________________\n", + "log_mel_spectrogram_4 (LogMe (None, None, 128, 1) 0 \n", + "_________________________________________________________________\n", + "batch_normalization_4 (Batch (None, None, 128, 1) 4 \n", + "=================================================================\n", + "Total params: 4\n", + "Trainable params: 2\n", + "Non-trainable params: 2\n", + "_________________________________________________________________\n" + ] + } + ], + "source": [ + "preprocess_model = preprocessin_model(sample_rate, fft_size, frame_step, n_mels)\n", + "preprocess_model.summary()\n" + ] + }, + { + "cell_type": "code", + "execution_count": 72, + "id": "43fa4991", + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Model: \"simple_rnn_model\"\n", + "_________________________________________________________________\n", + "Layer (type) Output Shape Param # \n", + "=================================================================\n", + "the_input (InputLayer) [(None, None, 128)] 0 \n", + "_________________________________________________________________\n", + "rnn (GRU) (None, None, 175) 160125 \n", + "_________________________________________________________________\n", + "softmax (Activation) (None, None, 175) 0 \n", + "=================================================================\n", + "Total params: 160,125\n", + "Trainable params: 160,125\n", + "Non-trainable params: 0\n", + "_________________________________________________________________\n" + ] + } + ], + "source": [ + "speech_model = simple_rnn_model(n_mels, output_dim)\n", + "speech_model.summary()\n", + "# speech_model = BidirectionalRNN(n_mels, output_dim=output_dim)\n", + "# speech_model.summary()" + ] + }, + { + "cell_type": "code", + "execution_count": 75, + "id": "7e0d5d52", + "metadata": {}, + "outputs": [], + "source": [ + "def build_model(output_dim, custom_model, preprocess_model, mfcc=False, calc=None):\n", + "\n", + " input_audios = Input(name='the_input', shape=(None,))\n", + " pre = preprocess_model(input_audios)\n", + " pre = tf.squeeze(pre, [3])\n", + "\n", + " y_pred = custom_model(pre)\n", + " model = Model(inputs=input_audios, outputs=y_pred, name=\"model_builder\")\n", + " model.output_length = calc\n", + "\n", + " return model" + ] + }, + { + "cell_type": "code", + "execution_count": 76, + "id": "bbaf2460", + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Model: \"model_builder\"\n", + "_________________________________________________________________\n", + "Layer (type) Output Shape Param # \n", + "=================================================================\n", + "the_input (InputLayer) [(None, None)] 0 \n", + "_________________________________________________________________\n", + "preprocessin_model (Function (None, None, 128, 1) 4 \n", + "_________________________________________________________________\n", + "tf.compat.v1.squeeze_5 (TFOp (None, None, 128) 0 \n", + "_________________________________________________________________\n", + "simple_rnn_model (Functional (None, None, 175) 160125 \n", + "=================================================================\n", + "Total params: 160,129\n", + "Trainable params: 160,127\n", + "Non-trainable params: 2\n", + "_________________________________________________________________\n" + ] + } + ], + "source": [ + "model = build_model(output_dim, speech_model, preprocess_model)\n", + "model.summary()\n" + ] + }, + { + "cell_type": "code", + "execution_count": 77, + "id": "d11f997b", "metadata": {}, "outputs": [], "source": [ - "audios" + "import mlflow" + ] + }, + { + "cell_type": "code", + "execution_count": 79, + "id": "9fd2234f", + "metadata": {}, + "outputs": [ + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2021/08/08 13:16:37 INFO mlflow.utils.autologging_utils: Created MLflow autologging run with ID 'd9db32294f5c4678815d6b6efc825325', which will track hyperparameters, performance metrics, model artifacts, and lineage information for the current tensorflow workflow\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Model: \"model_6\"\n", + "__________________________________________________________________________________________________\n", + "Layer (type) Output Shape Param # Connected to \n", + "==================================================================================================\n", + "the_input (InputLayer) [(None, None)] 0 \n", + "__________________________________________________________________________________________________\n", + "preprocessin_model (Functional) (None, None, 128, 1) 4 the_input[0][0] \n", + "__________________________________________________________________________________________________\n", + "tf.compat.v1.squeeze_5 (TFOpLam (None, None, 128) 0 preprocessin_model[1][0] \n", + "__________________________________________________________________________________________________\n", + "input_length (InputLayer) [(None, 1)] 0 \n", + "__________________________________________________________________________________________________\n", + "simple_rnn_model (Functional) (None, None, 175) 160125 tf.compat.v1.squeeze_5[0][0] \n", + "__________________________________________________________________________________________________\n", + "the_labels (InputLayer) [(None, None)] 0 \n", + "__________________________________________________________________________________________________\n", + "lambda_6 (Lambda) (None, 1) 0 input_length[0][0] \n", + "__________________________________________________________________________________________________\n", + "label_length (InputLayer) [(None, 1)] 0 \n", + "__________________________________________________________________________________________________\n", + "ctc (Lambda) (None, 1) 0 simple_rnn_model[1][0] \n", + " the_labels[0][0] \n", + " lambda_6[0][0] \n", + " label_length[0][0] \n", + "==================================================================================================\n", + "Total params: 160,129\n", + "Trainable params: 160,127\n", + "Non-trainable params: 2\n", + "__________________________________________________________________________________________________\n", + "None\n", + "Epoch 1/20\n", + "1/1 [==============================] - 10s 10s/step - loss: 720.1365\n", + "Epoch 2/20\n", + "1/1 [==============================] - 8s 8s/step - loss: 711.0939\n", + "Epoch 3/20\n", + "1/1 [==============================] - 6s 6s/step - loss: 703.3038\n", + "Epoch 4/20\n", + "1/1 [==============================] - 5s 5s/step - loss: 696.7689\n", + "Epoch 5/20\n", + "1/1 [==============================] - 5s 5s/step - loss: 691.0403\n", + "Epoch 6/20\n", + "1/1 [==============================] - 5s 5s/step - loss: 685.7213\n", + "Epoch 7/20\n", + "1/1 [==============================] - 5s 5s/step - loss: 680.5095\n", + "Epoch 8/20\n", + "1/1 [==============================] - 5s 5s/step - loss: 676.0887\n", + "Epoch 9/20\n", + "1/1 [==============================] - 5s 5s/step - loss: 673.8625\n", + "Epoch 10/20\n", + "1/1 [==============================] - 6s 6s/step - loss: 672.7012\n", + "Epoch 11/20\n", + "1/1 [==============================] - 5s 5s/step - loss: 671.8706\n", + "Epoch 12/20\n", + "1/1 [==============================] - 5s 5s/step - loss: 671.2330\n", + "Epoch 13/20\n", + "1/1 [==============================] - 5s 5s/step - loss: 670.7097\n", + "Epoch 14/20\n", + "1/1 [==============================] - 5s 5s/step - loss: 670.1967\n", + "Epoch 15/20\n", + "1/1 [==============================] - 5s 5s/step - loss: 669.3744\n", + "Epoch 16/20\n", + "1/1 [==============================] - 5s 5s/step - loss: 667.4127\n", + "Epoch 17/20\n", + "1/1 [==============================] - 5s 5s/step - loss: 665.1722\n", + "Epoch 18/20\n", + "1/1 [==============================] - 5s 5s/step - loss: 664.1326\n", + "Epoch 19/20\n", + "1/1 [==============================] - 5s 5s/step - loss: 662.3972\n", + "Epoch 20/20\n", + "1/1 [==============================] - 5s 5s/step - loss: 659.3508\n" + ] + } + ], + "source": [ + "mlflow.set_experiment('Speech Model-RNN-baseline')\n", + "mlflow.tensorflow.autolog()\n", + "train(model, 100, dg, epochs=20, batch_size=100)\n" ] }, + { + "cell_type": "code", + "execution_count": 1, + "id": "721048e0", + "metadata": {}, + "outputs": [], + "source": [] + }, + { + "cell_type": "code", + "execution_count": 3, + "id": "726654f7", + "metadata": {}, + "outputs": [], + "source": [] + }, { "cell_type": "code", "execution_count": null, + "id": "8d33bb32", "metadata": {}, "outputs": [], "source": [] @@ -2415,6 +1872,9 @@ "name": "AS2T.ipynb", "provenance": [] }, + "interpreter": { + "hash": "51d477eca99ce531616b0189382ec1bb5b39235ab0a3993ccfacd0c8fd3459be" + }, "kernelspec": { "display_name": "Python 3", "language": "python", @@ -2430,7 +1890,7 @@ "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", - "version": "3.7.6" + "version": "3.9.4" } }, "nbformat": 4, diff --git a/notebooks/Amharic_Speech_To_Text.ipynb b/notebooks/Amharic_Speech_To_Text.ipynb new file mode 100644 index 0000000..b25a23b --- /dev/null +++ b/notebooks/Amharic_Speech_To_Text.ipynb @@ -0,0 +1,1229 @@ +{ + "cells": [ + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## **Imports**" + ] + }, + { + "cell_type": "code", + "execution_count": 1, + "metadata": {}, + "outputs": [ + { + "name": "stderr", + "output_type": "stream", + "text": [ + "\n", + "Bad key \"text.kerning_factor\" on line 4 in\n", + "C:\\Users\\HP\\Anaconda3\\lib\\site-packages\\matplotlib\\mpl-data\\stylelib\\_classic_test_patch.mplstyle.\n", + "You probably need to get an updated matplotlibrc file from\n", + "http://github.com/matplotlib/matplotlib/blob/master/matplotlibrc.template\n", + "or from the matplotlib source distribution\n" + ] + } + ], + "source": [ + "# setting path\n", + "\n", + "import sys\n", + "sys.path.append('../scripts')\n", + "from dataset_loader import load_audio_files, load_transcripts, load_spectrograms_with_transcripts, load_spectrograms_with_transcripts_in_batches\n", + "from resize_and_augment import resize_audios_mono, augment_audio, equalize_transcript_dimension\n", + "from FeatureExtraction import FeatureExtraction\n", + "from transcript_encoder import fit_label_encoder, encode_transcripts, decode_predicted\n", + "from models import model_1\n", + "sys.path.append('../notebooks')" + ] + }, + { + "cell_type": "code", + "execution_count": 2, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "9" + ] + }, + "execution_count": 2, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "import librosa #for audio processing\n", + "import librosa.display\n", + "import IPython.display as ipd\n", + "import matplotlib.pyplot as plt\n", + "import numpy as np\n", + "import warnings\n", + "import os\n", + "import mlflow\n", + "import mlflow.keras\n", + "import logging\n", + "len(os.listdir('../data/train/wav/'))" + ] + }, + { + "cell_type": "code", + "execution_count": 3, + "metadata": {}, + "outputs": [], + "source": [ + "sample_rate = 22050" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## **Load Audio Files**" + ] + }, + { + "cell_type": "code", + "execution_count": 4, + "metadata": {}, + "outputs": [], + "source": [ + "audio_files, maximum_length = load_audio_files('../data/train/wav/', sample_rate, True)\n", + "logging.info('loaded audio files')" + ] + }, + { + "cell_type": "code", + "execution_count": 5, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "The longest audio is 9.088027210884354 seconds long\n" + ] + } + ], + "source": [ + "print(\"The longest audio is\",maximum_length/sample_rate, 'seconds long')" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## **Load Transcripts**" + ] + }, + { + "cell_type": "code", + "execution_count": 6, + "metadata": {}, + "outputs": [], + "source": [ + "transcripts = load_transcripts(\"../data/train/trsTrain.txt\")\n", + "logging.info('loaded transcripts')" + ] + }, + { + "cell_type": "code", + "execution_count": 7, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "200391" + ] + }, + "execution_count": 7, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "maximum_length" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "**Sample audio along with transcript**" + ] + }, + { + "cell_type": "code", + "execution_count": 8, + "metadata": {}, + "outputs": [], + "source": [ + "demo_audio = list(audio_files.keys())[0]" + ] + }, + { + "cell_type": "code", + "execution_count": 9, + "metadata": {}, + "outputs": [ + { + "data": { + "text/html": [ + "\n", + " \n", + " " + ], + "text/plain": [ + "" + ] + }, + "execution_count": 9, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "ipd.Audio(audio_files[demo_audio], rate=sample_rate)" + ] + }, + { + "cell_type": "code", + "execution_count": 10, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "" + ] + }, + "execution_count": 10, + "metadata": {}, + "output_type": "execute_result" + }, + { + "data": { + "image/png": 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d9srPeGFq1d42L3nxhzWBIFfrIvPur5twKEyNNKOYSJrYJhwrFz+jFSkOHy/FZP8F2omk/kj9EWaG82sz1uGntcapxXrH4pVvzzM10UZJznY7V6xI52ZeOXduKyhG28emYu3uItz36RJMmJtvextidWjsP3ICN7y/AKX+WYmhvb/Ho8h1NYPBVhwYN3UNPl0Qflae4uEvlmKPf4hIsy5HyNG9LaS2V96W6Hpz7v1kcdg7NrsWwdW6qPy+0RcUWv0Qqz98A/9WWYf36yU78KFOd7tb/ucPQg8fL6vSm2M0UUG93JIW71wSqzKTdD1hnrfeJ6DyWFe/tv+nke+2eGshnpuyGg9/uTTi57LjwvVTID1Af2clZeV4+ce12F6oH2T3HVd1wk+sLNh8AOv3RNZr9OqM9XhztvHyaA/9T/s9mrvpAFbvOoyVBr3QAHD6Sz8B8PZEAgA4GBL4/7TWWyWZ5m48YKkUTbOsGijzDyeHloJwojahGoMtl8zbdMCx7tOJedsxZ71+L1TrR6fi36pu/WjXS1Qox+p3y3Zh5mr3Jp3u8/fiWH11X5upnYuR5MEpev8zmOG2Q6OXSfkTlEDUTlaG7l6bsR69QmY7mZ0YUu5ynZxo/bJuX2DYKi+/oMqM3Iv/9TsA4IeV2ouLG9mwtwj//mkDZugsTG7GaeNnYtyUVSjx3+GXlFYgd8wUfDQvX+P5juCNWRuw5YB+Eebjpaq/L0ZR/K5Dx5A7Zgouf2sebvkwz7HnMSos++yU1Rj5+hxT+3nYRLkdN70VxahKOMrlz8qhMX/TAYz9pnJCxtrd1pauapZdGWwpN9fKsKJdxYL1MNhyyei35+HLxTvw6vS1juxfAthqcCKcttJ6roKZ5zRLOa6HvvxTlZ8dLy0PuluZtmIXVu00/6FSf2hKysqxbLu5khR61fvd7upXqM8FCyKcafmrQRAORJY/sTC/0PR7n7elAAdUdXz2HD6OLiG5ZKGUIRu9e4KHJi7FDVGu+ekk5X37WJVIPmP1Xs1h3EgNe+UX/G3aWmyIonzL8dIKLMyv7NUu8gfBY7+pmgto9jCJJA8sGv1fqFzJQt1Gu29sjW7ASsIMRz38ReQ9l06bErJ25ORlwbXW7HwVlRUMQt+b/UdKggIqtc8Wbguq9agcX3qlU0KVllcEerSUhHllgepyKdF33Az84MC1EWCw5ap3ftmE12Yad1dHY/BLs/UvyqoD3MwJ0UwBuA/nbsEbM9cbbpM7Zgr2HykJ9LRodaMfDpmlc8dHizHqzTk4cKRqLVyt4Ujlz/n3TxsxYe4WXPDP8At0A/oXEPWH2wtCT05BPQhRimRFgEguZNsLfYFtseokqTVrtuDoCVzk7/HR69matmKXauiLAO/US1POG2/9sgmHjpW6khC+etdhXP7WXFv3GU0vyMS84F7p3DFTAr3xblNyX5VaZFqMZkV/tXh7oKconHNf/xUAsKWgOKh3e/GWQt1zbujLrnz/+izj646ivELidv9EL6VnS8nVWrylEHuLSgxHhaLBYCtBKRfAvTofYnUdHq2LpZIgqhzb780xNwPnQ4Ocmdn+fe7XCJrCKS2X6PXcDMNhsF2HjqGkrDzoRPjcFF/ZCr0cihU7Dnm6V0RNCSwPhFR4vum/+qUDAr9r8towbupqzcfXGqyjZyXWUoIrJSdOadb6PUWas2aTVQ0v0FlmpboV/96470jYz5Be4nM4EsCXESzjs0ln6a3Zqhyf+z9bgmGv/BJRuyKhJHmf89qvQT12pn43zDFltK6k0c/0gqo+Lua3WXX+P+egTKeb+cGJS3WvOXqGvvwznvimcgJSskG3oV6ur9nk9rIKGchJVoItpQj0G7M2+Lfx/W3bCooxK4ph+VAMtlyQH4PKtcq5wkz1ai1KV+pK//Cd1WFH5Rq5raA4cFArdbk2R5EUGjpT68O5+YGv+78wCy//uE4zsFqmczd23htz4qZX5KUffUPOoaUVtHK0Qj36VXSFJ/cW6VfXLyqpmqSvZ5HO5AutEiehJ1D10lBqWrNODx8vNT204JSi46XYV1Ri63AhADzw+VLdGcOK6yK8gSg4WoLpq8JfYEKDkSEv/xy2R0M5l3y1OLJzUiK48yNvlc/p1aqupe1nrfHfhBvcvUXS6Wc2VaNqz5a1J1PnJyszZENHBk6U+R5/Y9Z63PSBfXl/DLZccMbff3L+SaK821dGbJRyD3sOW7tbUe5ABr04Gy/+sAa5Y6YEEhPv/Hgx3vnVeFacnk9CZmX+GHJhmLF6D96cXTWp82hJGVbsOGRYoiDc3Ww0xWHtEM1Qg9aCxlYYvTb3fboEV71jrR4UAJz/xq/4zd9TOXFh1RIfHZ+YFvh5cFtkyPdV993v+Zm4bYJzCdJmdH3qR/QZN8O2panUol1aS8+2Av3Px+KthYH8Oq1SDrvCLHel9Hg8ODE2OUvRVEN3KtXsqMENwB0xDMS2HihGh7HfB9beDKVVsFhNKzgKTf+wQq80yNXvzguaJR7aWuV75ddPf3E2njKoN6gubKrsN3QlAaUth4/ZW7OPwZaL1kY4NdmMaGedVUgZUd2RIxo9FG/97Aus1NPy1XkLVmo0hUvw3qTTa/bclNU47405QUNuoflsEr6A6nedemJ25kbFGydG6pbvOByoIK13Zxt6bMxesxetH50a3DaNxhWfKDecKRfvmtTJwOy1ey1VIV+0pTBQMiQSy7cfCuTWaB0P0SxcbYfQxeiLXe7Z1GLU+zdthTOJ2VrW7SlCSVkFCiO8gXxX42a521M/AogsX1D9sqg/z79t8JXSUIQLgrcUFOO/v+dj8rKdmq91uUawFdoDPmf9fqzZfbjKaM7C/AJ8rropvOqdeYY9/qEYbHmAE7PdtIp8hrr8rbk4VFyqeeIslxKvTre+LIV6EWSzw6WnjZ8VfNA6mIOzZncRHvj8DwCokjQrpcR7czbrLo/S74WZzjUsDLNJ6NEsoaTQShC1mgS/fPsh5I6ZYjqQDj2JKkPBK0NmoSqz7ZQT6dGSMpTrtE0ZXrz+vQV4XicXLV4JAdz4/kJ09V/gzHhm8ir8JYpSA0a5NADQoHa66X050dunlM5Q0woK7LS36Lilz4ZXirsq7VgXwYSYsCKItoyC0Acn/qHatW/nC/3LCSnnjdD34J5PlqDNY1OrTKoqVw0jKsFWaKrNviMlmnmwL05bg0e+9H1+XpuxHr9vPGCp6jyDLQ94LMp8mkgt2FyAjfu1P2xfLd6Bt8IUwDSytaDY0nBp33EzMXGhb4jQTA+S2RkvWr5esgOTl1UNRtfsLsLrs5ybHRoNs7l3kebqqGktEWP1GrHGX/9GveqAUW5Z6OwupU7R10uCk7Vf+sGXt9bmsak4dqIcnf/6g+46gEqbf163D1OWudvrYrdIeg+iHRlTz0jWCjD0SqdoueJte2cH6tVqUybIOOG7pTvRd9xM3PD+QnR76gdTK314J9iKfh95+QWan70VO6Jbw/WzhcGpIuqXTFlR5LL/m4tvluzA/iJfz9zP6/Zp3mie/0ZwvbMy1c7KpUTR8dKgkiyKnQcrb/4nLtyGCXPzA5MsXp+5Huv8o1K7LIzKMNiKMXWXqGKKi93vxx3qao+kkvfDXy7H8dJyDH5ptuF2L05bgzaPTY1qeQWjKuvRKDx6AlOXR7aGWEWF1LyIlZSVR9UjEYncMVOCpnhbXfqocrHfyt8zes0zUpMBhF9A+YTqzvTeTxebbs/OQ8cwdflOx5fkiBlV5KRXlFg5lnYfOo7FWwujykMqLa/AO79WzkjWepf0ZiRqWbL1IIpPlGGGKudy8rLK90dKGVgFI5TWxAe7Jx0tzC/Ee3M244tFvou71hJKyrJLP6/bh8PHyzAuZKmoKzTKTZitGL9qZ/gq9EaklNhWUBzIo6qa5+j7vob/c2fVZwu34dL/m4tf11cNcP7yv+Bz1fHSchQeNR6uVG7KpJSY4S+IrbRx/d4j+Hzh1iq9Tfd//kdg0kz+gWLNG82dh4KPofLyytehokKGnTnZtmEtPPzlMjzxbWUe2CvT1yHVv4i1lbp2ng22pAS+WbIdUkocKi4NrDclpcTzU1djr/+DeLD4RGCG0x0fLcJbP2/EtoJiLNpSiNwxUwLj+JOX7sTnC7dCSok56/djy4GjQQegcjAUHS8N6uJWPsRSShw7UY7Vuw7jro8X40RZBQ4Vl2LTviP4df0+3D4hD9sKirHj4DGUlVdg5c5DeH7Kajw7eRX2FZVg0ZYC/Lhyty09D8avm7WL4lXvzsd8hxfgtKLjE9PCbqMsamtmWz2h+R1WfLFom2bQDACvzVyPuz5eErhorNl9GNsKirH/SAny8guwef9R3PzBQizeWogvF21H7pgpuOCfc1BRIdH3+Rm4+5PKdfMu+7/fsWrnYdd6Zc7/Z+VdoeXi7f7DUD3EN27KKt3NlUTdcMGWevbUDAurFEgJ3PXxEnR8YhqeU7WjrLwCZeUVgec9dKwUq3Yexo6DvjIiJWXl+M1/Ifhp7V5s3n8UpeUVkFLiaEkZflq7F+v2FAVyp6SUuPOjRY7XTVLfeevlpnX+6w8oOHoC/V6YGTTEplWvLpzQ04rWeWbVrqLAa2VGpyd/wC0f5uE/v25CRYXEPZ8swT9nbUDB0RO4bcIinPr8TBw74StwnDtmCp7+biV2HjyGk5+chlPHzcCiLYWYunwXvlq8PSjx2S7PTF6FP/sDhyMRLHA+f3NBoKK9WbljpmDuxgM49/VfMfL1OXhz9nrkjpmCd37ZCCklBoyfhZGv/wopJb5e4jt/FB49gddmrMOgv83CxIVbUVZegdaPTsWgF2fjyW9WYPZaX57jV4t919Pf1u8PBEnpKZGFAAX+66XWLOLQ0jSPfb0cPZ6tWtYl1E9r9wZN5FEfYo98uTwwEzIa5RUSufVrIlkIlFXIsCk86vNRZkZK4Gvlb1yzuyjohjK5dr3GevsSsVpx26qTu3WXx84dF/TYRT1y0LhORmBdsUaZ6YHI9OIeOfhqifX6MInmtdHd8afP/gi/IUXkweEn4ZXp65AkgE0vjAz62fo9RRj+avR1hDo2yUTt9JSo16i0w4LHhqJRnQxMX7UHt1pY/uTpCzrjr5NW4rr+rfDMqC4A9IskAsDlvZtjYt52jL+4K0b3bam7bccmmYZ1jAAgf/xI5I6ZguZ1a2DOI0NMX+xuH9wmqqHz1GSB0vLYn0/TU5JMzTbt1jwLy7Yfwg2n5eLhER3Q6Unjyv1qMx86HUNf/hkA8P2fBuGFqavxi0PFH3OyawSGnHu1qqtbLiRWzurUGI+PPDmwnmEkJt7eHxmpSaYLLIfz1Pmd8NR3+jcvinO6NEHt9BTd5b2yaqRGnTOcP34k3puzGc9MrmzP8qfOQmZGKgBfbuyCzQXIHx98vtT6XE6+dyDO8w/9bRh3Dto9/n1UbauTkaIZECYJoGtOFi7onoNnJ+u/ji3q1sA2//qfmekpgVUVuuTUwYodhwOf+TYNa2HTvqPY9cH9KNm1XrMPOUXrQS8o0zhpheZvqLsAGWj5eKUScaJ6xT9poEL61gSsmVb5EbIj0AKMiyLGWt/nZ2Lj8+da/j1lcsWHc7egS04WvltqPLSqzE4d89VytG5QS3c7K6+NlMCXFurMRRNoAXAl0ALMl/VQas1JKS3NAAaABz+vvIF74PM/HD1G1bl9bgdagK+8zMMjOka1D7sr2JsJtADg+zAzHO3obFm67WBQoAUAhUdL0fWpHzHnkTM1h2D1nKfKsbLj06Q3I1XCV9h76fZDqJGa7F/Gp+ozqh8rUuUFbvPnJyqfeb1Z8GqeHUaMdLaKElIq+QleWbaCEo/SM5A7ZgpmrdmDDo0zXW6RM/41e4Plk/JB1d3yw18sC1uyQ+2KMAU7w1HaerD4BB76n3fXoXPLB3O3WK5BpV5xwks3A7E6vw975ecYPZNztCaT2jH6OurNqr11Sq7YwL/NDpQ4uvTfVWeLGrFjMkG4yTO+r6VuPqPejcyhCGpweTbYUkeU4T5QyUJV3Ez5X1Z+H2bGsubPhc7XXhfrhV+ruxH/8PVm3fTfPFN108wcV3qFBmMl9NlnrNnrZDUO2ymffaMCklqqFExUPaD3lsTrpy3agPpSvb4AACAASURBVNYNoe+BgKNVYuKG2WOwQoa/FtpFa9JX3pZClJVX4MeVuwM510bC5W+aYWYPJ8ordGdbHy8tR1pyUpXXWCvXTQCGXYWeHUZUtzncCxau9z7ce6b1c6nzNZGa1bt8M8eVE8m+VggRfOe3dNtBy6Uf4lHon6j+m/XekmrwsjhOCAQSlo2E/pivvY/R65Akgl+3Kq+hQx9svYkS8zcX4LYJ5irl21HBPSXJ3HGlF4SWlFYgLSUJofdtWr1u4V5Jz/ZsUWSMkv2IzNA6N5lZL88reBGOL1K6f4ORqMK9rE696npr0Vp5n//02ZKo2xGuEG845TpDjJH0ujHYIqKwvqzGiwcTJapYF1ktt1BDxo4F3M0GW8a9g1X3Ecm9AYMtilu10z07Ck4uiqaGGlF1EusORb0Zu06lkmkFSpoMXge7CiEz2KK45dUaceSub1gGhsiUaJY9i4ReOoJTrTAbxBmtkGHXEDeDLYpbDLWIvCXaHBmKnWQhbJnxZ4XZNV5tY8PhaNchzWCL4hZ7tkiLmYXMyRmMteJHarLgDasJdsWjDLYosKhmvOGJgrRs2OudopvVjVtV9Mm6pOoQGXvocGSwRRBxWpqRHVukhYV9icKrDp8Ss7MtY3EpYbBF8FT4b0Gspy1TfIh0qS+iaqUaRFteKt/GYIviFmMt0rJq12G3m0DkefE6omGF0SzDkA0dx2CL4rRfi8EWERHp89I1gsEWxW1Sa7mXPklERHGkOszm9tKfyGCLiIiomvFSPpNTzA4jMkGeiIiIHJD40RZ7toiIiMg1HopDHOOloVIGW0RERNVMdVhpwUtDpQy2iIiIKOF4KNZisEVERETkJAZbRERERA5isEVERETkIAZbRERERA5isEVERETkIAZbRERERA5isEVERETkIFuCLSHECCHEWiHEBiHEGI2fpwshPvf/fL4QIteO5yUiIiLyuqiDLSFEMoA3AZwDoBOAK4UQnUI2uxlAoZSyHYBXAfwt2uclIiIiigd29Gz1BbBBSrlJSnkCwGcARoVsMwrAB/6vvwAwVAghbHhuIiIiIk+zI9jKAbBN9f12/2Oa20gpywAcAlDfhucmIiIi8jQ7gi2tHqrQJYnMbAMhxG1CiDwhRF7x4UIbmkZERETkLjuCre0AWqi+bw5gp942QogUAFkACkJ3JKV8W0rZW0rZu2adujY0jYiIiMhddgRbCwG0F0K0FkKkARgNYFLINpMAXO//+lIAs6SUXlqQm4iIiMgRKdHuQEpZJoS4B8APAJIBvCelXCmEeAZAnpRyEoD/AJgghNgAX4/W6Gifl4iIiCgeRB1sAYCUciqAqSGPPan6+jiAy+x4LiIiIqJ4wgryRERERA5isEVERETkIAZbRERERA5isEVERETkIAZbRERERA5isEVERETkIAZbRERERA5isEVERETkIAZbRERElHCShNstqMRgi4iIqJrJSE38y78Q3om2Ev/VJiIioiAC3glEnOKlv5DBFhERUTXjoU4fx3jpb2SwRUREVM14KRBxitlhxFi8FAy2CKnJ8fmpS/ZS9iMRURzhMGJsMdiiuP3QMdYiIiI9Xuq9Y7BFcctDnyPykO4tst1uApHnSUi3m+C4JLPRVgwuJgy2KG55aVoveUfiX0KIoierwQfFS5cIBluEE+UVbjchIl76IJGHVIerCFGUqsPHJMlklxUT5IkMmO4ipmqlc06W202otmqkJrvdBDKpojpEWzZcIuzKDWawRXGLoRZp4XHhnmOl5W43gUwqLa/gJCMTKmyKSRlsUfziiYKIKCIVMvblc8ac0zGmz+elBE4GW0SUUO48o63bTSCKC7FOxWjbsHZMn6/CZLRlNNnKrqFxBlsUt46WcMiCqmqaVcPtJhDFhVgHWykx7kmrsGHuV7JNURKDrQTTuVkdt5tACeiBYSe53QQislms5xhZGba8sm+LqJ/P7CQAEfJ/8D4qv1aaH8miK3EVbDFFJ7yLezZ3uwkU57TOhx2aZMa+IRHieSK+JInY93iQj1PB1shuTTUfr52RYnoffz6rQ9TtKLOY3R66dUqSCArYlN0lJ1kPnTwbbCndm0mi8uSv97KlJPkWnAkXbQoR+Yk4mmOSp5HE9crlp1ja3sxFxe0LT+j5qXuL7LiqaeZUW7V2q/UY4wZrKqT1i6KaXcM8XhLuEAp3jJs9Bp1aqq2rTvmVHi2yMfvPZyB//Miw+6iVbj4w01Nu4rgyihvSU5JQVi5NvZ7hNvHsYZrifwUqZPipl2UVvoUHysNsJ2XkkxOimdQQywkRsjrUTvGQi3s2R7829fDHk8ORaeKuzcxFJZoLjxP+NLS9202IiJn3wwqtd0XrMY+9fZpmPHi6202wTZzWZDakdwgFOh78G+hd4M0eg07dmAxu3xAAUEf1GbxlUGsIIdC6QS1T+7CjbXpBkvrh1JQk3efKSE1GWYWs8npqFQKXgGGmvWeDrbREvF2hhKLcnX12W39k10xD0fEyl1tkvz65dXFGh4aWE2lPP6lh4OvJ9w7Es6M6G27fpmHlCXjWQ9EFAsr5rk5GKn58YHBU+0pE1/dvZfmm7MwOle/nKdVw7cnZfz4j6n3kZEc/cSP0oh9tXG9HrLXgsaFVHqtbKxXtG9XGwrHD0LOl73gZO7JT2H1lpFZe9+1I3tfLEVN2nZachIoK/R6w4PZUPt6gdrrltng2okn1B1v1aqUFHht/SVf85D/oT2pcG9f1bxX42YSb++ruq0mdjMDXSsQNAB0aZ6Jv63qB728b3Cbw9fWqfQ9s1yCCv8CaWmn2TC/t2IQJ8k765u4BAICTm1Z9ndc+N8L0CbVJnQzdO7xXLj8Fz11oHJzEyrvX9YEQ1gcbzurcGADwxHmd0CUnC9f2zzXcvlfLugCAd67rjTYG08NPbmo+d0wI4KTG2tv3zq2LM05qiLaqIO/jW04N2mbYyY0CJ+sr+hgn63ZqWgfjLuyCe85sZ7p9djn/lGamtjuluW9oJ6tGquFrrOWVy7sHvv7kllNtr5fUv019AL5p9oNVgfqT5wVfoOvWTLX1ec145fJTkBzlhX/6A4Pxvzv629Qi4AuT+zq7c2M8e2GXwPddcuqgUWZloBDt+rKZ6SloVCcDX991WtDjWTVSMf3B05GekowUkx0njTLTg4JaO4KtVJ3nFgAu7N4Mf7/8FJwor9DtCVTnZtVKq+yla17Xd55vUNsXn9x5etuw5357+9ltVCMtGV/eP0gzeHj72l44vUNDpKck44nzOuHQsVI0qJ2Od6/rjdYNayEnuwYOFpdizFfL8H/X9EJGajKWbC2ElBI9W9XDkZIy1EhN1ox6Hzv35MDXT4/qgvIKGbRdSVk5pi3fjVE9cgAAxSfKcPhYGZZuP4izOjUOFIrbe/g4/th2EPVqpaFXq7rYV1SCCgl8Mn8LXp+1ocrzrnxmBHLHTIn6dRvY3npg+P4NfXDjfxdG/dx2OLNDQ8xeu8/x57mwezN888dOy7/XvUU2vv/ToKAAXpGekoxr+rXC36atCfR6KcdakgAKjp5AvVppeP+3fAw9uRH2HC7B5W/NxXMXdsE1/Vrh3k8WY2D7BoFJDukpybiwRw4WbSnE6LfnRfcHRyjLf3Gzet5TTnLqGjVX9m2JTxds1dxeObEO6djIcL+Z6dFdbM/u3BhX9m2JMzpoP0/++JEoK69AkhBIShKQUuJ4aQVqpCXj3iHt0LhORtAJfPeh46idkRJ0PunTuh5OP6mhLZ9nM8aOPBnfLa16LF9wSlO8fHl3tH/8ewBAkr99dw9pZ7mYZc30yvexVnoK+uTWq7LNoPYN8OoV3dH7uRmW9v3lnaehZ8tstH50Kh49pyOuPLUlZq7egzs+Wozr+rfChHlbkJmRgpsGtMbgkxqi57PTcf/Q9rh1cBvsP1KCouNlKKuQuPDN3yw9r1kX92yOXYeORfS7y546C49/tRztdYL+UC3q1sBXdw1An3G+1/Cjm0/FNf+Zj2/uHoDuLbLx10krkF0jDb1z62HNsyNw/XsL8OHNfbF4SyE27y9Gt+ZZ6JKTFTj2WtariR4tstGhSSY+vbUf6tVKw+b9RzF91W48P3VN1EN1r13pC8J7+G+WAKBpVgZqqgKTfm3qY3tBcdh9fXHHaahfqzIQtCP3sfhEcHmgEZ2bYOXOQ9hx8Bi6t8hGq3o1DX8/6HOi+lIJ+lvWq4m8scMBAI+c0xFJT+1cq7cvzwZbgH4vzVmdmwS+Tk1OCnTpDevUOPB4k6xk/PfGyt4u9cFQ20LiXehJKT0lORBoAUDNtBTUTEtBkyxfm5Rku0Z1MoLa2ch/cb6sdwvNYMstX955GrJduFvU89a1vXHS2O8Nt/nwpr647r0FyB8/MuILWr1a1ruBFVq9WoqbB7bGmR0r78zVx1p9/3F608DWAIBW9WsFJYq+cVXPoH1d1tvXm6J1YYuFZU+dFfg60pOy+sZyUPsGusGWkgMR7mkW5BcEvr5tcBu8/csm3W3Vbc6qkYrJ9w5EizAnVwBBd+JCCNTw9zo3r1v1d5tkVQ261UOoTmmWnYGdB48DABrqDGm8NroHhBBY99w5KD5RFrihSk+x3ose2sugdTzkZNewNLyy6flzsaWgONDDu+CxoWiYmQ4hBEZ0aRr4bIQO4ak/M0oS9aqdh00/rxkt69XEv6/pGfi762RYP0c+c0Fn1MlIDfpcC2G8APSvjwwBACwaOwwpSUnIqpka9Pc+fUFlL1VGajI+v93Xw9W/bQP0V9XyzR8/EsdLy5GanITkJIEf7q8cTm/doBZa+j8HB4tLLf9dgO+maNaavcjUeF1SQjLOHxx+Eh4cHr50TMv6NYOGt5Vet7TkJEx/cDDW7i7CbRMWRdReRXKSwLbCY4Gvw1371O1Rp4ko5/IuIRMBZEnxEb19eXYYMVFpnexvOC039g3xS9KZoZmZkRJVjsH9w6wlVdevlYbJ9w5EWkqSZg6A2uCTGpqazWJEb2pytNJSkmwfyk1OEnj/xj627jOc/PEjgy4wVocbAnVrVL83yKDX9USZL9hKCnM7O6Bt/cDXY0aYH8qqnZ5iKtCKR3qvWeBilZKE7Jpphhf5cFKTk/CMKu9O6xlzTSY+A74aSklJwcnSjepkRDys1b6xvZXJG9dJR+dmWYEbK62ZcTMe9AUwT57XCbcOah1IMVBcp3Feb2PyNapfOz3QqxypDJ3RG5/ouo06NsnEorHDNG8E3762t+X9Kak6Qgj85ezgkg8t69dEq/q1cFbnJqjvTyvq0TIbvz58Jp7zD5GO6t5M87ox7OTGQd+rX4/kpCQ01hihAHyzEAEg/0AxJt0zAJPuqXxvP721H3b4A7Z2jcwfdwy2PGDsyJPDb+SAcRd1Qedm2lN0z+rUJKogsFZaCjY+f66pbTs2ycRvY4ZUuUtwyouXdkOvVnWrPN6paR3X3otwztQZ9gqlvoON1LxHq560rJ6a+/lzcM7vVplPpHUXrJAhqb4rnz4bQNWld5R8nvzxI5GUJJA/fiRSw9R8MXtnHU8iCZyinXSkDoS0gqLGdcz3ar1wcbeo2hJKLzfHzjypUO0aZSJ//EjcNLA1Hh/ZCd1NTByIdcV2PXYM0dXX6cWsXztN83GzOoQMuWbXqDxvKMHTS5d2Q4t6NQM9rHVrpgVGjxRNszLw6hXBpXmCgy1fQPrCxV2rtKGjqq5gt+bZ6NY8G8P9z92/bX3cOtg3OqHOKQ+HwZYHmE0gtMJM0HD1qa2QlqL93EnCN1XXKvVUX7N5IV/ddRoy1OtPOXg+GtKxES73D8/ljR1W5efX9m+FOY+cqfm7Cx437nHzAjuKj2oNjVntcWhRrybyx48MDMGFE7qshtKTEDpENqBdg0Cid6BtOgeM8vh9Q9vjkl6JVez3aEkZVjx9NjaZvKEBgH9e3SOqYLw8TI0FpXfSLYufGF7lsUiH4J2qoOOdYMvXjp4tq950mmFYnDSC186oR/v1K3uodu3bebtGvvOc3vs048HTMffRoVVu8NQ1DJXXoFNIWkiPFtl49/qqIwmPjTwZX97pmwgwpGNjvHhJtyo9Z0YYbLmoo4NVuevUiK4LOkmIiLr00zUW7XxtdHfUyUgJ6in7+2WVdxzqZMpw7h1iPNtLL19m3EVdkDd2GN5QfXC18kvSU5I1c3OstjPRGB0JDTPTI6ppdd+QdnjvBt+Qg7r0Q+A5BdAxZPZhl5wsfHvPwCrbhTqleRYGn+T8LGIjmRkpaKoRuNrh8PEy1E5PCTvsqtYoMyOqYHxIx8a42J+vqvW0ZntfnRLay9CinvfWyDR6v167orvuz+zWq1VdXNIzR/dmO1xv8U0Dqt6IK6kdkcSpei/L66O7B32GQoOr0Oe6tFcOnruwi+7wnjqfTOkMyAi5ZuU2qIWGmekYocq5Bny5buoRkcv7tKjyu0YYbLlg/bhzHH+OaO+flJPCVae2BOCbBm+Fcgey8flzMap7DpY9dXbgovj5bf2q9E6YFXoX8uezgoeHBrVvoFnTKUkINKidbliVOFxsaWVihRPOiyLP7AKT5QH0GN2RP3dhF3x086m6P9fz4Fkd0KaB76Q4vFPVO8TNL4xE56bhjxOtpn17z0A8d2HV4YFYWv7U2Zj95zOCykvYJZpjwYjR5I+W9WviFX9AoNWbGDqMU+Xn/pIDv48ZEkULzXOqOno0jHK21BOvnFa3Vhpevrw79h8p0fx5uKVy9IZtI6V3frmge07QTb9eiQZlk79f1h3X9GulvRFChxGVYCv4b1F6v+wO1hlsucDuA1WLcoDq5V2FHmChbhrg+71Mf4DR1kIioJr64B7dxxe4ZdVMNbz7MTpJtqwf3OuknmW66flzcfPA1kEzDZW7ojM6aPd4LXliOP59dU/Nn3mNUiPuvpDevSt6h1+wVe/vNyu3gX5yud7dsRa9JHm9C7V6XbLQmksKrwzNaMlITUbTLHtP2p/ccipeDrNMVGjdI7PSUpJwy8Dw6QOhL/kGEzeQ53b1BYjNbCju6TSnDqlw71usbdirO3lOU7jSLEBkn8f2quuL0a+H5nZaHe9NUdXNUtoZ2julpPXcM6Q9ZkZZYFmNwVaC05ttEZqEGEqpC6McyvcNCT+7MC0lCc9fpN+b0KFJJvq3qa87TGekS04d5I8fWSWhX/1ZS0ryDX2qP5AP+e/Q9C54dWul4ZyuzvQS2E35u0KHam9VFePV/V2T56R/6AxlGL1nkVyXQocccrJraM4wVQ+76A1teDnYckLtjJSIyjeYIeAr+GqVXt7ppapcubEjT8ZyVTkRpymHxZInhuPuM9sab2yR0fnTqHdQa9ipb+t6Uc+utpsQ+vmfy586Szcf98cHBqNhprmJEsqEjRVPn42HVTOLDdcz1BlGNDtzPiVJ4H7/8mOhw4jKuS/Nf57JqpGKthaL/xphsOWi8Zd0c2y2jICvp0e34rbFC5SZRUFH92kRGA7Su7h/elu/oOE4rcrcdWumBnJDAN/yLRNuMj9MpXxW7zi9LS7pmYMlGomzWvRekttNBDOxpu6ZtHNpq7oWZtcooumpDVcRPKtGKpY+6btAq6s5qz04/KTACdSL3IgFI83vtrutymf99sFtkJKcZDgj1Q5aM+Hq1krDX862t+J9hcHdS7ilkN6/ITj5euLtzs2YtOqxcytfJ73JFEbvod6KDVp+f9Q3nBxaYPz0Dg11S92EvrLKS62VQ6YlNTkpUJJDGS5Uyjxk10zFFX1a4NJe4UcKIsFgyyV5Y4ehe4tsRwtW6iVjntI8C3efYe+dHmCth0P5kPztkqpTwFOSkwK5IQDQpmFt3SCgSrcyKk92QviGU80GEP1a19d83Gq1baeoz+HdmldOM9d6DfQoOXh26t+mvukWXNqrOUaqehKza6aFvatX6g2l6LwPNw1sjfs9XNpBed/GXVRZkHJ4p8aGdcesWv3MCHx112m4uGfkeT+D2zcIGpJuUDsdN56Wi6n3DaqyreUAO0YfoV/+UjmTuG7N6EoQGDEKtpSlXPScaWIozi2tGwT35DwSUsvOzrexns77k56SrDvZ4i9nd8Db1/YKfK+c681OFElJFoHzuZIsrwRbyUkCf7ukG7pGmE8cDoMtl0SykKVZ793Q27Bo57f3DAyqbm934vcbV3YP5Gc5Teuc194/LdhqjDS6b2Wb1Xf4Ds0Cj8ojI/QTWLXW8lT+hj4RDBGFY2VG3KjuOXgzwhw5M0Gv3nqTXtCgdjrO7er73F2skQz9x5O+Htgr+1q/s66RloyeLesG0gYiKV3wj9E9MLpvy6BhoL9e0BmdmlUdFjupcW18cUd/9Gujf7PYrXlW5Y1PjKKtWukpyB8/EnMfHYL/OlgI2KikyQPDTwq8l+F8ems/u5rkCCfXBVbOsVaOjGbZNYKuXQPaNQha3zicvPzCQDqC0lOu5DcbDl/agMFWHPjm7gG4sq/54GVIx8aBcWgzh09ocrJWkTcrzj8lJ+rqx9FQLg5WT/DqAGvNsyMCpTnuOL2toyfuSPRq5TvBNK9bA9khd4hGr/1FPYzrTUV6SXT6UtqlWR3NQrShLorhjC6rBCrLh2jlCWbXTMM3dw/AOJdnUSrHlhEhBHrn1jPMl5sUUqIjlppmVf1cKMINlX5+W7+ghbe1vH9DX83HX7q0Gzo2qaP73Aql4HNairu95qH3L6GtaZodfG243oHVTqIZum7fONPSMOxJjWsHkuRDe8qdqq2mYLAVB8xUJtbTIoJk9Et1CkCqx/OjZXboy8xMO8CeJY/UH7b0lGR8c/cALHhsKLJqpOouXBxLWq9YWnISsmqkYuLt/Q3vkrVqumlNZrB64pt8r++C2q5RbYzq3syx/LbJ9w0KuxzMyqfPxj1nGtdhc4P6WP/r+Z0w40HfDCetnrruLbLD9hQaXRQql0my3MyI1AxTtPa2033pCuFy82LpFP8QvN5EgFPb1A+7tJNeEvhlvVuY6oFVtmli80xVq7J06jEqN6oNaqcjf/xI3DKoNb6667TACg7xaETnJnjqgs6qnq3g98lsYn+kogq2hBD1hBDThRDr/f9XOXqFEN2FEHOFECuFEMuEEFdE85zVTbR5He0a1Y5qpot6BthVp+rXL7HKrrsIZTdaSanRXnAyUpPD1g6KJaNjoW/reujfVjvnDPAVAw09Ds7p0qTKdlbfF2WJpVrpKXhtdA88eu7Jrg2N1LJY5DPWJHzJxUrBxdP875dRjs+0+6vmSxlRjvlIPl/hEru1hCv0m5NdA7+NGRJYfN0LlEPkvRv6YNyFXYw31hC6dl+k8sePjGr9WTv8WedvCa17N3Zkp4irzYcT6XqYVg1s3wBCp1j3iqfPdny5uGh7tsYAmCmlbA9gpv/7UMUArpNSdgYwAsA/hBCRd9VUM0P9yZRuzW6/+8x2gUU400PqKcXiLsfs3611mbD6knm9gkAkJTOMRDLzUHFRjxx8oTOT1ijoo0o3DWiNBY8Pxf9d00t3m7o10/DTn88IeszoOFV6JCKp6F9lXyY+D4+c0xFvXavffsAXcMWitmA4Ss+FcrEVAK42KIAZKn/8SKx4+mzccbr9k4vcopeTZWVR8UgJIfD9n6zdTEQjdNiwVLX8VCwKVkf7DKMAnOH/+gMAPwF4RL2BlHKd6uudQoi9ABoCOBjlcyecUac0w7dLdwY9FquoX0/NtJTAzDc7T5h29Wwpd4ah+7v61JY4L8qq6XHBpcPj1RguLZIoQt+qlOQkNMrMQKPMDN3e5/IKidwGtTC8U2NMX7UHgHFdsVsGtUZug1qWpuArQmfvmfmM5mTX0OydsbIodaxkZqRgX1EJBHwV+CNZfsvtVSScZlS82AlGNcnsFjpsWOZwQnyoaK+ejaWUuwDA/79hYosQoi+ANAAbo3zehPR3l6sLd4tyyquV4qB2JdC3a1Qb/7q6B+4Jqao+7qKuli44T53fCa3C5Gl4Rbj4u2UUf4cXZ17Gu/uHRV6WQpkhdeugylw4o/c/u2aabs6lkVXPnB00BDv1vkFR1QD0clAiBPDPq3oGXXxD11WsLkInEbVrlOm5Aqt2Ua+LOKp7s0DuXqyEDbaEEDOEECs0/o2y8kRCiKYAJgC4UUqpuTy8EOI2IUSeECJv3759VnafENzsap/10Ol49/reYbe7pp+qPAJ86+Ip+rUxP3yUk10D654zXuLj41tO1c0pUDu3azPdSvlm3TCgtW4V7HjzUBQ1p4zydpRg/NJe3p3x50W9Tcyi1KN19+1ExfzQXp5OzepEVUbD7R55Tf6X0pNtI8epPzevje4R8wA77NVFSjlMStlF49+3APb4gyglmNqrtQ8hRB0AUwCMlVLOM3iut6WUvaWUvRs2jN9ZD9F4LiRhM1bnhTYNa6NRprWARcJ4YdVwwq2pN6BdA0frkSWqlOQkR4+bv1/GIUQrhBB48rxOGBBBzaI6GrlXdg3B3+lAYWOFl8OZU0J68NOSk9BAo/I8JRa38waj7eudBOB6AOP9/38buoEQIg3A1wA+lFL+L8rnS3ih3e9O1/6wKrTb+bR2DbD2uRGOrdVGVZmpH+bEcfPCxV2xraDY/h1XA5HMxuvYJBP1/Tcb7VQL9dpVfNHJcgxe7DxS1hR97NyTgx6fM+ZMpCYlocez091oFsWI2yuBRBtsjQcwUQhxM4CtAC4DACFEbwB3SClvAXA5gMEA6gshbvD/3g1Syj+ifO5qJdxh8vCIDjh8rCzsfh4POdFEQxkCZ6AVWx1V613qHRedmtbBql2HbX3ezs2yqiwETrGhHvKwY6ah02JVMd6KD27sg6KSsirDiFZ79BOJF4Nip+gtZB8rUX1qpZQHAAzVeDwPwC3+rz8C8FE0z0PhF4Ie0bkJ2phYofyWQdHVu+nZKhsT5m3xfe1Q3RXSF5q8qtfH8eKl3XDeG3Ms799jHamkIRbT8qPlxYt4ozoZxjO4qqFw6zgmIDDmiQAAC1pJREFUEr2F7GMlMTKCE5iSsPxAmBlNZi+S0SaHqpd7ya6mM3i84rt7BuKDG7WXDbH6Nv9LWa+Q0RZRtVGdJgvEdc8WxY7Rwqdm9G9TH3M3HbCpNT5XWVivkexntDq9Uc7WzIdOx7ET5Q60iMgn3OQXolhzO0GenwiPiXS5kXC/1aKeue7i+4a0q1JpV4/bCYcUmbYNa1dZmkJU+YIoMtPuH4S3rw1fRsZrxo60L5+VvMftYIs9Wx5zUuPweVdawo3+mE1YffAse9b9IndFOhtxcPvqWXKF7NOxSeyqghOZZbYTwSns2fKYjk3qVFkLzQ52Ds2/cHFX+3ZGjpARJl+xt9K77E6v8eKMQSKnuH1uY7DlQeqT6pCOjfU3tKCFjUvRnNmhkWaxRfIOs6WYpt43CPMfG+rJ2WMU7F9X9bR1f5EG5ETxyO2eLV4xPUg9BNSyvj1B0rX9W9m2XlmTrAwse+psW/ZFzjBadketUzNlyIfRlte5fWee6KrTzLzqKNJ8aLsw2EoQTbOMC/PVyUjF9aflxqYx5LquOdaKj57cNNPRiuJkzae3noqGIcU27Q4GOIxIANC2YS1s3HfU7WY4LtnlYJrDiAkidCFZqt6sLqrdqn4tLHnyLIdaQ1b1b9sgaIkecl51DT0fryazMFNcrrPFYIsowVWnKtFkXrS1+ygx9G1d3+0mOO7SXs2Rk+3ueZDBFlGCe3C48eoDFB/svi8f3aeFzXukeGRXLq+Xnda2vus5eQy2PIhzhIgolN3XCqtDzYmO+fHkJH7aiIjiAIMBcsqcR87E1acm5vJrD5/dAUM6ur8EeeL3HxIRJQDOHnTWKS2yUaua5rE1r1sT4y5KzGLVd53Zzu0mAGDPVlx5/4Y+bjeBiCgh9WxZFyufGeF2MyhBMdjyIL2ClPVqpcW4JUTkGezYIopbDLbiCBPniYiI4g+DLQ9797reQd9XmFyChQgAGmWmAwDO6dLU5ZaQHdixRRS/GGx52LBOwYtQm13vjggAXr2iOwAWr0wUTbNYnJYoXjHYiiMVjLXIgi45Wbi4Z47bzSCbdGiSifzxI23f77ldm9i+TyIKxmDLg/RiqgpGW2RBVo1UvHJ5d7ebQR53WW9WkidyGoOtOMJYi4iIKP4w2IojkvMRiYiI4g6DLQ9qXCcDzetWTYY9tRqszk5EsfPeDb0xqF0Dt5tBlPC4XI8H1U5PwZxHhlR5PDmJk7+JyD5DOjYOvxERRY09W0REREQOYrBFRERE5CAGWwmgW/Mst5tAREREOhhsJYDRfVq63QQiIiLSwWCLiIiIyEEMthIA628RERF5F4OtBMD1qYmIiLyLwVYCYKxFRETkXQy2EgG7toiIiDyLwVYCYKhFRETkXQy2EgA7toiIiLyLwVYCkIy2iIiIPIvBVgKoYKxFRETkWQy2EgBjLSIiIu9isJUAGtdJd7sJREREpIPBVgIY2bWp200gIiIiHQy2EoAQwu0mEBERkQ4GW0REREQOYrAV5waf1NDtJhAREZGBqIItIUQ9IcR0IcR6//91DbatI4TYIYT4ZzTPScHeGN3D7SYQERGRgWh7tsYAmCmlbA9gpv97Pc8C+DnK56MQWTVT3W4CERERGYg22BoF4AP/1x8AuFBrIyFELwCNAfwY5fORSo3UZLebQERERGFEG2w1llLuAgD//41CNxBCJAF4GcBfwu1MCHGbECJPCJG3b9++KJuW+FY/O8LtJhAREVEYKeE2EELMANBE40ePm3yOuwBMlVJuC1eiQEr5NoC3AaB3794sjE5ERERxL2ywJaUcpvczIcQeIURTKeUuIURTAHs1NusPYJAQ4i4AtQGkCSGOSCmN8ruIiIiIEkLYYCuMSQCuBzDe//+3oRtIKa9WvhZC3ACgNwMtIiIiqi6izdkaD2C4EGI9gOH+7yGE6C2EeDfaxhERERHFu6h6tqSUBwAM1Xg8D8AtGo//F8B/o3lOIiIionjCCvJEREREDmKwRUREROQgBltEREREDmKwRUREROQgBltxZuzIk91uAhEREVnAYCvOhKvCT0RERN7CYCtONa9bw+0mEBERkQkMtoiIiIgcxGArziiDiBxNJCIiig8MtuIMgywiIqL4wmArTknpdguIiIjIDAZbcYbDiERERPGFwVacGd65idtNICIiIgsYbMWZnGxfyYcbT2vtckuIiIjIjBS3G0DWTbi5Lwa2a+B2M4iIiMgEBltxaFD7hm43gYiIiEziMCIRERGRgxhsERERETmIwRYRERGRgxhsERERETmIwRYRERGRgxhsERERETmIwRYRERGRgxhsERERETmIwRYRERGRgxhsERERETlISCndboMmIUQRgLVut4NiogGA/W43gmKC73X1wfe6+uB77dNKSqm5np6X10ZcK6Xs7XYjyHlCiDy+19UD3+vqg+919cH3OjwOIxIRERE5iMEWERERkYO8HGy97XYDKGb4XlcffK+rD77X1Qff6zA8myBPRERElAi83LNFREREFPc8GWwJIUYIIdYKITYIIca43R5yhhCihRBithBitRBipRDiT263iZwjhEgWQiwRQkx2uy3kHCFEthDiCyHEGv9nu7/bbSJnCCEe8J+7VwghPhVCZLjdJq/yXLAlhEgG8CaAcwB0AnClEKKTu60ih5QBeEhKeTKAfgDu5nud0P4EYLXbjSDHvQZgmpSyI4BTwPc8IQkhcgDcB6C3lLILgGQAo91tlXd5LtgC0BfABinlJinlCQCfARjlcpvIAVLKXVLKxf6vi+A7Kee42ypyghCiOYCRAN51uy3kHCFEHQCDAfwHAKSUJ6SUB91tFTkoBUANIUQKgJoAdrrcHs/yYrCVA2Cb6vvt4AU44QkhcgH0ADDf3ZaQQ/4B4GEAFW43hBzVBsA+AO/7h4zfFULUcrtRZD8p5Q4AfwewFcAuAIeklD+62yrv8mKwJTQe45TJBCaEqA3gSwD3SykPu90espcQ4jwAe6WUi9xuCzkuBUBPAP+WUvYAcBQA824TkBCiLnyjTq0BNANQSwhxjbut8i4vBlvbAbRQfd8c7JpMWEKIVPgCrY+llF+53R5yxAAAFwgh8uFLCxgihPjI3SaRQ7YD2C6lVHqov4Av+KLEMwzAZinlPillKYCvAJzmcps8y4vB1kIA7YUQrYUQafAl3E1yuU3kACGEgC+3Y7WU8hW320POkFI+KqVsLqXMhe/zPEtKyTvgBCSl3A1gmxCig/+hoQBWudgkcs5WAP2EEDX95/Kh4GQIXZ5biFpKWSaEuAfAD/DNbnhPSrnS5WaRMwYAuBbAciHEH/7HHpNSTnWxTUQUnXsBfOy/Wd4E4EaX20MOkFLOF0J8AWAxfDPLl4CV5HWxgjwRERGRg7w4jEhERESUMBhsERERETmIwRYRERGRgxhsERERETmIwRYRERGRgzxX+oGIyAohRH0AM/3fNgFQDt+SMQBQLKVkoUUichVLPxBRwhBCPAXgiJTy7263hYhIwWFEIkpYQogj/v/PEEL8LISYKIRYJ4QYL4S4WgixQAixXAjR1r9dQyHEl0KIhf5/A9z9C4goETDYIqLq4hQAfwLQFb6VC06SUvYF8C58Vc8B4DUAr0op+wC4xP8zIqKoMGeLiKqLhVLKXQAghNgI4Ef/48sBnOn/ehiATr6l3gAAdYQQmVLKopi2lIgSCoMtIqouSlRfV6i+r0DluTAJQH8p5bFYNoyIEhuHEYmIKv0I4B7lGyFEdxfbQkQJgsEWEVGl+wD0FkIsE0KsAnCH2w0iovjH0g9EREREDmLPFhEREZGDGGwREREROYjBFhEREZGDGGwREREROYjBFhEREZGDGGwREREROYjBFhEREZGDGGwREREROej/AcrJypzOly38AAAAAElFTkSuQmCC\n", + "text/plain": [ + "
" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "plt.figure(figsize=(10, 5))\n", + "librosa.display.waveplot(audio_files[demo_audio], sr=sample_rate)" + ] + }, + { + "cell_type": "code", + "execution_count": 11, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "' የተለያዩ የ ትግራይ አውራጃ ተወላጆች ገንዘባቸው ን አዋጥ ተው የ ልማት ተቋማትን እንዲ መሰርቱ ትልማ አይ ፈቅድ ም'" + ] + }, + "execution_count": 11, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "transcripts[demo_audio]" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## **Resize Audios For Mono Channel**" + ] + }, + { + "cell_type": "code", + "execution_count": 12, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "(200391,)\n" + ] + } + ], + "source": [ + "audio_files = resize_audios_mono(audio_files, maximum_length)\n", + "print(audio_files[demo_audio].shape)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "**Sample Padded Audio**" + ] + }, + { + "cell_type": "code", + "execution_count": 13, + "metadata": {}, + "outputs": [ + { + "data": { + "text/html": [ + "\n", + " \n", + " " + ], + "text/plain": [ + "" + ] + }, + "execution_count": 13, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "ipd.Audio(audio_files[demo_audio], rate=sample_rate)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "**Waveplot For Padded Audio**" + ] + }, + { + "cell_type": "code", + "execution_count": 14, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "" + ] + }, + "execution_count": 14, + "metadata": {}, + "output_type": "execute_result" + }, + { + "data": { + "image/png": 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\n", + "text/plain": [ + "
" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "plt.figure(figsize=(10, 5))\n", + "librosa.display.waveplot(audio_files[demo_audio], sr= sample_rate)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## **Augment Audios**" + ] + }, + { + "cell_type": "code", + "execution_count": 15, + "metadata": {}, + "outputs": [], + "source": [ + "audio_files = augment_audio(audio_files, sample_rate)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## **Extract Features**" + ] + }, + { + "cell_type": "code", + "execution_count": 16, + "metadata": {}, + "outputs": [], + "source": [ + "feature_extractor = FeatureExtraction()" + ] + }, + { + "cell_type": "code", + "execution_count": 17, + "metadata": {}, + "outputs": [], + "source": [ + "mfcc_features = feature_extractor.extract_features(audio_files, sample_rate)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "**Plot MFCCs**" + ] + }, + { + "cell_type": "code", + "execution_count": 18, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "(20, 392)\n" + ] + }, + { + "data": { + "text/plain": [ + "" + ] + }, + "execution_count": 18, + "metadata": {}, + "output_type": "execute_result" + }, + { + "data": { + "image/png": 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\n", + "text/plain": [ + "
" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "fig, ax = plt.subplots()\n", + "ax = plt.Axes(fig, [0., 0., 1., 1.])\n", + "ax.set_axis_off()\n", + "fig.add_axes(ax)\n", + "mfccs = mfcc_features[demo_audio]\n", + "print(mfccs.shape)\n", + "librosa.display.specshow(mfccs, sr=sample_rate, x_axis='time')" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "**Plot Mel Spectrogram**" + ] + }, + { + "cell_type": "code", + "execution_count": 19, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "" + ] + }, + "execution_count": 19, + "metadata": {}, + "output_type": "execute_result" + }, + { + "data": { + "image/png": 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\n", 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\n", 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\n", + "text/plain": [ + "" + ] + }, + "execution_count": 23, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "ipd.Image(filename=f'../data/train/mel_spectros/{demo_audio}.png')" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "**Fit Label Encoder with the Characters in the Transcripts**" + ] + }, + { + "cell_type": "code", + "execution_count": 24, + "metadata": {}, + "outputs": [], + "source": [ + "char_encoder = fit_label_encoder(transcripts)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "**Encode the Characters in the Transcripts**" + ] + }, + { + "cell_type": "code", + "execution_count": 25, + "metadata": {}, + "outputs": [], + "source": [ + "transcripts_encoded = encode_transcripts(transcripts, char_encoder)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "**Equalize transcript length by padding with spaces**" + ] + }, + { + "cell_type": "code", + "execution_count": 26, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "maximum number of characters in a transcript: 164\n" + ] + } + ], + "source": [ + "enc_aug_transcripts = equalize_transcript_dimension(transcripts_encoded, 20)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## **Prepare Training Set**" + ] + }, + { + "cell_type": "code", + "execution_count": 25, + "metadata": {}, + "outputs": [], + "source": [ + "# X_train, y_train = load_spectrograms_with_transcripts(mfcc_features, \n", + "# enc_aug_transcripts,\n", + "# '../data/train/mfcc_spectros/')\n", + "# X_train.shape, len(y_train)" + ] + }, + { + "cell_type": "code", + "execution_count": 34, + "metadata": {}, + "outputs": [], + "source": [ + "# X_train, y_train = load_spectrograms_with_transcripts_in_batches(mfcc_features, \n", + "# enc_aug_transcripts, 4, 0,\n", + "# '../data/train/mfcc_spectros/')\n", + "# X_train.shape, y_train.shape" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## **Deep Learning Model**" + ] + }, + { + "cell_type": "code", + "execution_count": 27, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "'2.2.0'" + ] + }, + "execution_count": 27, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "import tensorflow as tf\n", + "tf.__version__" + ] + }, + { + "cell_type": "code", + "execution_count": 28, + "metadata": { + "scrolled": true + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Model: \"ocr_model_v1\"\n", + "__________________________________________________________________________________________________\n", + "Layer (type) Output Shape Param # Connected to \n", + "==================================================================================================\n", + "image (InputLayer) [(None, 400, 600, 4) 0 \n", + "__________________________________________________________________________________________________\n", + "Conv1 (Conv2D) (None, 400, 600, 32) 1184 image[0][0] \n", + "__________________________________________________________________________________________________\n", + "pool1 (MaxPooling2D) (None, 200, 300, 32) 0 Conv1[0][0] \n", + "__________________________________________________________________________________________________\n", + "reshape (Reshape) (None, 200, 9600) 0 pool1[0][0] \n", + "__________________________________________________________________________________________________\n", + "dense1 (Dense) (None, 200, 64) 614464 reshape[0][0] \n", + "__________________________________________________________________________________________________\n", + "dropout (Dropout) (None, 200, 64) 0 dense1[0][0] \n", + "__________________________________________________________________________________________________\n", + "bidirectional (Bidirectional) (None, 200, 256) 197632 dropout[0][0] \n", + "__________________________________________________________________________________________________\n", + "bidirectional_1 (Bidirectional) (None, 200, 128) 164352 bidirectional[0][0] \n", + "__________________________________________________________________________________________________\n", + "label (InputLayer) [(None, None)] 0 \n", + "__________________________________________________________________________________________________\n", + "dense2 (Dense) (None, 200, 223) 28767 bidirectional_1[0][0] \n", + "__________________________________________________________________________________________________\n", + "ctc_loss (CTCLayer) (None, 200, 223) 0 label[0][0] \n", + "==================================================================================================\n", + "Total params: 1,006,399\n", + "Trainable params: 1,006,399\n", + "Non-trainable params: 0\n", + "__________________________________________________________________________________________________\n" + ] + } + ], + "source": [ + "model = model_1(char_encoder)\n", + "model.summary()" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## **Train Model**" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "This module loads data_batch_size spectrograms at a time and trains the model for the given number of epochs and with a given training_batch_size." + ] + }, + { + "cell_type": "code", + "execution_count": 46, + "metadata": { + "scrolled": true + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Epoch 1: training batch 0\n", + "2/2 [==============================] - 1s 547ms/step - loss: 9.9330\n", + "Epoch 2: training batch 0\n", + "2/2 [==============================] - 1s 610ms/step - loss: 9.8221\n", + "Epoch 3: training batch 0\n", + "2/2 [==============================] - 1s 552ms/step - loss: 9.5274\n", + "Epoch 4: training batch 0\n", + "2/2 [==============================] - 1s 515ms/step - loss: 9.6992\n", + "Epoch 5: training batch 0\n", + "2/2 [==============================] - 1s 492ms/step - loss: 9.8245\n", + "Epoch 6: training batch 0\n", + "2/2 [==============================] - 1s 487ms/step - loss: 9.5080\n", + "Epoch 7: training batch 0\n", + "2/2 [==============================] - 1s 501ms/step - loss: 9.8121\n", + "Epoch 8: training batch 0\n", + "2/2 [==============================] - 1s 497ms/step - loss: 9.6737\n", + "Epoch 9: training batch 0\n", + "2/2 [==============================] - 1s 522ms/step - loss: 9.3763\n", + "Epoch 10: training batch 0\n", + "2/2 [==============================] - 1s 493ms/step - loss: 9.5555\n", + "Epoch 11: training batch 0\n", + "2/2 [==============================] - 1s 499ms/step - loss: 9.5716\n", + "Epoch 12: training batch 0\n", + "2/2 [==============================] - 1s 495ms/step - loss: 9.2393\n", + "Epoch 13: training batch 0\n", + "2/2 [==============================] - 1s 486ms/step - loss: 9.6243\n", + "Epoch 14: training batch 0\n", + "2/2 [==============================] - 1s 486ms/step - loss: 9.2361\n", + "Epoch 15: training batch 0\n", + "2/2 [==============================] - 1s 490ms/step - loss: 9.4999\n", + "Epoch 16: training batch 0\n", + "2/2 [==============================] - 1s 485ms/step - loss: 13.8971\n", + "Epoch 17: training batch 0\n", + "2/2 [==============================] - 1s 491ms/step - loss: 14.6708\n", + "Epoch 18: training batch 0\n", + "2/2 [==============================] - 1s 548ms/step - loss: 11.6119\n", + "Epoch 19: training batch 0\n", + "2/2 [==============================] - 1s 491ms/step - loss: 12.5770\n", + "Epoch 20: training batch 0\n", + "2/2 [==============================] - 1s 495ms/step - loss: 12.9739\n", + "Epoch 21: training batch 0\n", + "2/2 [==============================] - 1s 527ms/step - loss: 11.9551\n", + "Epoch 22: training batch 0\n", + "2/2 [==============================] - 1s 490ms/step - loss: 12.5808\n", + "Epoch 23: training batch 0\n", + "2/2 [==============================] - 1s 509ms/step - loss: 12.3561\n", + "Epoch 24: training batch 0\n", + "2/2 [==============================] - 1s 498ms/step - loss: 12.3167\n", + "Epoch 25: training batch 0\n", + "2/2 [==============================] - 1s 496ms/step - loss: 11.2651\n", + "Epoch 26: training batch 0\n", + "2/2 [==============================] - 1s 493ms/step - loss: 12.3103\n", + "Epoch 27: training batch 0\n", + "2/2 [==============================] - 1s 493ms/step - loss: 11.6182\n", + "Epoch 28: training batch 0\n", + "2/2 [==============================] - 1s 490ms/step - loss: 11.9412\n", + "Epoch 29: training batch 0\n", + "2/2 [==============================] - 1s 492ms/step - loss: 11.7609\n", + "Epoch 30: training batch 0\n", + "2/2 [==============================] - 1s 496ms/step - loss: 13.0226\n", + "Epoch 31: training batch 0\n", + "2/2 [==============================] - 1s 484ms/step - loss: 11.2963\n", + "Epoch 32: training batch 0\n", + "2/2 [==============================] - 1s 490ms/step - loss: 11.8948\n", + "Epoch 33: training batch 0\n", + "2/2 [==============================] - 1s 503ms/step - loss: 11.5651\n", + "Epoch 34: training batch 0\n", + "2/2 [==============================] - 1s 518ms/step - loss: 10.8037\n", + "Epoch 35: training batch 0\n", + "2/2 [==============================] - 1s 491ms/step - loss: 10.2351\n", + "Epoch 36: training batch 0\n", + "2/2 [==============================] - 1s 483ms/step - loss: 10.4666\n", + "Epoch 37: training batch 0\n", + "2/2 [==============================] - 1s 483ms/step - loss: 10.2531\n", + "Epoch 38: training batch 0\n", + "2/2 [==============================] - 1s 493ms/step - loss: 10.1900\n", + "Epoch 39: training batch 0\n", + "2/2 [==============================] - 1s 484ms/step - loss: 9.7024\n", + "Epoch 40: training batch 0\n", + "2/2 [==============================] - 1s 492ms/step - loss: 9.7461\n", + "Epoch 41: training batch 0\n", + "2/2 [==============================] - 1s 487ms/step - loss: 9.4322\n", + "Epoch 42: training batch 0\n", + "2/2 [==============================] - 1s 485ms/step - loss: 9.3189\n", + "Epoch 43: training batch 0\n", + "2/2 [==============================] - 1s 491ms/step - loss: 9.0496\n", + "Epoch 44: training batch 0\n", + "2/2 [==============================] - 1s 506ms/step - loss: 9.0522\n", + "Epoch 45: training batch 0\n", + "2/2 [==============================] - 1s 498ms/step - loss: 9.0502\n", + "Epoch 46: training batch 0\n", + "2/2 [==============================] - 1s 500ms/step - loss: 8.9161\n", + "Epoch 47: training batch 0\n", + "2/2 [==============================] - 1s 482ms/step - loss: 8.7722\n", + "Epoch 48: training batch 0\n", + "2/2 [==============================] - 1s 509ms/step - loss: 8.7449\n", + "Epoch 49: training batch 0\n", + "2/2 [==============================] - 1s 478ms/step - loss: 8.4528\n", + "Epoch 50: training batch 0\n", + "2/2 [==============================] - 1s 487ms/step - loss: 8.6229\n", + "Epoch 51: training batch 0\n", + "2/2 [==============================] - 1s 495ms/step - loss: 8.6585\n", + "Epoch 52: training batch 0\n", + "2/2 [==============================] - 1s 489ms/step - loss: 8.3667\n", + "Epoch 53: training batch 0\n", + "2/2 [==============================] - 1s 490ms/step - loss: 8.2179\n", + "Epoch 54: training batch 0\n", + "2/2 [==============================] - 1s 484ms/step - loss: 8.2233\n", + "Epoch 55: training batch 0\n", + "2/2 [==============================] - 1s 484ms/step - loss: 8.1195\n", + "Epoch 56: training batch 0\n", + "2/2 [==============================] - 1s 498ms/step - loss: 8.3913\n", + "Epoch 57: training batch 0\n", + "2/2 [==============================] - 1s 489ms/step - loss: 8.1767\n", + "Epoch 58: training batch 0\n", + "2/2 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[==============================] - 1s 573ms/step - loss: 7.4664\n", + "Epoch 77: training batch 0\n", + "2/2 [==============================] - 1s 520ms/step - loss: 8.0552\n", + "Epoch 78: training batch 0\n", + "2/2 [==============================] - 1s 496ms/step - loss: 8.0745\n", + "Epoch 79: training batch 0\n", + "2/2 [==============================] - 1s 484ms/step - loss: 8.6436\n", + "Epoch 80: training batch 0\n", + "2/2 [==============================] - 1s 508ms/step - loss: 8.6005\n", + "Epoch 81: training batch 0\n", + "2/2 [==============================] - 1s 511ms/step - loss: 8.0689\n", + "Epoch 82: training batch 0\n", + "2/2 [==============================] - 1s 555ms/step - loss: 8.4664\n", + "Epoch 83: training batch 0\n", + "2/2 [==============================] - 1s 580ms/step - loss: 8.4581\n", + "Epoch 84: training batch 0\n", + "2/2 [==============================] - 1s 531ms/step - loss: 8.1449\n", + "Epoch 85: training batch 0\n", + "2/2 [==============================] - 1s 596ms/step - loss: 7.6878\n", + "Epoch 86: training batch 0\n", + "2/2 [==============================] - 1s 525ms/step - loss: 7.8021\n", + "Epoch 87: training batch 0\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "2/2 [==============================] - 1s 530ms/step - loss: 8.5794\n", + "Epoch 88: training batch 0\n", + "2/2 [==============================] - 1s 506ms/step - loss: 7.8884\n", + "Epoch 89: training batch 0\n", + "2/2 [==============================] - 1s 516ms/step - loss: 7.9601\n", + "Epoch 90: training batch 0\n", + "2/2 [==============================] - 1s 546ms/step - loss: 7.8547\n", + "Epoch 91: training batch 0\n", + "2/2 [==============================] - 1s 566ms/step - loss: 8.1808\n", + "Epoch 92: training batch 0\n", + "2/2 [==============================] - 1s 668ms/step - loss: 8.2037\n", + "Epoch 93: training batch 0\n", + "2/2 [==============================] - 1s 572ms/step - loss: 7.7512\n", + "Epoch 94: training batch 0\n", + "2/2 [==============================] - 1s 552ms/step - loss: 7.9144\n", + "Epoch 95: training batch 0\n", + "2/2 [==============================] - 1s 487ms/step - loss: 7.5426\n", + "Epoch 96: training batch 0\n", + "2/2 [==============================] - 1s 478ms/step - loss: 7.6200\n", + "Epoch 97: training batch 0\n", + "2/2 [==============================] - 1s 475ms/step - loss: 7.7152\n", + "Epoch 98: training batch 0\n", + "2/2 [==============================] - 1s 472ms/step - loss: 7.2939\n", + "Epoch 99: training batch 0\n", + "2/2 [==============================] - 1s 470ms/step - loss: 7.4473\n", + "Epoch 100: training batch 0\n", + "2/2 [==============================] - 1s 478ms/step - loss: 7.3207\n" + ] + } + ], + "source": [ + "import math\n", + "\n", + "data_batch_size = 9\n", + "training_batch_size = 5\n", + "number_of_epochs = 100\n", + "\n", + "number_of_batches = math.ceil(len(mfcc_features)/data_batch_size)\n", + "\n", + "for i in range(number_of_epochs):\n", + " for j in range(number_of_batches):\n", + " print(f'Epoch {i+1}: training batch {j}')\n", + " X_train, y_train = load_spectrograms_with_transcripts_in_batches(mfcc_features, \n", + " enc_aug_transcripts, data_batch_size, j,\n", + " '../data/train/mel_spectros/')\n", + " history = model.fit([X_train, y_train], batch_size = training_batch_size, epochs = 1)\n", + "with mlflow.start_run() as run:\n", + " mlflow.log_metric(\"ctc_loss\", history.history['loss'][-1])" + ] + }, + { + "cell_type": "code", + "execution_count": 49, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "pridicted: የ ጠመንኩስ ተ ና አ\n", + "actual: የ ጠመንጃ ተኩስ ተከፈተ ና አ\n" + ] + } + ], + "source": [ + "predicted = model.predict([X_train,y_train])\n", + "predicted_trans = decode_predicted(predicted, char_encoder)\n", + "real_trans = [''.join(char_encoder.inverse_transform(y)) for y in y_train]\n", + "print(\"pridicted:\",predicted_trans[1])\n", + "print(\"actual:\",real_trans[1])" + ] + }, + { + "cell_type": "code", + "execution_count": 48, + "metadata": {}, + "outputs": [], + "source": [ + "#[np.argmax(pred) for pred in predicted[0]]" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [] + } + ], + "metadata": { + "kernelspec": { + "display_name": "Python 3", + "language": "python", + "name": "python3" + }, + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 3 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython3", + "version": "3.7.1" + } + }, + "nbformat": 4, + "nbformat_minor": 2 +} diff --git a/notebooks/ModelBuilding.ipynb b/notebooks/ModelBuilding.ipynb new file mode 100755 index 0000000..592ea9c --- /dev/null +++ b/notebooks/ModelBuilding.ipynb @@ -0,0 +1,2323 @@ +{ + "cells": [ + { + "cell_type": "code", + "execution_count": 42, + "id": "c34a6094", + "metadata": { + "executionInfo": { + "elapsed": 2895, + "status": "ok", + "timestamp": 1628699389341, + "user": { + "displayName": "Daniel Zelalem", + "photoUrl": "", + "userId": "17933366000899068375" + }, + "user_tz": -180 + }, + "id": "c34a6094" + }, + "outputs": [], + "source": [ + "import os\n", + "import sys\n", + "sys.path.append(os.path.abspath(os.path.join('../scripts')))\n", + "sys.path.append(os.path.abspath(os.path.join('./scripts')))\n", + "import pandas as pd\n", + "import IPython.display as ipd\n", + "import matplotlib.pyplot as plt\n", + "import numpy as np\n", + "from scipy.io import wavfile #for audio processing\n", + "import os\n", + "import pickle\n", + "import pandas as pd\n", + "from collections import Counter\n", + "import librosa\n", + "import tensorflow as tf\n", + "from tensorflow.keras.models import Model, Sequential\n", + "from tensorflow.keras.layers import * \n", + "from tensorflow.keras.callbacks import Callback, ModelCheckpoint\n", + "from tensorflow.keras.preprocessing.sequence import pad_sequences\n", + "from tensorflow.keras.optimizers import SGD, Adam, RMSprop\n", + "from tensorflow.keras import backend as K\n", + "from jiwer import wer\n", + "import random\n", + "\n", + "\n", + "import mlflow" + ] + }, + { + "cell_type": "code", + "execution_count": 80, + "id": "cef121c6", + "metadata": {}, + "outputs": [], + "source": [ + "import warnings\n", + "warnings.filterwarnings('ignore')" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "14DrOASH1-ag", + "metadata": { + "executionInfo": { + "elapsed": 1707, + "status": "ok", + "timestamp": 1628689887618, + "user": { + "displayName": "Daniel Zelalem", + "photoUrl": "", + "userId": "17933366000899068375" + }, + "user_tz": -180 + }, + "id": "14DrOASH1-ag" + }, + "outputs": [], + "source": [ + "# !ln -s ./drive/MyDrive/SST/data/ ./\n", + "# !ln -s ./drive/MyDrive/SST/scripts/* ./" + ] + }, + { + "cell_type": "code", + "execution_count": 3, + "id": "IQLOtaNr2GSB", + "metadata": { + "colab": { + "base_uri": "https://localhost:8080/" + }, + "executionInfo": { + "elapsed": 625, + "status": "ok", + "timestamp": 1628689876631, + "user": { + "displayName": "Daniel Zelalem", + "photoUrl": "", + "userId": "17933366000899068375" + }, + "user_tz": -180 + }, + "id": "IQLOtaNr2GSB", + "outputId": "05b3d77e-6ba7-43fc-8256-92e5e2539d74" + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Drive already mounted at /content/drive; to attempt to forcibly remount, call drive.mount(\"/content/drive\", force_remount=True).\n" + ] + } + ], + "source": [ + "# from google.colab import drive\n", + "# drive.mount('/content/drive')" + ] + }, + { + "cell_type": "code", + "execution_count": 32, + "id": "3f315bab", + "metadata": {}, + "outputs": [], + "source": [ + "# !pip3 install jiwer\n" + ] + }, + { + "cell_type": "code", + "execution_count": 43, + "id": "acf88600", + "metadata": { + "executionInfo": { + "elapsed": 981, + "status": "ok", + "timestamp": 1628699393166, + "user": { + "displayName": "Daniel Zelalem", + "photoUrl": "", + "userId": "17933366000899068375" + }, + "user_tz": -180 + }, + "id": "acf88600" + }, + "outputs": [], + "source": [ + "import helper\n" + ] + }, + { + "cell_type": "code", + "execution_count": 60, + "id": "4f219ca9", + "metadata": { + "executionInfo": { + "elapsed": 4, + "status": "ok", + "timestamp": 1628699394673, + "user": { + "displayName": "Daniel Zelalem", + "photoUrl": "", + "userId": "17933366000899068375" + }, + "user_tz": -180 + }, + "id": "4f219ca9" + }, + "outputs": [], + "source": [ + "from data_generator import DataGenerator\n", + "from tokenizer import Tokenizer\n", + "from logspectrorgam import LogMelSpectrogram\n", + "from ctc_loss import CTC_loss\n", + "from model2 import simple_rnn_model, CNN_net, BidirectionalRNN2, cnn_rnn_model" + ] + }, + { + "cell_type": "markdown", + "id": "a808c537", + "metadata": {}, + "source": [ + "### Defining hop_size for our audio features " + ] + }, + { + "cell_type": "markdown", + "id": "fc6c9b55", + "metadata": {}, + "source": [ + "### Init CTC_loss class" + ] + }, + { + "cell_type": "code", + "execution_count": 46, + "id": "e464cd2c", + "metadata": {}, + "outputs": [], + "source": [ + "frame_step = 256\n", + "ctc = CTC_loss(frame_step)" + ] + }, + { + "cell_type": "markdown", + "id": "a1e2ce09", + "metadata": {}, + "source": [ + "### Defination of preprocessing model" + ] + }, + { + "cell_type": "markdown", + "id": "8498d74e", + "metadata": {}, + "source": [ + "- This model uses LogMelSpectrogram to generate features of an audio data at run time\n", + "- We will use this model as a part of our speech to text models to convert audio data to log melspectrogram" + ] + }, + { + "cell_type": "code", + "execution_count": 47, + "id": "09c8fa57", + "metadata": { + "executionInfo": { + "elapsed": 623, + "status": "ok", + "timestamp": 1628699400742, + "user": { + "displayName": "Daniel Zelalem", + "photoUrl": "", + "userId": "17933366000899068375" + }, + "user_tz": -180 + }, + "id": "09c8fa57" + }, + "outputs": [], + "source": [ + "def preprocessin_model(sample_rate, fft_size, frame_step, n_mels, mfcc=False):\n", + "\n", + " input_data = Input(name='input', shape=(None,), dtype=\"float32\")\n", + " featLayer = LogMelSpectrogram(\n", + " fft_size=fft_size,\n", + " hop_size=frame_step,\n", + " n_mels=n_mels,\n", + " \n", + " sample_rate=sample_rate,\n", + " f_min=0.0,\n", + " \n", + " f_max=int(sample_rate / 2),\n", + " )(input_data)\n", + " \n", + " x = BatchNormalization(axis=2)(featLayer)\n", + " model = Model(inputs=input_data, outputs=x, name=\"preprocessin_model\")\n", + "\n", + " return model" + ] + }, + { + "cell_type": "markdown", + "id": "84ea3e3e", + "metadata": {}, + "source": [ + "### Model trainer function" + ] + }, + { + "cell_type": "code", + "execution_count": 48, + "id": "7abeb89a", + "metadata": { + "executionInfo": { + "elapsed": 542, + "status": "ok", + "timestamp": 1628699406370, + "user": { + "displayName": "Daniel Zelalem", + "photoUrl": "", + "userId": "17933366000899068375" + }, + "user_tz": -180 + }, + "id": "7abeb89a" + }, + "outputs": [], + "source": [ + "def train(model_builder, \n", + " data_gen,\n", + " batch_size = 32,\n", + " epochs=20, \n", + " verbose=1,\n", + " save_path=\"../models/model.h5\",\n", + " optimizer=SGD(learning_rate=0.01, decay=1e-6, momentum=0.9, nesterov=True, clipnorm=5),\n", + " ): \n", + " \n", + " model = ctc.add_ctc_loss(model_builder)\n", + "\n", + " checkpointer = ModelCheckpoint(filepath=save_path, verbose=0)\n", + " model.compile(loss={'ctc': lambda y_true, y_pred: y_pred}, optimizer=optimizer)\n", + " print(model.summary())\n", + "\n", + "\n", + " hist = model.fit_generator(generator=data_gen,\n", + " callbacks=[checkpointer],\n", + "\n", + " epochs=epochs,\n", + " verbose=verbose, \n", + " use_multiprocessing=False)\n", + " return model" + ] + }, + { + "cell_type": "markdown", + "id": "dbd30b71", + "metadata": {}, + "source": [ + "### Loading our audio data and translation data from pickle file\n", + "\n", + "- audio_obj is a key value pair dict where the key is the file name of the audio and value is the audio data\n", + "- translation_obj is a key value pair dict where the key is the file name of the audio and value is the transcription \n" + ] + }, + { + "cell_type": "markdown", + "id": "4a07f40f", + "metadata": {}, + "source": [ + "#### The metadata is a pandas dataframe which holds meta data information for each audio" + ] + }, + { + "cell_type": "code", + "execution_count": 49, + "id": "3f654a55", + "metadata": { + "colab": { + "base_uri": "https://localhost:8080/" + }, + "executionInfo": { + "elapsed": 2912, + "status": "ok", + "timestamp": 1628699411261, + "user": { + "displayName": "Daniel Zelalem", + "photoUrl": "", + "userId": "17933366000899068375" + }, + "user_tz": -180 + }, + "id": "3f654a55", + "outputId": "c01d68d8-1b78-41f1-ea6f-6345db44bff8" + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "file read as csv\n" + ] + } + ], + "source": [ + "\n", + "translation_obj = helper.read_obj(\"../data/translation_dict.pkl\")\n", + "audio_obj = helper.read_obj(\"../data/audio_dict.pkl\")\n", + "meta_data = helper.read_csv(\"../data/meta_data.csv\")\n" + ] + }, + { + "cell_type": "markdown", + "id": "317f5cac", + "metadata": {}, + "source": [ + "#### Sorting the audios based on the duration using the metadata" + ] + }, + { + "cell_type": "code", + "execution_count": 50, + "id": "xO7gtHd07skA", + "metadata": { + "colab": { + "base_uri": "https://localhost:8080/", + "height": 504 + }, + "executionInfo": { + "elapsed": 11, + "status": "ok", + "timestamp": 1628699411262, + "user": { + "displayName": "Daniel Zelalem", + "photoUrl": "", + "userId": "17933366000899068375" + }, + "user_tz": -180 + }, + "id": "xO7gtHd07skA", + "outputId": "028c0876-dfa9-45f3-d192-5297099bddf5" + }, + "outputs": [ + { + "data": { + "text/html": [ + "
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translationlabelchannelsample_rateduration
4133እኛ ም እ ኮ ፉትቦል ን እንወዳ ለ ንtr_3933_tr40034180002.048
1476አሸናፊ ፈጣን ተጨዋች ነውtr_1541_tr16042180002.048
408እንስራ ው ተ ሸነቆረtr_10369_tr100091180002.176
73ጥያቄ ያችን ጆንያ ሙሉ ነውtr_10067_tr098029180002.176
3574ኳስ ጨዋታ ኳስ ነውtr_342_tr04042180002.176
..................
2614በ አውሮፕላኗ ተመትቶ መውደቅ ሳቢያ ዜጐቻቸው ን ላ ጡት የ ብሪታኒያ ና ...tr_2566_tr260671800020.352
1652ሁሴን አይዲድ እንደ ገለጹት ኢትዮጵያ ሁኔታዎች ከ ተመቻቹ ላት ሶማሊያ ን...tr_16_tr010161800020.736
2222ከ ግዛታቸው ዋ ና ከተማ ጋሪ ስ ሆነው በ ስልክ ሚስተር ሞሪስ ከ ስደተኞ...tr_2212_tr230131800020.992
2608የተ ለቀቁት ምርኮኞች በ አካባቢያቸው ሰላማዊ ኑሮ እንዲ ኖሩ የ ትራንስፖ...tr_2560_tr260611800021.120
2613የ ትምህርት ደረጃቸው ንና የ አገልግሎት ሁኔታ ቸውን ስን መረምር የሚ ደ...tr_2565_tr260661800022.784
\n", + "

5000 rows × 5 columns

\n", + "
" + ], + "text/plain": [ + " translation label \\\n", + "4133 እኛ ም እ ኮ ፉትቦል ን እንወዳ ለ ን tr_3933_tr40034 \n", + "1476 አሸናፊ ፈጣን ተጨዋች ነው tr_1541_tr16042 \n", + "408 እንስራ ው ተ ሸነቆረ tr_10369_tr100091 \n", + "73 ጥያቄ ያችን ጆንያ ሙሉ ነው tr_10067_tr098029 \n", + "3574 ኳስ ጨዋታ ኳስ ነው tr_342_tr04042 \n", + "... ... ... \n", + "2614 በ አውሮፕላኗ ተመትቶ መውደቅ ሳቢያ ዜጐቻቸው ን ላ ጡት የ ብሪታኒያ ና ... tr_2566_tr26067 \n", + "1652 ሁሴን አይዲድ እንደ ገለጹት ኢትዮጵያ ሁኔታዎች ከ ተመቻቹ ላት ሶማሊያ ን... tr_16_tr01016 \n", + "2222 ከ ግዛታቸው ዋ ና ከተማ ጋሪ ስ ሆነው በ ስልክ ሚስተር ሞሪስ ከ ስደተኞ... tr_2212_tr23013 \n", + "2608 የተ ለቀቁት ምርኮኞች በ አካባቢያቸው ሰላማዊ ኑሮ እንዲ ኖሩ የ ትራንስፖ... tr_2560_tr26061 \n", + "2613 የ ትምህርት ደረጃቸው ንና የ አገልግሎት ሁኔታ ቸውን ስን መረምር የሚ ደ... tr_2565_tr26066 \n", + "\n", + " channel sample_rate duration \n", + "4133 1 8000 2.048 \n", + "1476 1 8000 2.048 \n", + "408 1 8000 2.176 \n", + "73 1 8000 2.176 \n", + "3574 1 8000 2.176 \n", + "... ... ... ... \n", + "2614 1 8000 20.352 \n", + "1652 1 8000 20.736 \n", + "2222 1 8000 20.992 \n", + "2608 1 8000 21.120 \n", + "2613 1 8000 22.784 \n", + "\n", + "[5000 rows x 5 columns]" + ] + }, + "execution_count": 50, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "sorted_metadata = meta_data.sort_values(by=\"duration\")\n", + "labels = sorted_metadata['label'].to_list()\n", + "sorted_metadata" + ] + }, + { + "cell_type": "markdown", + "id": "2618565e", + "metadata": {}, + "source": [ + "#### extracting audios and translations in lists" + ] + }, + { + "cell_type": "code", + "execution_count": 51, + "id": "ef6a4e11", + "metadata": { + "executionInfo": { + "elapsed": 553, + "status": "ok", + "timestamp": 1628699415091, + "user": { + "displayName": "Daniel Zelalem", + "photoUrl": "", + "userId": "17933366000899068375" + }, + "user_tz": -180 + }, + "id": "ef6a4e11" + }, + "outputs": [], + "source": [ + "audios = []\n", + "for label in labels:\n", + " audios.append(audio_obj[label][0])\n", + " \n", + "translations = []\n", + "for label in labels:\n", + " translations.append(translation_obj[label])" + ] + }, + { + "cell_type": "markdown", + "id": "93e0c54a", + "metadata": {}, + "source": [ + "### Build function" + ] + }, + { + "cell_type": "markdown", + "id": "6dc44f6b", + "metadata": {}, + "source": [ + "- Build function takes a speech model and a preprocessing model (a model that gives melespectrogram features) and build them into a single speech model" + ] + }, + { + "cell_type": "code", + "execution_count": 52, + "id": "3675d659", + "metadata": { + "executionInfo": { + "elapsed": 4, + "status": "ok", + "timestamp": 1628699416838, + "user": { + "displayName": "Daniel Zelalem", + "photoUrl": "", + "userId": "17933366000899068375" + }, + "user_tz": -180 + }, + "id": "3675d659" + }, + "outputs": [], + "source": [ + "def build_model(output_dim, custom_model, preprocess_model, mfcc=False, calc=None):\n", + "\n", + " input_audios = Input(name='the_input', shape=(None,))\n", + " pre = preprocess_model(input_audios)\n", + " pre = tf.squeeze(pre, [3])\n", + "\n", + " y_pred = custom_model(pre)\n", + " model = Model(inputs=input_audios, outputs=y_pred, name=\"model_builder\")\n", + " model.output_length = calc\n", + "\n", + " return model" + ] + }, + { + "cell_type": "markdown", + "id": "701a3070", + "metadata": {}, + "source": [ + "### Predict function" + ] + }, + { + "cell_type": "code", + "execution_count": 53, + "id": "CKKxhFiFozcF", + "metadata": { + "executionInfo": { + "elapsed": 3, + "status": "ok", + "timestamp": 1628699418994, + "user": { + "displayName": "Daniel Zelalem", + "photoUrl": "", + "userId": "17933366000899068375" + }, + "user_tz": -180 + }, + "id": "CKKxhFiFozcF" + }, + "outputs": [], + "source": [ + "def predict(model, audio, tokenizer, int_to_char, actual=None):\n", + " \n", + " pred_audios = tf.convert_to_tensor([audio])\n", + " \n", + " y_pred = model.predict(pred_audios)\n", + "\n", + " input_shape = tf.keras.backend.shape(y_pred)\n", + " input_length = tf.ones(shape=input_shape[0]) * tf.keras.backend.cast(input_shape[1], 'float32')\n", + " prediction = tf.keras.backend.ctc_decode(y_pred, input_length, greedy=False)[0][0]\n", + " \n", + " pred = K.eval(prediction).flatten().tolist()\n", + " pred = [i for i in pred if i != -1]\n", + " \n", + " predicted_text = tokenizer.decode_text(pred, int_to_char)\n", + " \n", + " error = None\n", + " if actual != None:\n", + " error = wer(actual, predicted_text)\n", + " \n", + " return predicted_text, error" + ] + }, + { + "cell_type": "markdown", + "id": "e68b421f", + "metadata": {}, + "source": [ + "### Init our translation tokenizer and build a charchter mapping dict" + ] + }, + { + "cell_type": "code", + "execution_count": 54, + "id": "107cd033", + "metadata": { + "colab": { + "base_uri": "https://localhost:8080/" + }, + "executionInfo": { + "elapsed": 725, + "status": "ok", + "timestamp": 1628699421859, + "user": { + "displayName": "Daniel Zelalem", + "photoUrl": "", + "userId": "17933366000899068375" + }, + "user_tz": -180 + }, + "id": "107cd033", + "outputId": "2803c0e0-8fa0-4a94-948a-caa10db28729" + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "sample snt: እኛ ም እ ኮ ፉትቦል ን እንወዳ ለ ን\n", + "encoded snt: [13, 74, 1, 16, 1, 13, 1, 67, 1, 142, 3, 122, 12, 1, 2, 1, 13, 2, 37, 39, 1, 11, 1, 2]\n", + "decoed snt: እኛ ም እ ኮ ፉትቦል ን እንወዳ ለ ን\n" + ] + } + ], + "source": [ + "tokenizer = Tokenizer(translations)\n", + "int_to_char, char_to_int = tokenizer.build_dict()\n", + "sample = translations[0]\n", + "encoded = tokenizer.encode(sample, char_to_int)\n", + "decoded = tokenizer.decode_text(encoded, int_to_char)\n", + "\n", + "print(f\"sample snt: {sample}\")\n", + "print(f\"encoded snt: {encoded}\")\n", + "print(f\"decoed snt: {decoded}\")" + ] + }, + { + "cell_type": "code", + "execution_count": 102, + "id": "353195f4", + "metadata": {}, + "outputs": [], + "source": [ + "helper.write_obj(\"../int_to_char.pkl\", int_to_char)\n", + "helper.write_obj(\"../char_to_int.pkl\", char_to_int)" + ] + }, + { + "cell_type": "markdown", + "id": "92e07788", + "metadata": {}, + "source": [ + "### init our variables" + ] + }, + { + "cell_type": "code", + "execution_count": 55, + "id": "bdea9379", + "metadata": { + "executionInfo": { + "elapsed": 3, + "status": "ok", + "timestamp": 1628699424858, + "user": { + "displayName": "Daniel Zelalem", + "photoUrl": "", + "userId": "17933366000899068375" + }, + "user_tz": -180 + }, + "id": "bdea9379" + }, + "outputs": [], + "source": [ + "\n", + "sample_rate = 8000\n", + "fft_size = 512\n", + "frame_step = 256\n", + "n_mels = 128\n", + "\n", + "batch_size = 100\n", + "epochs = 20\n", + "data_len = len(translations)\n", + "output_dim = len(char_to_int) + 2\n" + ] + }, + { + "cell_type": "markdown", + "id": "3e534a2f", + "metadata": {}, + "source": [ + "### Init our DataGenerator and build our preprocessing model" + ] + }, + { + "cell_type": "code", + "execution_count": 57, + "id": "cb25dda1", + "metadata": { + "colab": { + "base_uri": "https://localhost:8080/" + }, + "executionInfo": { + "elapsed": 1693, + "status": "ok", + "timestamp": 1628699431823, + "user": { + "displayName": "Daniel Zelalem", + "photoUrl": "", + "userId": "17933366000899068375" + }, + "user_tz": -180 + }, + "id": "cb25dda1", + "outputId": "10156bd8-68dd-4ae4-fda4-c8ef21311ec1" + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Model: \"preprocessin_model\"\n", + "_________________________________________________________________\n", + "Layer (type) Output Shape Param # \n", + "=================================================================\n", + "input (InputLayer) [(None, None)] 0 \n", + "_________________________________________________________________\n", + "log_mel_spectrogram_1 (LogMe (None, None, 128, 1) 0 \n", + "_________________________________________________________________\n", + "batch_normalization_1 (Batch (None, None, 128, 1) 512 \n", + "=================================================================\n", + "Total params: 512\n", + "Trainable params: 256\n", + "Non-trainable params: 256\n", + "_________________________________________________________________\n" + ] + } + ], + "source": [ + "dg = DataGenerator(translations, audios, batch_size, shuffle=True)\n", + "preprocess_model = preprocessin_model(sample_rate, fft_size, frame_step, n_mels)\n", + "preprocess_model.summary()" + ] + }, + { + "cell_type": "markdown", + "id": "0eac923e", + "metadata": {}, + "source": [ + "### checking log melespectorgram of sample audio data using our preprocessing model" + ] + }, + { + "cell_type": "code", + "execution_count": 22, + "id": "ZdGw4xLn2L34", + "metadata": { + "colab": { + "base_uri": "https://localhost:8080/", + "height": 289 + }, + "executionInfo": { + "elapsed": 3181, + "status": "ok", + "timestamp": 1628699180083, + "user": { + "displayName": "Daniel Zelalem", + "photoUrl": "", + "userId": "17933366000899068375" + }, + "user_tz": -180 + }, + "id": "ZdGw4xLn2L34", + "outputId": "c52302db-2df7-4ed7-ba14-351efc8ae59f" + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "(1, 65536)\n" + ] + }, + { + "data": { + "text/plain": [ + "(1, 255, 128, 1)" + ] + }, + "metadata": { + "tags": [] + }, + "output_type": "display_data" + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "char_len 96\n" + ] + }, + { + "data": { + "image/png": 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\n", + "text/plain": [ + "
" + ] + }, + "metadata": { + "tags": [] + }, + "output_type": "display_data" + } + ], + "source": [ + "\n", + "\n", + "sample_audio = dg[0][0]['the_input'][0].numpy()\n", + "sample_lbl = dg[0][0]['the_labels'][0].numpy()\n", + "\n", + "a = np.zeros((1, len(sample_audio)))\n", + "a[0, ] = sample_audio\n", + "print(a.shape)\n", + "pred = preprocess_model.predict(a)\n", + "fig, ax = plt.subplots(figsize=(16, 4))\n", + "display(pred.shape)\n", + "pred = pred[0, :, :, 0]\n", + "librosa.display.specshow(pred.T, sr=8000, hop_length=128, cmap=\"jet\")\n", + "print(\"char_len\", len(sample_lbl))" + ] + }, + { + "cell_type": "code", + "execution_count": 27, + "id": "XeV4Uu6eCxRr", + "metadata": { + "colab": { + "base_uri": "https://localhost:8080/", + "height": 289 + }, + "executionInfo": { + "elapsed": 778, + "status": "ok", + "timestamp": 1628679511029, + "user": { + "displayName": "Daniel Zelalem", + "photoUrl": "", + "userId": "17933366000899068375" + }, + "user_tz": -180 + }, + "id": "XeV4Uu6eCxRr", + "outputId": "5f1be4d3-0be4-46fb-a9f5-7fde8586829a" + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "(1, 34816)\n" + ] + }, + { + "data": { + "text/plain": [ + "(1, 135, 128, 1)" + ] + }, + "metadata": { + "tags": [] + }, + "output_type": "display_data" + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "char_len 44\n" + ] + }, + { + "data": { + "image/png": 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\n", + "text/plain": [ + "
" + ] + }, + "metadata": { + "tags": [] + }, + "output_type": "display_data" + } + ], + "source": [ + "\n", + "sample_audio = dg[49][0]['the_input'][-1].numpy()\n", + "sample_lbl = dg[49][0]['the_labels'][-1].numpy()\n", + "\n", + "a = np.zeros((1, len(sample_audio)))\n", + "a[0, ] = sample_audio\n", + "print(a.shape)\n", + "pred = preprocess_model.predict(a)\n", + "fig, ax = plt.subplots(figsize=(16, 4))\n", + "display(pred.shape)\n", + "pred = pred[0, :, :, 0]\n", + "librosa.display.specshow(pred.T, sr=8000, hop_length=128, cmap=\"jet\")\n", + "print(\"char_len\", len(sample_lbl))" + ] + }, + { + "cell_type": "markdown", + "id": "0cd4bbf1", + "metadata": { + "id": "myDkV2oA2YY5" + }, + "source": [ + "### 1. Simple RNN model for speech to text" + ] + }, + { + "cell_type": "markdown", + "id": "661fb764", + "metadata": {}, + "source": [ + "#### creating a simple rnn model" + ] + }, + { + "cell_type": "code", + "execution_count": 62, + "id": "e43ae703", + "metadata": { + "colab": { + "base_uri": "https://localhost:8080/" + }, + "executionInfo": { + "elapsed": 610, + "status": "ok", + "timestamp": 1628679533946, + "user": { + "displayName": "Daniel Zelalem", + "photoUrl": "", + "userId": "17933366000899068375" + }, + "user_tz": -180 + }, + "id": "e43ae703", + "outputId": "7785164e-5e79-4509-f847-fa4735f8ad84" + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Model: \"simple_rnn_model\"\n", + "_________________________________________________________________\n", + "Layer (type) Output Shape Param # \n", + "=================================================================\n", + "the_input (InputLayer) [(None, None, 128)] 0 \n", + "_________________________________________________________________\n", + "rnn (GRU) (None, None, 223) 236157 \n", + "_________________________________________________________________\n", + "softmax (Activation) (None, None, 223) 0 \n", + "=================================================================\n", + "Total params: 236,157\n", + "Trainable params: 236,157\n", + "Non-trainable params: 0\n", + "_________________________________________________________________\n" + ] + } + ], + "source": [ + "speech_simple_rnn = simple_rnn_model(n_mels, output_dim)\n", + "speech_simple_rnn.summary()" + ] + }, + { + "cell_type": "markdown", + "id": "89cf48ad", + "metadata": {}, + "source": [ + "#### Building a simple rnn moel by stacking preprocessin_model and speech_simple_rnn" + ] + }, + { + "cell_type": "code", + "execution_count": 65, + "id": "b8e25a3f", + "metadata": { + "colab": { + "base_uri": "https://localhost:8080/" + }, + "executionInfo": { + "elapsed": 412, + "status": "ok", + "timestamp": 1628679536551, + "user": { + "displayName": "Daniel Zelalem", + "photoUrl": "", + "userId": "17933366000899068375" + }, + "user_tz": -180 + }, + "id": "b8e25a3f", + "outputId": "ef5342d7-b372-4a01-aa3b-b7125ba742e0" + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Model: \"model_builder\"\n", + "_________________________________________________________________\n", + "Layer (type) Output Shape Param # \n", + "=================================================================\n", + "the_input (InputLayer) [(None, None)] 0 \n", + "_________________________________________________________________\n", + "preprocessin_model (Function (None, None, 128, 1) 512 \n", + "_________________________________________________________________\n", + "tf.compat.v1.squeeze_3 (TFOp (None, None, 128) 0 \n", + "_________________________________________________________________\n", + "simple_rnn_model (Functional (None, None, 223) 236157 \n", + "=================================================================\n", + "Total params: 236,669\n", + "Trainable params: 236,413\n", + "Non-trainable params: 256\n", + "_________________________________________________________________\n" + ] + } + ], + "source": [ + "simple_rnn_speech_model = build_model(output_dim, speech_simple_rnn, preprocess_model)\n", + "simple_rnn_speech_model.summary()" + ] + }, + { + "cell_type": "markdown", + "id": "85c2c2cb", + "metadata": {}, + "source": [ + "#### Training" + ] + }, + { + "cell_type": "code", + "execution_count": 29, + "id": "01feee42", + "metadata": { + "colab": { + "base_uri": "https://localhost:8080/" + }, + "executionInfo": { + "elapsed": 246858, + "status": "ok", + "timestamp": 1628679787023, + "user": { + "displayName": "Daniel Zelalem", + "photoUrl": "", + "userId": "17933366000899068375" + }, + "user_tz": -180 + }, + "id": "01feee42", + "outputId": "41153299-6698-4e00-a9fe-218f47b93b90" + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Model: \"model\"\n", + "__________________________________________________________________________________________________\n", + "Layer (type) Output Shape Param # Connected to \n", + "==================================================================================================\n", + "the_input (InputLayer) [(None, None)] 0 \n", + "__________________________________________________________________________________________________\n", + "preprocessin_model (Functional) (None, None, 128, 1) 512 the_input[0][0] \n", + "__________________________________________________________________________________________________\n", + "tf.compat.v1.squeeze (TFOpLambd (None, None, 128) 0 preprocessin_model[0][0] \n", + "__________________________________________________________________________________________________\n", + "input_length (InputLayer) [(None, 1)] 0 \n", + "__________________________________________________________________________________________________\n", + "simple_rnn_model (Functional) (None, None, 223) 236157 tf.compat.v1.squeeze[0][0] \n", + "__________________________________________________________________________________________________\n", + "the_labels (InputLayer) [(None, None)] 0 \n", + "__________________________________________________________________________________________________\n", + "lambda (Lambda) (None, 1) 0 input_length[0][0] \n", + "__________________________________________________________________________________________________\n", + "label_length (InputLayer) [(None, 1)] 0 \n", + "__________________________________________________________________________________________________\n", + "ctc (Lambda) (None, 1) 0 simple_rnn_model[0][0] \n", + " the_labels[0][0] \n", + " lambda[0][0] \n", + " label_length[0][0] \n", + "==================================================================================================\n", + "Total params: 236,669\n", + "Trainable params: 236,413\n", + "Non-trainable params: 256\n", + "__________________________________________________________________________________________________\n", + "None\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "/Library/Frameworks/Python.framework/Versions/3.9/lib/python3.9/site-packages/tensorflow/python/keras/engine/training.py:1940: UserWarning: `Model.fit_generator` is deprecated and will be removed in a future version. Please use `Model.fit`, which supports generators.\n", + " warnings.warn('`Model.fit_generator` is deprecated and '\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Epoch 1/20\n", + "50/50 [==============================] - 74s 1s/step - loss: 741.7604\n", + "Epoch 2/20\n", + "50/50 [==============================] - 71s 1s/step - loss: 682.7922\n", + "Epoch 3/20\n", + "50/50 [==============================] - 78s 2s/step - loss: 682.0422\n", + "Epoch 4/20\n", + "50/50 [==============================] - 85s 2s/step - loss: 681.6732\n", + "Epoch 5/20\n", + "50/50 [==============================] - 85s 2s/step - loss: 681.3718\n", + "Epoch 6/20\n", + "50/50 [==============================] - 77s 2s/step - loss: 681.1526\n", + "Epoch 7/20\n", + "50/50 [==============================] - 73s 1s/step - loss: 680.9636\n", + "Epoch 8/20\n", + "50/50 [==============================] - 75s 2s/step - loss: 680.7802\n", + "Epoch 9/20\n", + "50/50 [==============================] - 68s 1s/step - loss: 680.6910\n", + "Epoch 10/20\n", + "50/50 [==============================] - 69s 1s/step - loss: 680.3199\n", + "Epoch 11/20\n", + "50/50 [==============================] - 87s 2s/step - loss: 680.0570\n", + "Epoch 12/20\n", + "50/50 [==============================] - 74s 1s/step - loss: 679.8464\n", + "Epoch 13/20\n", + "50/50 [==============================] - 92s 2s/step - loss: 679.8269\n", + "Epoch 14/20\n", + "50/50 [==============================] - 77s 2s/step - loss: 679.6784\n", + "Epoch 15/20\n", + "50/50 [==============================] - 71s 1s/step - loss: 679.6099\n", + "Epoch 16/20\n", + "50/50 [==============================] - 70s 1s/step - loss: 679.4676\n", + "Epoch 17/20\n", + "50/50 [==============================] - 69s 1s/step - loss: 679.3322\n", + "Epoch 18/20\n", + "50/50 [==============================] - 69s 1s/step - loss: 679.2448\n", + "Epoch 19/20\n", + "50/50 [==============================] - 76s 2s/step - loss: 679.2038\n", + "Epoch 20/20\n", + "50/50 [==============================] - 72s 1s/step - loss: 679.1887\n" + ] + }, + { + "data": { + "text/plain": [ + "" + ] + }, + "execution_count": 29, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "# mlflow.set_experiment('Speech Model-RNN-baseline')\n", + "# mlflow.tensorflow.autolog()\n", + "train(simple_rnn_speech_model, dg, epochs=20, save_path=\"../models/simple_rnn_model.h5\", batch_size=batch_size)" + ] + }, + { + "cell_type": "markdown", + "id": "55bc4ecd", + "metadata": {}, + "source": [ + "#### Predicting using simple rnn model" + ] + }, + { + "cell_type": "code", + "execution_count": 69, + "id": "5qmBzRhlmmgh", + "metadata": { + "colab": { + "base_uri": "https://localhost:8080/" + }, + "executionInfo": { + "elapsed": 1256, + "status": "ok", + "timestamp": 1628679833252, + "user": { + "displayName": "Daniel Zelalem", + "photoUrl": "", + "userId": "17933366000899068375" + }, + "user_tz": -180 + }, + "id": "5qmBzRhlmmgh", + "outputId": "9ae51d9d-88f5-41c3-c645-22e1abbccc0b" + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "actual በ ባህል በ ቋንቋ አንድ ናቸው\n", + "predicted ተ ተ ን ያ ያ አ አ አ ን ንር ን አ አ አ ን \n", + "WER: 2.5\n" + ] + } + ], + "source": [ + "\n", + "simple_rnn_speech_model.load_weights(\"../models/simple_rnn_model.h5\")\n", + "\n", + "\n", + "actual_translation = translations[10]\n", + "sample_test_audio = audios[0]\n", + "predicted, error = predict(simple_rnn_speech_model, sample_test_audio , tokenizer, int_to_char, actual=actual_translation)\n", + "\n", + "print(\"actual\", actual_translation)\n", + "print(\"predicted\", predicted)\n", + "print(\"WER: \", error)\n" + ] + }, + { + "cell_type": "code", + "execution_count": 19, + "id": "X1fMYpsW-3M6", + "metadata": { + "executionInfo": { + "elapsed": 779, + "status": "ok", + "timestamp": 1628699442061, + "user": { + "displayName": "Daniel Zelalem", + "photoUrl": "", + "userId": "17933366000899068375" + }, + "user_tz": -180 + }, + "id": "X1fMYpsW-3M6" + }, + "outputs": [], + "source": [ + "# def ctc_lambda_func(args):\n", + "# y_pred, labels, input_length, label_length = args\n", + "# return K.ctc_batch_cost(labels, y_pred, input_length, label_length)\n", + "\n", + "\n", + "# def input_lengths_lambda_func(args):\n", + "# hop_size = frame_step\n", + "# input_length = args\n", + "# return tf.cast(tf.math.ceil(input_length/hop_size)-1, dtype=\"float32\")\n", + "\n", + "\n", + "# def add_ctc_loss(model_builder):\n", + "# the_labels = Input(name='the_labels', shape=(None,), dtype='float32')\n", + "# input_lengths = Input(name='input_length', shape=(1,), dtype='float32')\n", + "# label_lengths = Input(name='label_length', shape=(1,), dtype='float32')\n", + "\n", + "# input_lengths2 = Lambda(input_lengths_lambda_func)(input_lengths)\n", + "# if model_builder.output_length:\n", + "# output_lengths = Lambda(\n", + "# model_builder.output_length)(input_lengths2)\n", + "# else:\n", + "# output_lengths = input_lengths2\n", + "\n", + "# loss_out = Lambda(ctc_lambda_func, output_shape=(1,), name='ctc')(\n", + "# [model_builder.output, the_labels, output_lengths, label_lengths])\n", + "# model = Model(inputs=[model_builder.input, the_labels,\n", + "# input_lengths, label_lengths], outputs=loss_out)\n", + "# return model" + ] + }, + { + "cell_type": "markdown", + "id": "e1621a85", + "metadata": {}, + "source": [ + "### 2. Using CNN + simple rnn" + ] + }, + { + "cell_type": "markdown", + "id": "7108a01e", + "metadata": {}, + "source": [ + "#### Creating cnn_rnn model" + ] + }, + { + "cell_type": "code", + "execution_count": 84, + "id": "w6LXjBNVyq_f", + "metadata": { + "colab": { + "base_uri": "https://localhost:8080/" + }, + "executionInfo": { + "elapsed": 387, + "status": "ok", + "timestamp": 1628682451974, + "user": { + "displayName": "Daniel Zelalem", + "photoUrl": "", + "userId": "17933366000899068375" + }, + "user_tz": -180 + }, + "id": "w6LXjBNVyq_f", + "outputId": "f3e38510-ea5e-4a5f-c69e-7b50a9cb8422" + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Model: \"model_2\"\n", + "_________________________________________________________________\n", + "Layer (type) Output Shape Param # \n", + "=================================================================\n", + "the_input (InputLayer) [(None, None, 128)] 0 \n", + "_________________________________________________________________\n", + "conv1d (Conv1D) (None, None, 250) 128250 \n", + "_________________________________________________________________\n", + "bn_conv_1d (BatchNormalizati (None, None, 250) 1000 \n", + "_________________________________________________________________\n", + "rnn (SimpleRNN) (None, None, 400) 260400 \n", + "_________________________________________________________________\n", + "batch_normalization_17 (Batc (None, None, 400) 1600 \n", + "_________________________________________________________________\n", + "time_distributed_3 (TimeDist (None, None, 223) 89423 \n", + "_________________________________________________________________\n", + "softmax (Activation) (None, None, 223) 0 \n", + "=================================================================\n", + "Total params: 480,673\n", + "Trainable params: 479,373\n", + "Non-trainable params: 1,300\n", + "_________________________________________________________________\n" + ] + } + ], + "source": [ + "speech_cnn_rnn = cnn_rnn_model(n_mels, 250, 4, 1, 'same', 400, output_dim)\n", + "speech_cnn_rnn.summary()" + ] + }, + { + "cell_type": "markdown", + "id": "be79576d", + "metadata": {}, + "source": [ + "#### Building a cnn_rnn speech model by stacking speech_cnn_rnn and preprocess_model" + ] + }, + { + "cell_type": "code", + "execution_count": 86, + "id": "s56xi_OY1JRz", + "metadata": { + "colab": { + "base_uri": "https://localhost:8080/" + }, + "executionInfo": { + "elapsed": 427, + "status": "ok", + "timestamp": 1628682459201, + "user": { + "displayName": "Daniel Zelalem", + "photoUrl": "", + "userId": "17933366000899068375" + }, + "user_tz": -180 + }, + "id": "s56xi_OY1JRz", + "outputId": "59e78795-252b-4c6e-d271-6a2cff16dd89" + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Model: \"model_builder\"\n", + "_________________________________________________________________\n", + "Layer (type) Output Shape Param # \n", + "=================================================================\n", + "the_input (InputLayer) [(None, None)] 0 \n", + "_________________________________________________________________\n", + "preprocessin_model (Function (None, None, 128, 1) 512 \n", + "_________________________________________________________________\n", + "tf.compat.v1.squeeze_6 (TFOp (None, None, 128) 0 \n", + "_________________________________________________________________\n", + "model_2 (Functional) (None, None, 223) 480673 \n", + "=================================================================\n", + "Total params: 481,185\n", + "Trainable params: 479,629\n", + "Non-trainable params: 1,556\n", + "_________________________________________________________________\n" + ] + } + ], + "source": [ + "speech_cnn_rnn_model = build_model(output_dim, speech_cnn_rnn, preprocess_model)\n", + "speech_cnn_rnn_model.summary()" + ] + }, + { + "cell_type": "markdown", + "id": "faacbd43", + "metadata": {}, + "source": [ + "#### Training" + ] + }, + { + "cell_type": "code", + "execution_count": 46, + "id": "M2bfG1CcFMYk", + "metadata": { + "colab": { + "base_uri": "https://localhost:8080/" + }, + "executionInfo": { + "elapsed": 554119, + "status": "ok", + "timestamp": 1628683716655, + "user": { + "displayName": "Daniel Zelalem", + "photoUrl": "", + "userId": "17933366000899068375" + }, + "user_tz": -180 + }, + "id": "M2bfG1CcFMYk", + "outputId": "52e665ac-db82-488d-f0d7-a3d66921d1f2" + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Model: \"model_6\"\n", + "__________________________________________________________________________________________________\n", + "Layer (type) Output Shape Param # Connected to \n", + "==================================================================================================\n", + "the_input (InputLayer) [(None, None)] 0 \n", + "__________________________________________________________________________________________________\n", + "preprocessin_model (Functional) (None, None, 128, 1) 512 the_input[0][0] \n", + "__________________________________________________________________________________________________\n", + "tf.compat.v1.squeeze_3 (TFOpLam (None, None, 128) 0 preprocessin_model[3][0] \n", + "__________________________________________________________________________________________________\n", + "input_length (InputLayer) [(None, 1)] 0 \n", + "__________________________________________________________________________________________________\n", + "model_4 (Functional) (None, None, 223) 480673 tf.compat.v1.squeeze_3[0][0] \n", + "__________________________________________________________________________________________________\n", + "the_labels (InputLayer) [(None, None)] 0 \n", + "__________________________________________________________________________________________________\n", + "lambda_4 (Lambda) (None, 1) 0 input_length[0][0] \n", + "__________________________________________________________________________________________________\n", + "label_length (InputLayer) [(None, 1)] 0 \n", + "__________________________________________________________________________________________________\n", + "ctc (Lambda) (None, 1) 0 model_4[0][0] \n", + " the_labels[0][0] \n", + " lambda_4[0][0] \n", + " label_length[0][0] \n", + "==================================================================================================\n", + "Total params: 481,185\n", + "Trainable params: 479,629\n", + "Non-trainable params: 1,556\n", + "__________________________________________________________________________________________________\n", + "None\n", + "Epoch 1/20\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "/usr/local/lib/python3.7/dist-packages/tensorflow/python/keras/engine/training.py:1940: UserWarning: `Model.fit_generator` is deprecated and will be removed in a future version. Please use `Model.fit`, which supports generators.\n", + " warnings.warn('`Model.fit_generator` is deprecated and '\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "50/50 [==============================] - 29s 549ms/step - loss: 63.8157\n", + "Epoch 2/20\n", + "50/50 [==============================] - 27s 539ms/step - loss: 62.2648\n", + "Epoch 3/20\n", + "50/50 [==============================] - 29s 582ms/step - loss: 60.5698\n", + "Epoch 4/20\n", + "50/50 [==============================] - 29s 564ms/step - loss: 59.1693\n", + "Epoch 5/20\n", + "50/50 [==============================] - 27s 538ms/step - loss: 57.8804\n", + "Epoch 6/20\n", + "50/50 [==============================] - 28s 562ms/step - loss: 56.3250\n", + "Epoch 7/20\n", + "50/50 [==============================] - 27s 551ms/step - loss: 55.1084\n", + "Epoch 8/20\n", + "50/50 [==============================] - 27s 533ms/step - loss: 53.8964\n", + "Epoch 9/20\n", + "50/50 [==============================] - 29s 579ms/step - loss: 52.6477\n", + "Epoch 10/20\n", + "50/50 [==============================] - 26s 530ms/step - loss: 51.7327\n", + "Epoch 11/20\n", + "50/50 [==============================] - 28s 568ms/step - loss: 50.4534\n", + "Epoch 12/20\n", + "50/50 [==============================] - 27s 531ms/step - loss: 48.9551\n", + "Epoch 13/20\n", + "50/50 [==============================] - 27s 534ms/step - loss: 48.2614\n", + "Epoch 14/20\n", + "50/50 [==============================] - 28s 564ms/step - loss: 47.1542\n", + "Epoch 15/20\n", + "50/50 [==============================] - 26s 532ms/step - loss: 46.4222\n", + "Epoch 16/20\n", + "50/50 [==============================] - 29s 578ms/step - loss: 45.2917\n", + "Epoch 17/20\n", + "50/50 [==============================] - 28s 566ms/step - loss: 44.5295\n", + "Epoch 18/20\n", + "50/50 [==============================] - 27s 522ms/step - loss: 43.6852\n", + "Epoch 19/20\n", + "50/50 [==============================] - 27s 540ms/step - loss: 43.0850\n", + "Epoch 20/20\n", + "50/50 [==============================] - 28s 561ms/step - loss: 41.7842\n" + ] + }, + { + "data": { + "text/plain": [ + "" + ] + }, + "execution_count": 46, + "metadata": { + "tags": [] + }, + "output_type": "execute_result" + } + ], + "source": [ + "\n", + "train(speech_cnn_rnn_model, dg, epochs=20, save_path=\"../models/cnn_rnn_model.h5\", batch_size=batch_size)\n" + ] + }, + { + "cell_type": "markdown", + "id": "e22464a4", + "metadata": {}, + "source": [ + "#### Infer cnn_rnn_model" + ] + }, + { + "cell_type": "code", + "execution_count": 88, + "id": "497eaeee", + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "actual የ ኖርዌይ የ ማእድን ካምፓኒ ኢትዮጵያ ውስጥ እንዲ ሰራ ፈቃድ ተሰጠው\n", + "predicted ስእሄ ን ሮ የ ማ እድደም ካን ፓ ንኔ ዲኢትዮጵያ ው ችጥ ክ ኒ ሳአራፈዋቀልሽሻት ታሁ\n", + "WER: 1.36\n", + "\n", + "actual አደጋ ጣ ዮቹ ኢትዮጵያዊ ውን ሾፌር ሆን ብለው ከ ሌሎ ለ ይተው እንደ ገደሉት ም ተመልክ ቷል\n", + "predicted ር ካዳጋያ ዳያበ ካከተር ጠ ያ ዊያን ሽው ሄያር ሀን ክላብ ንከ በር ሂ ር የ ከንደ ገደሩ ሳ ዳንነርክ ትለች\n", + "WER: 1.24\n", + "\n", + "actual ብቻ እንደ ው ለ ነገሩ እንጂ ያነሳ ሁት ሙትን ለ መውቀስ ፈልጌ አይደለም\n", + "predicted ብ ቻእንዳ ለ ላገበ እንጂ ያ ን ሰ ዎት ሙ ተች ለ መውቀሰ ፈልቄያይደድለ \n", + "WER: 1.00\n", + "\n", + "actual እዚህ አካባቢ ያለው ወገናችን ብዙ እውነት ይናገራል\n", + "predicted ጥጹት ስ ክት አንልላሩ ሀበራትጥምን በ ሶኦነክ እንና አልከራ \n", + "WER: 1.29\n", + "\n", + "actual ዘነበ ች ሰራተኛዋ ን አታ ን ጓጉ ብላ ተቆጣ ቻት\n", + "predicted ንነበ ች ራት ዋ ን አ ታ ን ባጉ በላ ተቆርጣ ቻት\n", + "WER: 0.80\n", + "\n", + "actual ሶስተኛው ሜይን ፍሬ ም ኮምፒውተር ይባላል\n", + "predicted እስት ተይ ኛ ው ሜይም ጥሬም ኰፒውሩታ ሪ ታና \n", + "WER: 1.50\n", + "\n", + "actual ተድላ በልጅነ ቱ ቆረ በ\n", + "predicted ተድ ላ በ ልዜን ቱ ቆእ ት አ\n", + "WER: 1.40\n", + "\n", + "actual በዚህ ኮሚቴ ስር የ ቴክኒክ ኮሚቴ ይኖራል\n", + "predicted በ ዚህ ኮሚቴ ሱር የ ቴክ ኒክ ኮሚቴ ይሞራት\n", + "WER: 0.86\n", + "\n", + "actual ብዙ ጨዋታዎች ን እንደ ተመለከቱ ገልጸው ልናል\n", + "predicted ብዙ ጨዋታዎች ን እንደ ተመለከቱ ገልጸው ልናል\n", + "WER: 0.00\n", + "\n", + "actual ችግሩ ንም እንዲ ፈታ ጥረት እያደረግን ነው\n", + "predicted ችግ ሩ ለም እንዲ ስፈት ተጥረት እያደረገን ናው\n", + "WER: 1.00\n", + "\n" + ] + } + ], + "source": [ + "speech_cnn_rnn_model.load_weights(\"../models/cnn_rnn_model.h5\")\n", + "\n", + "for k in range(10):\n", + " \n", + "\n", + " i = random.randint(0, 3000)\n", + " \n", + " actual_translation = translations[i]\n", + " sample_test_audio = audios[i]\n", + "\n", + " predicted, error = predict(speech_cnn_rnn_model, sample_test_audio,\n", + " tokenizer, int_to_char, actual=actual_translation)\n", + " \n", + " print(\"actual\", actual_translation)\n", + " print(\"predicted\", predicted)\n", + " print(f\"WER: {error:.2f}\")\n", + "\n", + " print()" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "jlPXyg-VsNv9", + "metadata": { + "id": "jlPXyg-VsNv9" + }, + "outputs": [], + "source": [] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "w3VPIL4TsUhA", + "metadata": { + "id": "w3VPIL4TsUhA" + }, + "outputs": [], + "source": [] + }, + { + "cell_type": "markdown", + "id": "3ccdcd98", + "metadata": { + "id": "cN2FhIzesUkJ" + }, + "source": [ + "## FINAL MODEL BETTER MODEL" + ] + }, + { + "cell_type": "markdown", + "id": "6a31b0eb", + "metadata": { + "id": "8I9rcUBqsUsE" + }, + "source": [ + "### 3. Using CNN and Bi directional rnn" + ] + }, + { + "cell_type": "code", + "execution_count": 72, + "id": "_Rz94NaiCLRk", + "metadata": { + "executionInfo": { + "elapsed": 540, + "status": "ok", + "timestamp": 1628699450931, + "user": { + "displayName": "Daniel Zelalem", + "photoUrl": "", + "userId": "17933366000899068375" + }, + "user_tz": -180 + }, + "id": "_Rz94NaiCLRk" + }, + "outputs": [], + "source": [ + "# since this model requires expenisive resource for training, we minimize the batch size to 32\n", + "\n", + "batch_size = 32\n", + "dg = DataGenerator(translations, audios, batch_size, shuffle=True)\n", + "\n" + ] + }, + { + "cell_type": "markdown", + "id": "a78c79f4", + "metadata": {}, + "source": [ + "#### First we create a cnn model that expects a logmelespectrogram prediction as input" + ] + }, + { + "cell_type": "code", + "execution_count": 73, + "id": "RJBipVrVyD18", + "metadata": { + "colab": { + "base_uri": "https://localhost:8080/" + }, + "executionInfo": { + "elapsed": 556, + "status": "ok", + "timestamp": 1628699455132, + "user": { + "displayName": "Daniel Zelalem", + "photoUrl": "", + "userId": "17933366000899068375" + }, + "user_tz": -180 + }, + "id": "RJBipVrVyD18", + "outputId": "567e673d-42bc-40ac-b82a-0e6966675169" + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Model: \"cnn\"\n", + "_________________________________________________________________\n", + "Layer (type) Output Shape Param # \n", + "=================================================================\n", + "the_input (InputLayer) [(None, None, 128, 1)] 0 \n", + "_________________________________________________________________\n", + "conv2d (Conv2D) (None, None, 128, 128) 6400 \n", + "_________________________________________________________________\n", + "activation (Activation) (None, None, 128, 128) 0 \n", + "_________________________________________________________________\n", + "batch_normalization_10 (Batc (None, None, 128, 128) 512 \n", + "_________________________________________________________________\n", + "max_pooling2d (MaxPooling2D) (None, None, 64, 128) 0 \n", + "_________________________________________________________________\n", + "conv2d_1 (Conv2D) (None, None, 64, 64) 204864 \n", + "_________________________________________________________________\n", + "activation_1 (Activation) (None, None, 64, 64) 0 \n", + "_________________________________________________________________\n", + "batch_normalization_11 (Batc (None, None, 64, 64) 256 \n", + "_________________________________________________________________\n", + "max_pooling2d_1 (MaxPooling2 (None, None, 32, 64) 0 \n", + "_________________________________________________________________\n", + "conv2d_2 (Conv2D) (None, None, 32, 64) 36928 \n", + "_________________________________________________________________\n", + "activation_2 (Activation) (None, None, 32, 64) 0 \n", + "_________________________________________________________________\n", + "batch_normalization_12 (Batc (None, None, 32, 64) 256 \n", + "_________________________________________________________________\n", + "max_pooling2d_2 (MaxPooling2 (None, None, 16, 64) 0 \n", + "_________________________________________________________________\n", + "reshape (Reshape) (None, None, 1024) 0 \n", + "=================================================================\n", + "Total params: 249,216\n", + "Trainable params: 248,704\n", + "Non-trainable params: 512\n", + "_________________________________________________________________\n" + ] + }, + { + "data": { + "text/plain": [ + "(None, TensorShape([None, None, 1024]))" + ] + }, + "execution_count": 73, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "cnn_model, cnn_shape = CNN_net(n_mels)\n", + "cnn_model.summary(), cnn_shape" + ] + }, + { + "cell_type": "markdown", + "id": "11e5a40c", + "metadata": {}, + "source": [ + "#### Create our Bi directional RNN" + ] + }, + { + "cell_type": "code", + "execution_count": 24, + "id": "6wTL17mK3hg4", + "metadata": { + "colab": { + "base_uri": "https://localhost:8080/" + }, + "executionInfo": { + "elapsed": 3640, + "status": "ok", + "timestamp": 1628699464815, + "user": { + "displayName": "Daniel Zelalem", + "photoUrl": "", + "userId": "17933366000899068375" + }, + "user_tz": -180 + }, + "id": "6wTL17mK3hg4", + "outputId": "02e6d5b8-3326-4f57-c101-3fcbb215e2c2" + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Model: \"BidirectionalRNN\"\n", + "_________________________________________________________________\n", + "Layer (type) Output Shape Param # \n", + "=================================================================\n", + "the_input (InputLayer) [(None, None, 1024)] 0 \n", + "_________________________________________________________________\n", + "bidirectional (Bidirectional (None, None, 800) 4560000 \n", + "_________________________________________________________________\n", + "batch_normalization_4 (Batch (None, None, 800) 3200 \n", + "_________________________________________________________________\n", + "dropout (Dropout) (None, None, 800) 0 \n", + "_________________________________________________________________\n", + "bidirectional_1 (Bidirection (None, None, 800) 3843200 \n", + "_________________________________________________________________\n", + "batch_normalization_5 (Batch (None, None, 800) 3200 \n", + "_________________________________________________________________\n", + "dropout_1 (Dropout) (None, None, 800) 0 \n", + "_________________________________________________________________\n", + "bidirectional_2 (Bidirection (None, None, 800) 3843200 \n", + "_________________________________________________________________\n", + "batch_normalization_6 (Batch (None, None, 800) 3200 \n", + "_________________________________________________________________\n", + "dropout_2 (Dropout) (None, None, 800) 0 \n", + "_________________________________________________________________\n", + "bidirectional_3 (Bidirection (None, None, 800) 3843200 \n", + "_________________________________________________________________\n", + "batch_normalization_7 (Batch (None, None, 800) 3200 \n", + "_________________________________________________________________\n", + "dropout_3 (Dropout) (None, None, 800) 0 \n", + "_________________________________________________________________\n", + "time_distributed (TimeDistri (None, None, 223) 178623 \n", + "_________________________________________________________________\n", + "softmax (Activation) (None, None, 223) 0 \n", + "=================================================================\n", + "Total params: 16,281,023\n", + "Trainable params: 16,274,623\n", + "Non-trainable params: 6,400\n", + "_________________________________________________________________\n" + ] + } + ], + "source": [ + "BI_RNN_2 = BidirectionalRNN2(1024, batch_size=batch_size, output_dim=output_dim)\n", + "BI_RNN_2.summary()" + ] + }, + { + "cell_type": "markdown", + "id": "84188544", + "metadata": {}, + "source": [ + "#### Define a builder that stacks preprocess_model, cnn_model and the custom model(BI-RNN) into a single model" + ] + }, + { + "cell_type": "code", + "execution_count": 75, + "id": "fA-kpf8c5a0W", + "metadata": { + "executionInfo": { + "elapsed": 5, + "status": "ok", + "timestamp": 1628699465570, + "user": { + "displayName": "Daniel Zelalem", + "photoUrl": "", + "userId": "17933366000899068375" + }, + "user_tz": -180 + }, + "id": "fA-kpf8c5a0W" + }, + "outputs": [], + "source": [ + "def build_model2(output_dim, cnn_model, custom_model, preprocess_model, mfcc=False, calc=None):\n", + "\n", + " input_audios = Input(name='the_input', shape=(None,))\n", + " pre = preprocess_model(input_audios)\n", + " pre = tf.squeeze(pre, [3])\n", + "\n", + " cnn_output = cnn_model(pre)\n", + "\n", + " y_pred = custom_model(cnn_output)\n", + " model = Model(inputs=input_audios, outputs=y_pred, name=\"model_builder\")\n", + " model.output_length = calc\n", + "\n", + " return model" + ] + }, + { + "cell_type": "markdown", + "id": "53718565", + "metadata": {}, + "source": [ + "#### Building our cnn-bi-rnn model using build2 function" + ] + }, + { + "cell_type": "code", + "execution_count": 26, + "id": "jmo82oGp5xa8", + "metadata": { + "colab": { + "base_uri": "https://localhost:8080/" + }, + "executionInfo": { + "elapsed": 3570, + "status": "ok", + "timestamp": 1628699471716, + "user": { + "displayName": "Daniel Zelalem", + "photoUrl": "", + "userId": "17933366000899068375" + }, + "user_tz": -180 + }, + "id": "jmo82oGp5xa8", + "outputId": "53400ce2-cee7-4401-bf0b-6030a37ac4d0" + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Model: \"model_builder\"\n", + "_________________________________________________________________\n", + "Layer (type) Output Shape Param # \n", + "=================================================================\n", + "the_input (InputLayer) [(None, None)] 0 \n", + "_________________________________________________________________\n", + "preprocessin_model (Function (None, None, 128, 1) 512 \n", + "_________________________________________________________________\n", + "tf.compat.v1.squeeze (TFOpLa (None, None, 128) 0 \n", + "_________________________________________________________________\n", + "cnn (Functional) (None, None, 1024) 249216 \n", + "_________________________________________________________________\n", + "BidirectionalRNN (Functional (None, None, 223) 16281023 \n", + "=================================================================\n", + "Total params: 16,530,751\n", + "Trainable params: 16,523,583\n", + "Non-trainable params: 7,168\n", + "_________________________________________________________________\n" + ] + } + ], + "source": [ + "cnn_bi_rnn_model = build_model2(output_dim, cnn_model, BI_RNN_2, preprocess_model)\n", + "cnn_bi_rnn_model.summary()" + ] + }, + { + "cell_type": "code", + "execution_count": 94, + "id": "X38CX655C2hb", + "metadata": { + "executionInfo": { + "elapsed": 4, + "status": "ok", + "timestamp": 1628699512025, + "user": { + "displayName": "Daniel Zelalem", + "photoUrl": "", + "userId": "17933366000899068375" + }, + "user_tz": -180 + }, + "id": "X38CX655C2hb" + }, + "outputs": [], + "source": [ + "# if a pretrained model exists load pretrained model\n", + "try:\n", + " cnn_bi_rnn_model.load_weights(\"../models/cnn-bi-rnn.h5\")\n", + "except:\n", + " pass" + ] + }, + { + "cell_type": "markdown", + "id": "ec35fcce", + "metadata": {}, + "source": [ + "#### Training" + ] + }, + { + "cell_type": "code", + "execution_count": 83, + "id": "VpezKF8CAReX", + "metadata": { + "colab": { + "base_uri": "https://localhost:8080/", + "height": 956 + }, + "executionInfo": { + "elapsed": 39382, + "status": "error", + "timestamp": 1628699374537, + "user": { + "displayName": "Daniel Zelalem", + "photoUrl": "", + "userId": "17933366000899068375" + }, + "user_tz": -180 + }, + "id": "VpezKF8CAReX", + "outputId": "53e03b76-3415-490a-ad59-872f9dfdfaf9" + }, + "outputs": [], + "source": [ + "\n", + "train(cnn_bi_rnn_model, dg, epochs=20, save_path=\"../models/cnn_bi_rnn_model.h5\", batch_size=batch_size)\n" + ] + }, + { + "cell_type": "markdown", + "id": "bdb75f4f", + "metadata": {}, + "source": [ + "#### Inference" + ] + }, + { + "cell_type": "code", + "execution_count": 82, + "id": "SYqCyyi0SIYG", + "metadata": { + "colab": { + "base_uri": "https://localhost:8080/" + }, + "executionInfo": { + "elapsed": 26235, + "status": "ok", + "timestamp": 1628699510451, + "user": { + "displayName": "Daniel Zelalem", + "photoUrl": "", + "userId": "17933366000899068375" + }, + "user_tz": -180 + }, + "id": "SYqCyyi0SIYG", + "outputId": "0941430e-f042-4fa9-c40f-c0041a153884" + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "actual ሀያት ተባባሪ ዎቹ ና ተሳታፊ ዎቹን አወያየ\n", + "predicted ሀያት ተባረ ዎች ና ተሻታሺ ዎች ን አጐራ የጀ\n", + "WER: 1.00\n", + "\n", + "actual እንዲያ መሬት አይ ን ካ ኝ ይል የነበረ ሰው በ ድንገት ቆረቆዘ አይደል\n", + "predicted እንዲያ መሬት አይ ን ካ ኝ ይል የነበረ ሰው በ ድንገት ቆረቆዘ አይደል\n", + "WER: 0.00\n", + "\n", + "actual ቡድናችን የ ተሸነፈ ው እ ኮ ከ ቅዱስ ጊዮርጊስ ጋር ስን ጫወት ብቻ ነው\n", + "predicted ቡድናችን የ ተሸነ ፈ ውእ ኮ ከህረ ቅዱስ ጊዮርጊስ ጋር ስን ጫ ወጥ ብቻ ሉ\n", + "WER: 0.50\n", + "\n", + "actual ፈ ቲያ ሰኢድ ወይዘሪት አዲስ አበባ ተባለች\n", + "predicted ከ ቲያ ፈቂድ ወዘሪት አዲስ አበባ ተታለች\n", + "WER: 0.57\n", + "\n", + "actual እጀ ጐልዳ ፋው ሰው ዬ መጻፍ አይችልም\n", + "predicted እጀ ጐልዳ ፋው ሰው ዬ መጻፍ አይችልም\n", + "WER: 0.00\n", + "\n", + "actual የ ኢትዮጵያ ነጻ ፕሬስ ጋዜጠኞች ማህበር ጽፈት ቤት ና የ ኢትዮ ታይም ቢሮ ተዘረፈ\n", + "predicted የ ኢትዮጵያ ነጻ ፐሬስ ካዜጠኞሽ ማህባል ጽፈት ቤት ና የ ኢትዮ ታይል ዜሮ ተዘረራ ት\n", + "WER: 0.50\n", + "\n", + "actual በ አውሮፓ ውስጥ አንድ መቶ ሀምሳ ቢሊዮን ቴሌቪዥን አለ\n", + "predicted በ አውርታው ውስጥ አንድ መት ሀብሳብ ቢሊዮየን ን ቴክኬክሽን አለ\n", + "WER: 0.67\n", + "\n", + "actual በ ኦልድ ትራ ፎርድ ማንቸስተር ዩናትድ ብላክበርን ን አስተናግ ዷል\n", + "predicted ተቆል ድ ትራ ፎርድ ማንቸስተር ዩናትድ ትላክበርለን አስተናግ ዷል\n", + "WER: 0.40\n", + "\n", + "actual ኢትዮጵያ ለ ደረሰባት ለሚደርስ ባት የእኔ ም የ እሳቸው ም የ ሁላችን ም እጅ አለ በት\n", + "predicted ኢትዮጵያ ለ ደረሰባት ለሚደርስ ዛት የ እኔ ም የ እሳቸው ም የ ሁላችን ም ጥይጅ አለ በት\n", + "WER: 0.25\n", + "\n", + "actual በሮማ በ ተደረገው ጨዋታ ሮማ ፍሮዬንቲ ና አስተናግ ዶ በድል ተ ወጥቶ አል\n", + "predicted በሮማ በ ተደረገው ጨዋታ አሮማ ፍሮ ዬንቺ ና አስተናግ ዶ በድል ተ ወጥጧ አል\n", + "WER: 0.31\n", + "\n" + ] + } + ], + "source": [ + "\n", + "cnn_bi_rnn_model.load_weights(\"../models/cnn-bi-rnn.h5\")\n", + "for k in range(10):\n", + " \n", + "\n", + " i = random.randint(0, 3000)\n", + " \n", + " actual_translation = translations[i]\n", + " sample_test_audio = audios[i]\n", + "\n", + " predicted, error = predict(cnn_bi_rnn_model, sample_test_audio,\n", + " tokenizer, int_to_char, actual=actual_translation)\n", + " \n", + " print(\"actual\", actual_translation)\n", + " print(\"predicted\", predicted)\n", + " print(f\"WER: {error:.2f}\")\n", + "\n", + " print()\n", + " \n" + ] + }, + { + "cell_type": "code", + "execution_count": 100, + "id": "0a9f1553", + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + } + ], + "source": [ + "cnn_bi_rnn_model.save('../models/final_speech_model.h5')\n" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "4686b15a", + "metadata": {}, + "outputs": [], + "source": [] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "da039d06", + "metadata": {}, + "outputs": [], + "source": [] + } + ], + "metadata": { + "accelerator": "GPU", + "colab": { + "collapsed_sections": [], + "name": "ModelTrain.ipynb", + "provenance": [] + }, + "kernelspec": { + "display_name": "Python 3", + "language": "python", + "name": "python3" + }, + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 3 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython3", + "version": "3.9.4" + } + }, + "nbformat": 4, + "nbformat_minor": 5 +} diff --git a/notebooks/data_preprocessing.ipynb b/notebooks/data_preprocessing.ipynb index 23cae7c..222f5fa 100644 --- a/notebooks/data_preprocessing.ipynb +++ b/notebooks/data_preprocessing.ipynb @@ -2,7 +2,8 @@ "cells": [ { "cell_type": "code", - "execution_count": 1, + "execution_count": 4, + "id": "f7d9521a", "metadata": { "id": "c0c8988a" }, @@ -19,25 +20,38 @@ "import os\n", "import pickle\n", "import pandas as pd\n", + "from collections import Counter\n", + "\n", "import librosa #for audio processing\n", "import librosa.display\n", - "\n" + "# import tensorflow as tf\n" ] }, { "cell_type": "code", - "execution_count": 2, + "execution_count": 5, + "id": "0f3e2190", + "metadata": {}, + "outputs": [], + "source": [ + "import helper\n" + ] + }, + { + "cell_type": "code", + "execution_count": 6, + "id": "8f21a9e9", "metadata": {}, "outputs": [], "source": [ "from data_augmentation import Data_Augmentation\n", - "from data_loader import DataLoader\n", - "import helper" + "from data_loader import DataLoader\n" ] }, { "cell_type": "code", - "execution_count": 3, + "execution_count": 14, + "id": "1a71decd", "metadata": { "id": "HOaIKtShaPnS" }, @@ -49,7 +63,8 @@ }, { "cell_type": "code", - "execution_count": 7, + "execution_count": 15, + "id": "4a6e0ca8", "metadata": { "id": "7PV5In98aX4m" }, @@ -57,12 +72,52 @@ "source": [ "train_audio_folder = train_path + \"/wav/\"\n", "train_script_file = train_path + \"trsTrain.txt\"\n", - "sample_rate = 22000" + "sample_rate = 8000" ] }, { "cell_type": "code", - "execution_count": 8, + "execution_count": 19, + "id": "f99f7115", + "metadata": {}, + "outputs": [], + "source": [ + "test_audio_folder = test_path + \"/wav/\"\n", + "test_script_file = test_path + \"trsTest.txt\"" + ] + }, + { + "cell_type": "code", + "execution_count": 7, + "id": "a28a20ce", + "metadata": {}, + "outputs": [], + "source": [ + "def clean_signal(signal, normalize = False ,trim_db = None, clean_db = None):\n", + "\n", + " if normalize:\n", + " feats_mean = np.mean(signal, axis=0)\n", + " feats_std = np.std(signal, axis=0)\n", + " signal = (signal - feats_mean) / (feats_std + 1e-14)\n", + "\n", + " if trim_db:\n", + " signal, index = librosa.effects.trim(signal, top_db=trim_db)\n", + "\n", + " if clean_db:\n", + " yt = librosa.effects.split(signal, top_db=clean_db)\n", + " clean_signal = []\n", + " for start_i, end_i in yt:\n", + " clean_signal.append( signal[start_i: end_i])\n", + "\n", + " signal = np.concatenate(np.array(clean_signal),axis=0)\n", + "\n", + " return signal" + ] + }, + { + "cell_type": "code", + "execution_count": 10, + "id": "3a1da3e9", "metadata": {}, "outputs": [], "source": [ @@ -71,19 +126,21 @@ }, { "cell_type": "code", - "execution_count": 9, + "execution_count": 11, + "id": "c114f207", "metadata": { "id": "jFTW5hIX6ids" }, "outputs": [], "source": [ "translation_obj = data_loader.extract_transcription_and_labels()\n", - "audio_dict = data_loader.extract_audio(100)" + "audio_dict = data_loader.extract_audio(5000)" ] }, { "cell_type": "code", - "execution_count": 10, + "execution_count": 12, + "id": "74f9e143", "metadata": { "id": "6CTYhPjR5frn" }, @@ -96,7 +153,8 @@ }, { "cell_type": "code", - "execution_count": 11, + "execution_count": 14, + "id": "73945c97", "metadata": { "id": "XwsX1sBJngY6" }, @@ -109,1013 +167,29 @@ }, { "cell_type": "code", - "execution_count": 12, + "execution_count": 20, + "id": "a215741b", + "metadata": {}, + "outputs": [], + "source": [ + "test_data_loader = DataLoader(test_audio_folder, test_script_file, sr=sample_rate)\n", + "test_translation_obj = test_data_loader.extract_transcription_and_labels()\n", + "test_audio_dict = test_data_loader.extract_audio(20)\n", + "\n", + "helper.write_obj(\"../data/test_audio_dict.pkl\", test_audio_dict)\n", + "helper.write_obj(\"../data/test_translation_dict.pkl\", test_translation_obj)" + ] + }, + { + "cell_type": "code", + "execution_count": 15, + "id": "8dc1a7d1", "metadata": {}, "outputs": [ { "data": { "text/plain": [ - "{'tr_1_tr01001': 'ያንደኛ ደረጃ ትምህርታቸው ን ጐንደር ተ ም ረዋል',\n", - " 'tr_2_tr01002': 'የተ ለቀቁት ምርኮኞች በ አካባቢያቸው ሰላማዊ ኑሮ እንዲ ኖሩ የ ትራንስፖርት ና መጓጓዣ ገንዘብ ተሰጥቷ ቸው መሸኘታቸው ን አመልክቶ በ የ ዞ ናቸው እንደ ደረሱ መቃቋሚያ እንደሚ ሰጣቸው ም አስ ታውቋል',\n", - " 'tr_3_tr01003': 'በ አዲስ አበባው ስታዲየም በ ተካሄዱ ት ሁለት ግጥሚያ ዎች በ መጀመሪያ የ ተገናኙ ት መድን ና ሙገር ሲሚንቶ ሲ ሆኑ በ ውጤቱ ም ሶስት ለ ሶስት ተለያይ ተዋል',\n", - " 'tr_4_tr01004': 'ወሬው ን ወሬ ያደረጉ ምስጢረ ኞች ናቸው',\n", - " 'tr_5_tr01005': 'ኢትዮጵያዊ ቷ በ ብሄራዊ ባህላዊ አለባበስ ከ አለም አንደኝነት ን ተቀዳጀ ች',\n", - " 'tr_6_tr01006': 'ከ ትምክህት እንዳይ ቆጠር ብን እንጂ በ አለም ታሪክ ውስጥ በ ነጮች ያል ተረገጠ ች አገር ኢትዮጵያ ና ት',\n", - " 'tr_7_tr01007': 'እህቶቹ የኤርትራ ዜጐች ና የ ሻእቢያ ደጋፊዎች ናቸው',\n", - " 'tr_8_tr01008': 'እናንተ ም መቀበሪያ እንዳ ታጡ ተጠንቀቁ',\n", - " 'tr_9_tr01009': 'አንቶኔሊ በ አጼ ምንሊክ ፊት የ ፈጸመው ድፍረት በ ኢጣሊያ ን ምክር ቤት አስተ ቸው',\n", - " 'tr_10_tr01010': 'ግን ወደ ኋላው ላይ ኢሳያስ እንደ ልማ ዳቸው ሁሉን ም የ መልከ ፍ ዲፕሎማሲ ያቸው እስራኤል ንም ያስ ወር ፋቸው ጀመር',\n", - " 'tr_11_tr01011': 'ከ የ አቅጣጫ ው እየ ደረሷቸው ያሉ መረጃዎች አሳሳቢ ችግሮች እየ ደረሱ መሆናቸው ን የሚ ጠቁሙ መሆናቸው ን ፕሬዝዳንቱ ተናግረ ዋል',\n", - " 'tr_12_tr01012': 'ከ ማወቁ በፊት እንደ ተበጠበጠ ገበያ እንዳይ በታተን ይህ ነው አጀንዳ ችን ሌላ አጀንዳ የ ለ ንም',\n", - " 'tr_13_tr01013': 'ኢትዮጵያ ም ሰራዊቷ በ ኤርትራ እንደሚ ገኝ አል ካደ ችም',\n", - " 'tr_14_tr01014': 'ላቁኦተ ትምህርት ቤት መንገድ ና ሆስፒታል ተ ገንብቷል',\n", - " 'tr_15_tr01015': 'ኦስሪያን በ ሀገሩ አንድ ለ ዜሮ አሸንፎ ሶስት ነጥብ ይ ዟል',\n", - " 'tr_16_tr01016': 'ሁሴን አይዲድ እንደ ገለጹት ኢትዮጵያ ሁኔታዎች ከ ተመቻቹ ላት ሶማሊያ ን ከ መውረር ስለማ ት መለስ ከ እርቁ ይልቅ ሶማሊያ ን ከ ኢትዩጵያ ና ኢትዮጵያ ካ ደራጀ ቻቸው ሀይሎች ለ መጠበቅ መዘጋጀት ያስፈልጋ ል',\n", - " 'tr_17_tr01017': 'በ ሙስና ክስ የ ተመሰረተባቸው ነጋዴዎች መገናኛ ብዙሀን ን ከሰሱ',\n", - " 'tr_18_tr01018': 'ኢትዮጵያ የመን ና ሱዳን ኢሳያስ ን ለ ማውረድ ተስማም ተዋል ተ ባለ',\n", - " 'tr_19_tr01019': 'ለማ ን አቤት ማለት እንደሚ ቻል ም ግራ ገብቶ ናል በ ማለት ነጋዴ ዎቹ ብሶ ታቸውን ገልጸዋል',\n", - " 'tr_20_tr01020': 'በ ኢትዮጵያውያ ን ብቻ ሳን ወሰን የ ኢትዮጵያ ወዳጆች የሆኑ የ ኢትዮጵያ ታሪክ አዋቂዎች ም በ ውጪ የሚገኙ በዚህ ስራ ላይ ተሳታፊ እንዲሆኑ ጥረት አድርገ ናል',\n", - " 'tr_21_tr01021': 'ኢትዮጵያ ውስጥ የ ነበሩት ኤርትራውያን ም ተመሳሳይ እድል ነበራቸው',\n", - " 'tr_22_tr01022': 'የ ደህንነት ኢሚግሬሽን ና ስደተኞች ባለስልጣን ሰራተኞች በ በኩላቸው ተጓዦቹ ሰነዱ ን እንዲ ያሟሉ ለ ቀይ መስቀል ኮሚቴው ማስታወ ቃቸው ን ተናግረ ዋል',\n", - " 'tr_23_tr01023': 'ሁለት መቶ ሺ ያህሉ ደግሞ አብዛኛዎቹ ሲ ሰደዱ ቀሪዎቹ ሞ ተዋል ወይን ም ተ ሸሽገ ዋል',\n", - " 'tr_24_tr01024': 'ዛሬ ም ደግ መ ን ይህንኑ እን ላለን',\n", - " 'tr_25_tr01025': 'በ ቦሌ አለም አቀፍ አውሮፕላን ማረፊያ ጸረ ናርኮቲክ የ ቁጥጥር ክፍል አደገኛ እጾች አዘዋዋሪ ዎች ኢትዮጵያ ን መሸጋገሪያ እንዳያ ደርጓት ማሳሰቡ ን በ ዘገባው አ ስፍሯል',\n", - " 'tr_26_tr01026': 'ዘጠና ሁለት ኢትዮጵያውያ ን የ ደረሱበት ጠፉ',\n", - " 'tr_27_tr01027': 'መረጃ ያልተገኘ ባቸው ቤታቸው ናቸው በ ማለት ምላሽ ሰጥተዋል',\n", - " 'tr_28_tr01028': 'ኮንፍረንሱ ን የ መሩት ስር ዊሊያም ራሪ አዲስ ፎረ ም ለአፍሪካ ኢንቬስተመንት አዲስ ራእይ እንደሆነ ገልጸዋል',\n", - " 'tr_29_tr01029': 'መላእክት ያጀቡ ት ህጻን ቦረና ህጻናት ን የሚጠብቁ ና የሚንከባከ ቧቸው መላእክት አሉ ይባላል',\n", - " 'tr_30_tr01030': 'እውቅና ን መ ጐናጸፍ መጥፎ ጐን እንዳለው በሚገባ ተረድ ቻለሁ',\n", - " 'tr_31_tr01031': 'እውቅና ን ማግኘቴ ለ እኔ ትልቅ ክብር ነው',\n", - " 'tr_32_tr01032': 'ም ን ለማ ለት ነው ግልጽ አድርገው',\n", - " 'tr_33_tr01033': 'ከዚያ በ ተጨማሪ የ ስልጠና ውን ሂደት የሚ ያሻሽል ላቸው ይ ሻሉ',\n", - " 'tr_34_tr01034': 'ጨዋታው ቀጥሎ ፔናልቲ ውስጥ ቺላቬርት ኳስ ያገኝ ና ሳ ያውቅ ለ ፓሌርሞ ያቀ ብለዋል',\n", - " 'tr_35_tr01035': 'አንዋር ጊዮርጊስ ሊገባ ነው',\n", - " 'tr_36_tr01036': 'ሆን ተብሎ ም እየተደረገ ብኝ ነው',\n", - " 'tr_37_tr01037': 'ጨዋታው የሚ ከናወነው ሚያዝያ አስራ ስምንት ቀን ነው',\n", - " 'tr_38_tr01038': 'ኢንጂነር ግዛው ተክለ ማሪያም ግልጽ ባልሆነ ምክንያት ከ ተጫዋቾቹ ጋር ሳይ ተዋወቁ ቀር ተዋል',\n", - " 'tr_39_tr01039': 'ደንቡ ን ያጸደቀ ው የ ፌዴራል እ ስፖርት ምክር ቤት ነው',\n", - " 'tr_40_tr01040': 'ያን ን ማ ፕሮግራም ያወጡ ት እ ኮ እነ ክቡር አቶ ይድነቃቸው ተሰማ ናቸው',\n", - " 'tr_41_tr01041': 'እንዲያ ውም እንደሚ ወራው ሊፒ ጁቬንትስ ዘንድሮ ለ ቻምፒየንስ ሊግ ድል ማብቃት ና ስማቸው ን መጠበቅ ነው አላማቸው',\n", - " 'tr_42_tr01042': 'ሞዛምቢክ ን ያሸነፈ ው ታዳጊ ቡድናችን ትላንት ጠዋት አዲስ አባ ገባ',\n", - " 'tr_43_tr01043': 'በ አቶ ወንድሙ እምነት ኢትዮጵያውያኑ በ አገራቸው የተደላደለ ኑሮ ሊኖሩ በ ቻሉ',\n", - " 'tr_44_tr01044': 'ስንት ና ስንት ጀግኖች እንደ ወጡ ቀር ተዋል',\n", - " 'tr_45_tr01045': 'በ ኢትዮጵያ በ ድርቅ ለ ተጐዱ እስካሁን የተገኘው አርባ ሺ ዶላር ብቻ ነው',\n", - " 'tr_46_tr01046': 'ተጨማሪ የ ኢትዮጵያ ወታደሮች ሰሞኑ ን ሱማሊያ ገቡ',\n", - " 'tr_47_tr01047': 'ጠቅላይ ሚኒስትሩ አዲስ አበባ ውስጥ ለሚገኙ ዲፕሎማቶች ማብራሪያ በ ሰጡበት ወቅት ወረራው በ ሰላማዊ መንገድ ሊ ወገድ ስለ መቻሉ እስካሁን ፍንጭ አለማ የ ታቸውን ገልጠዋል',\n", - " 'tr_48_tr01048': 'የ ኢትዮጵያ ና የኤርትራ ባለስልጣናት ነገ ይገናኛ ሉ',\n", - " 'tr_49_tr01049': 'በ ስምንት ነጥብ ሰባት ሚሊዮን ብር እዳ ክስ ሊ መሰረት ነው',\n", - " 'tr_50_tr01050': 'የ ኢትዮጵያ ሚሊሺያ ዎች የ ኬንያ ን ድንበር ጥሰው ጉዳት ማድረሳቸው ን እናውቃለን ብለዋል',\n", - " 'tr_51_tr01051': 'ሚኒስትሩ አቶ ስዩም መስፍን ን ለ ማሳመን እየ ጣሩ መሆኑን ለ ጉዳዩ ቅርበት ያ ላቸው ምንጮች ተናግረ ዋል',\n", - " 'tr_52_tr01052': 'ይህም በ ኢትዮጵያ የ ዋጋ መውደቅ ን ያስከትላል',\n", - " 'tr_53_tr01053': 'ምርጫ ችን ደግሞ የማ ያቋርጥ ስደት ሆነ',\n", - " 'tr_54_tr01054': 'ወደ ትንተና ውስጥ ነበር የ ገባው',\n", - " 'tr_55_tr01055': 'እንዲ ህ እንደ ሱ የማከብራቸው ሰዎች ብዙ አይደሉም',\n", - " 'tr_56_tr01056': 'ማን ሞቶ ማን ነጻ እንዲ ወጣ ነው የሚ ፈለገው እዚህ አገር ውስጥ እ ያንዳንዳችን ለ ራሳችን መቆም አለ ብን የሚሉ ነበሩ',\n", - " 'tr_57_tr01057': 'በ ዋሽንግተን ዲሲ ና በ አካባቢ ዋ ማለት ም በ ሜሪላንድ ና በ ቨርጂኒያ ስቴ ቶች ላሉ ኤርትራውያን ና ለ ኢትዮጵያውያ ንም ጭምር ለ ፕሮፖጋንዳ የሚ ጠቅመው የ ሬዲዮ አገልግሎት ጀም ሯል',\n", - " 'tr_58_tr01058': 'አስከሬ ን አጃቢ ዎች በ ዱላ ተ ደበደቡ',\n", - " 'tr_59_tr01059': 'ህገወጥ ግድያ ና እስራት እንዲ ቆም ተጠየቀ',\n", - " 'tr_60_tr01060': 'ሻእቢያ ከ ስድስት መቶ በላይ ኢትዮጵያውያ ን አስሮ እ ያሰቃ የ ነው',\n", - " 'tr_61_tr01061': 'መንግስት በ ኢንቨስትመንት እንቅስቃሴ ላይ የ ተከሰቱ የ ፖሊሲ ና የ አሰራር ግድፈቶች ን ለ ማስወገድ እርምጃ መውሰዱ ከ ግሉ ኢንቨስትመንት ፍሰት የ ሚገኘው ን ድርሻ እንደሚያ ሻሽለው ም ገለጹ',\n", - " 'tr_62_tr01062': 'እኔ ግን ነፍጠኛ ም መድፈኛ ም እንዳል ሆ ኩኝ ልንገራችሁ ብዬ እንጂ ፖለቲከኛ ሳል ሆን አሽሙረኛ ነኝ ብዬ እናንተ ን ላሳምናችሁ አል ሞክር ም',\n", - " 'tr_63_tr01063': 'ኮሎኔል በዛብህ ጴጥሮስ የ አማራጭ ሀይሎች ሊቀመንበር የ ዶክተር በየነ ጴጥሮስ ወንድም መሆናቸው ተያይዞ ተ ገልጿ ል',\n", - " 'tr_64_tr01064': 'የ መስተዳድሩ መግለጫ ከተማዋ ስር ነቀል ለውጥ እንደሚ ያስፈልጋት ገልጾ ህዝቡ በዚህ እንዲ ሳተፍ ቢ ጠይቅ ም ጊዜያዊ መስተዳድሩ የ መዋቅር ለውጡ ን ያስፈጽማል ተብሎ አይጠበቅ ም',\n", - " 'tr_65_tr01065': 'ለወደፊቱ በሚ ዘጋጀው ጉባኤ የ በ ኩሌን ሀሳብ ለ ካድሬው ይዤ አቀርባ ለሁ',\n", - " 'tr_66_tr01066': 'ኤኤፍፒ ከ ሶስት ሺ በላይ የኤርትራ ኩናማ ዎች ወደ ኢትዮጵያ ሸሽተው በ መግባት የኤርትራ ሰራዊት በ ሀይል እየ መለመላቸው ነው ሲሉ ውንጀላ ሰንዝ ረዋል',\n", - " 'tr_67_tr01067': 'ዋናው አላማችን አባላ ቶቻችን በ ስፖርቱ ተሳታፊ እንዲሆኑ ና ለ ሀገራችን ስፖርት የ በኩላቸው ን አስተዋጽኦ እንዲ ያበረክቱ እንጂ እንደ አንዳንድ ክለቦች ድርጅት ን ለ ማስተዋወቅ አይደለም',\n", - " 'tr_68_tr01068': 'በ ማጠቃለያ ውም በ እርዳታ አ ሰባሰቡ ወቅት ኢህአዲግ በ በጐ አይ ን የማ ይመለከታቸው ና በ አሸባሪነት ጠርጥሬ ያ ቸዋለሁ የሚ ላቸው ኢትዮጵያውያ ን የ ህግ ታራሚዎች ሳይ ቀሩ በ እርዳታው ተሳትፎ ማድረጋቸው ን አመልክ ቷል',\n", - " 'tr_69_tr01069': 'አውደ ጥናቱ ችግሩ ን ለ መቅረፍ የ ተጀመሩ ጥረቶች ን ለ ማገዝ የ ሚያስችል እንደሆነ ም ገልጸዋል',\n", - " 'tr_70_tr01070': 'የሚ ሆነው እውነተኛ ወሬ ዜና ነው',\n", - " 'tr_71_tr01071': 'ይሄን ኛው ን አዋጅ እንዴት እንደ ተቀበሉት ባ ና ውቅም ቅሉ እንዲ ህ ተነቦ ነበር',\n", - " 'tr_72_tr01072': 'ኢህአዲግ ያለ ተወዳዳሪ ብቻ ውን ሮጦ ብቻ ውን ነው ያሸነፈ ው',\n", - " 'tr_73_tr01073': 'ይህ ስ ከ ተጽእኖ ዎቹ አንዱ ሊሆን አይችልም',\n", - " 'tr_74_tr01074': 'ይሁን እንጂ ውሳኔው ቀደም ብሎ የተጻፈ ና የ ተፈረመ በመሆኑ የ እለቱ ን ችሎት እንደማያስ ተጓጉለው አቶ መንበረ ጸሀይ ገልጸው ብይኑ ንና ትእዛዙ ን ማሰማት ቀጥ ለዋል',\n", - " 'tr_75_tr01075': 'አስራ ሁለታችን ን ከ ማእከላዊ ኮሚቴ ለ ማገድ የተወሰደ እርምጃ ነው',\n", - " 'tr_76_tr01076': 'አዲስ አበባ ውስጥ ያሉት ሰራተኞች ተቃውሞ የሚያቀርቡ ት ከ ከተማ ላለ መውጣት ነው',\n", - " 'tr_77_tr01077': 'የ ዩኒቨርስቲ ተማሪዎች በ አውሮፕላን እንዳይ ሳ ፈሩ ተከለከለ',\n", - " 'tr_78_tr01078': 'ምግቡ ለ ኢትዮጵያ ሰራዊት እንዳይደርስ ዋስትና መሰጠት አለ በት',\n", - " 'tr_79_tr01079': 'የ ኢትዮጵያ ና የኤርትራ ልኡካን አሜሪካ ውስጥ ሊ ነጋገሩ ነው',\n", - " 'tr_80_tr01080': 'አጽማቸው አፋር ክልል እንዳረፈ ም የሚናገሩ ምንጮች አሉ',\n", - " 'tr_81_tr01081': 'የ ማህበሩ መሪ ዶክተር ታዬ ወልደሰማያት ማስረጃ በ ሌለው ና ባል ተጣራ ምክንያት ለ እስር በቅ ተዋል',\n", - " 'tr_82_tr01082': 'በ ደጀን ሙስሊሞች ብሩህ ተስፋ ይታ ያል',\n", - " 'tr_83_tr01083': 'ማክሰኞ አዲስ አበባ ላይ በ አስር ሰአት ባንኮች ከ ትራንስ ኢትዮጵያ ነበር የ ተጫወቱ ት',\n", - " 'tr_84_tr01084': 'አ ና ም ዶክተር ሊ ዲዮ ቶሌዶ ከ ረዳታቸው ከ ዶክተር ጆ ሀኪም ዳ ሞታ ጋር በ መሆን ሮናልዶ ን ወደ ሊ ላስ ክሊኒክ ይወስዱ ታል',\n", - " 'tr_85_tr01085': 'ለ ምሳሌ ዲዮ ን ደብሊን ን ፓትሪክ ኩላይቨርት ን ን ሮናልድ ዴ ቦዬርን ና የኢንተሩ ን ንዋንክዎ ካኑ ን ለ መውሰድ ድርድር ጀምረው መጨረሻው ን ሳያዩ ት ተዋል',\n", - " 'tr_86_tr01086': 'እ ውን ኢትዮጵያ ቡና ልት ገባ ነው ላንተ ያለ ኝ አድናቆት ፍጹም ልዩ ነው',\n", - " 'tr_87_tr01087': 'ካፍ በ ግንቦት ወር ለ ሶስት እጩ ኢንስ ትራክተሮች በ ግብጽ ኮርስ እንደሚ ሰጥ አያይዘው አስረድ ተዋል',\n", - " 'tr_88_tr01088': 'በ ኔ ላይ እምነት እንዳለው ገለጸ ልኝ',\n", - " 'tr_89_tr01089': 'የ ኢትዮጵያ አየር መንገድ አውሮፕላኖቹ ን በ ሁለት ና በ ሶስት አመታት ውስጥ በ አዲሶቹ ለ መተካት እቅድ እንዳለው ገለጠ',\n", - " 'tr_90_tr01090': 'እርስዎ ስ ንግድ ዎን ለ ማስፋፋት ይኸ ን ን የ መገናኛ መሳሪያ አስብ ው በታል ን',\n", - " 'tr_91_tr01091': 'ኩባንያው ሰባ አንድ ነጥብ ሰማኒያ አምስት አክሲዮ ኖች ሲ ኖሩት እ ያንዳንዷ አክሲዮን አምስት ሺ ብር ዋጋ አላ ት',\n", - " 'tr_92_tr01092': 'የመንግስት መዋቅሮች ደካሞች ናቸው',\n", - " 'tr_93_tr01093': 'አንዳንዴ ም ሲያ ቃዣ ቸው የ ጐሰኛ ኢትዮጵያ ን ፈጥረ ናል ህዝቦች ፈንጥዘው በ ኢትዮጵያዊ ነታቸው ኮር ተው ተቀብለው ናል ለማ ለት ይዳዳ ቸዋል',\n", - " 'tr_94_tr01094': 'ስለዚህ ም እንደ ገና የ ረሀቡ ን ቁልቁለት ይ ያያ ዘዋል',\n", - " 'tr_95_tr01095': 'እነዚህ ና የ መሳሰሉት ድሎች የ ዚያ ትውልድ አባላት እንደ ጧፍ በር ተው እንደ ሰም ቀል ጠው የ ተገኙ ድሎች ናቸው',\n", - " 'tr_96_tr01096': 'እድሜ አቸው ጠና ያሉ አንድ አዛውንት ገበሬ እንዲ ህ አሉ',\n", - " 'tr_97_tr01097': 'ስንቅ ማቅረብ እጅግ አ ዳግ ቶታል',\n", - " 'tr_98_tr01098': 'እኔ ም ዛሬ አንድ ያደረገ ን ምክንያት በ መፈጠሩ ደስ ብሎ ኛል',\n", - " 'tr_99_tr01099': 'እነሆ ከ አስር አመት በኋላ ሼህ አላሙዲ ን ያቺ ን ወጣት እዚያ ው የ ተዋወቁ በት ዋሽንግተን ውስጥ በ ደመቀ ሰርግ አገ ቧት',\n", - " 'tr_100_tr01100': 'አለቃ የጻፏቸው መጽሀፍት ውድ ና ጣፋጭ ከ መሆናቸው የተነሳ በ ህትመታቸው ወቅት ገዝተው ከሚ ጠቀሙ ት ብልህ ዎች በስተቀር ዘግይተው የ ሚፈልጓቸው ሰዎች አ ያገኟቸው ም',\n", - " 'tr_101_tr02001': 'በ ኮምፒውተር ሳይንስ ፎን ት ቴክኖሎጂ ለ ዶክትሬት ዲግሪ ጥናት እያደረጉ የሚገኙት ን አቶ ፍቅሬ ን የ ዛሬው እንግዳ ችን አድርገ ና ቸዋል',\n", - " 'tr_102_tr02002': 'የ ውሀው ዘርፍ ያለበት ን የ ፋይናንስ ችግር ለ መፍታት የ ውሀ ሀብት ልማት ፈንድ እንደሚ ቋቋም ገለጹ',\n", - " 'tr_103_tr02003': 'የ መንገደኞች ማስተናገጃ ህንጻው በ ሰአት እስከ ሶስት ሺ ያህል መንገደኞች ን ማስተናገድ ይችላል',\n", - " 'tr_104_tr02004': 'መቼም ትላንት ጀምሮ የሰኔ ጾም ገብቷል',\n", - " 'tr_105_tr02005': 'ሚስት አ ግብተው ሶስት ልጆች በት ነው የ ጠፉት ቄስ ፊሊ ጶ ስ ደብር ተገኙ',\n", - " 'tr_106_tr02006': 'አፍሪካ ውስጥ ከሚገኙ ት አገሮች ም እንኳ ን ስ ልት ገዛ ቀርቶ እርሷ እራሷ ገዢ ተ ብላ በ ዘመነ ኞቹ ተፈርጃ ለች',\n", - " 'tr_107_tr02007': 'በ ኬንያ መንግስት በ ኘሮ ፌሽና ሎች የ ታቀፈ ግድያ ማለቱ ተ ገልጧል',\n", - " 'tr_108_tr02008': 'ፓትርያርኩ ንም እንዳት ቃወ ሟቸው በ ማለት ማስጠንቀቂያ ና ዛቻ አዘል ትምህርት መስጠታቸው ነው',\n", - " 'tr_109_tr02009': 'የሚደረግ ባቸውን በደል ና ተንኮል በ ቸልታ ያለፉ መስለው ያደ ባሉ',\n", - " 'tr_110_tr02010': 'እስራኤል የ ኢትዮጵያ ደጋፊ ና ት በ ማለት ወቀሱ',\n", - " 'tr_111_tr02011': 'ንግድ ባንክ ን ያስ ተዳድራ ሉ የተባሉት ህንዶች አን መጣ ም አሉ',\n", - " 'tr_112_tr02012': 'ጥያቄዎች ያሉት ይ ጠይቅ ያጣራ',\n", - " 'tr_113_tr02013': 'የ ኢትዮጵያ አላማ አሁን ግቡ ን መ ቷል',\n", - " 'tr_114_tr02014': 'ገዢው ፓርቲ የ ህወሀት የ ሞኖፖሊ ኩባንያዎች ተደራጅተው ኢኮኖሚው ን መቆጣጠራቸው ን ይቃወ ማሉ',\n", - " 'tr_115_tr02015': 'አባ ጳውሎስ በ እንቁላል ተ ደበደቡ',\n", - " 'tr_116_tr02016': 'የ ሱዳን ና የ ኢትዮጵያ ድንበር ስብሰባ ዛሬ ይጀ መራል',\n", - " 'tr_117_tr02017': 'የ ኢትዮጵያ መንግስት ወደ ሶማሊያ ወታደሮች ልኳ ል መባሉ ን አስተባ በሉ',\n", - " 'tr_118_tr02018': 'ፕሬዚዳንቱ በ ጉባኤው ላይ የ ኢትዮጵያ ን አቋም የሚያ ንጸባርቅ ንግግር እንደሚያደርጉ ይጠበቃል',\n", - " 'tr_119_tr02019': 'የ ተባበሩት መንግስታት ድርጅት ኢትዮጵያ ውጊያው ን እንድታ ቆም ጠየቀ',\n", - " 'tr_120_tr02020': 'የመጀመሪያ ው ምክንያት ሁኔታው ን ለማፋጠን ነው',\n", - " 'tr_121_tr02021': 'ስለሆነ ም ኢትዮጵያውያ ን እንደ ማንኛውም የውጭ ዜጋ መታየት ያለ ባቸው ጊዜ ደርሷ ል ብለዋል',\n", - " 'tr_122_tr02022': 'የ አለም ህዝቦች ኢትዮጵያ ን ከሚ ያውቁ በት ታሪካዊ ክስተቶች አንዱ የ ኦሎምፒክ መድረክ ነው',\n", - " 'tr_123_tr02023': 'አብዛኛዎቹ ባህላቸው እንደሚ ፈቅድላቸው ይናገራሉ',\n", - " 'tr_124_tr02024': 'ይህ የ ጸና አቋማችን ለ ወዳጆቻችን ም ሆነ ለገዳዮ ቻችን ግልጽ ሊሆን ይገባል',\n", - " 'tr_125_tr02025': 'በ ተጨማሪ ም ም ንም አይነት የ ውጪ ቋንቋ ያለ መቻላቸው በ ቁጥጥሩ ስራ ላይ አሉታዊ ተጽእኖ እንዳለው ዘገባው ያስረዳ ል',\n", - " 'tr_126_tr02026': 'ከ ተመላሽ ኢትዮጵያውያ ን የ ሚገኘው መረጃ እስረኞቹ ግፍ ና በደል እየ ተፈጸመባቸው ነው የሚ ል መሆኑን አስ ታውቋል',\n", - " 'tr_127_tr02027': 'ኢትዮጵያ ና ግብጽ ስለ አባይ ሊ ነጋገሩ ነው',\n", - " 'tr_128_tr02028': 'በ ኮንፈረንሱ ላይ ከ አራት መቶ የማ ያንሱ የተለያዩ ኩባንያዎች ና ሀገሮች ተወካዮች እንዲሁም የውጭ ሀገር ጋዜጠኞች ተገኝ ተዋል',\n", - " 'tr_129_tr02029': 'የ አቶ በሽር ገለቴ ን ስድስት ላሞች አውጥተው ሲ ኳት ኑ አደሩ',\n", - " 'tr_130_tr02030': 'ቤተሰብ ህ ውስጥ እግር ኳስ ትልቅ ቦታ አለ ው ተብሎ ተጠይቆ ኤዌን ሲ መልስ አ ዎን አባቴ ቴሪ ፕሮፌሽናል ኳስ ተጫዋች ነበር ብሏል',\n", - " 'tr_131_tr02031': 'አንዳንድ ሴቶች ደግሞ ይመጡ ና ሳመ ን ይሉ ኛል',\n", - " 'tr_132_tr02032': 'ተጫዋቾቹ ብዙ የሚያ ማርሩ በት ነገር አለ',\n", - " 'tr_133_tr02033': 'በጣም ዲሲፕሊን አክባሪ ነው',\n", - " 'tr_134_tr02034': 'ሊቨርፑል ኤዌን ን ለ ተጨማሪ አመታት ኮንትራት ሊያስ ፈርመው ደሞዙ ን በ እጥፍ አሳድጐ ለታል',\n", - " 'tr_135_tr02035': 'በ ኦሮሚያ ክልል የተወሰኑ ጥቂት ቡድኖች ሊኖሩ እንደሚ ችሉ ያገኘ ነው መረጃ ይ ጠቁ ማል',\n", - " 'tr_136_tr02036': 'ምክንያቱ ም ተጫዋቾቹ ትንፋሽ ስለሚ ኖራቸው እንደ ፈለጋቸው ለ መንቀሳቀስ ይችላሉ',\n", - " 'tr_137_tr02037': 'የ ባባንጊዳ አዲስ ባለቤት በ እናትዋ ኢትዮጵያዊ ት ስት ሆን በ ቅርቡ እዚህ አዲስ አባ መጥታ እንደ ነበር ታውቋል',\n", - " 'tr_138_tr02038': 'ለምን ስ እና ንገላታ ቸዋለን የሚ ል አስተያየት ሰንዝ ረዋል',\n", - " 'tr_139_tr02039': 'ይኸው ችግር በ ኢትዮጵያ አትሌቲክስ ፌዴሬሽን ውስጥ መከሰት ጀም ሯል',\n", - " 'tr_140_tr02040': 'ሁለቱ አሸናፊዎች ለ ኢትዮጵያ ሻምፒዮና ያል ፋሉ',\n", - " 'tr_141_tr02041': 'ነገሩን የሚያ ጠናክረው የ ጁቬ ሀላፊዎች ዘወትር ከ ቪያሊ ጋር በ ስልክ እንደሚ ገናኙ ስለሚ ታወቅ ነው',\n", - " 'tr_142_tr02042': 'የ ኢትዮጵያ ታዳጊ ቡድን የ ሞዛምቢክ አቻው ን አሸንፎ ትላንትና ጠዋት አዲስ አባ ገብቷል',\n", - " 'tr_143_tr02043': 'ኢትዮጵያ በ አንሚ ላይ አዲስ ትእዛዝ አ ወጣች',\n", - " 'tr_144_tr02044': 'እናቶች አባቶች ወንድሞች ና እህቶች ያለ ጧሪ ና ተቆርቋሪ ቀር ተዋል',\n", - " 'tr_145_tr02045': 'በ ላሊበላ ግን ሁሉም ተ ደንቀው ተ ገርመው ና እንደ ተደሰቱ ይናገራሉ',\n", - " 'tr_146_tr02046': 'የ ኢትዮጵያ መንግስት በ አካባቢው አሉ ብሎ የሚ ጠረጥ ራቸውን ተቃዋሚዎች እንቅስቃሴ ለ መግታት በ ቅርቡ ወደ ሱማሊያ ተጨማሪ ሰራዊቱ ን እንዳስገባ ሲ ሲ አይ የ ተሰኘው ሬድዮ ገልጿ ል',\n", - " 'tr_147_tr02047': 'የ ተማሪዎቹ አመጽ ቀጥ ሏል ወደ ሌሎች ዩኒቨርስቲ ዎችም ተዛ ም ቷል',\n", - " 'tr_148_tr02048': 'የ ሟች ማንነት ን ሙሉ በ ሙሉ እንዳል ተደረሰበት ፖሊስ አስ ታውቋል',\n", - " 'tr_149_tr02049': 'ስድስት መቶ የሚሆኑ የ ኢትዮጵያ ና የ ሶማሊያ ስደተኞች የመን ገቡ',\n", - " 'tr_150_tr02050': 'በ ተጨማሪ ም ኢትዮጵያ ውስጥ ውንብድና ፈጽመው ወደ ኬንያ የ ገቡት ን ሽፍቶች ሽፋን ሲሰጡ ቆይ ተዋል',\n", - " 'tr_151_tr02051': 'ስህተት ያለበት የ ምርጫ ቅጽ ተገኘ',\n", - " 'tr_152_tr02052': 'ይህኛው ዘዴ ካልሰራ ኢህአዴግ ን ማለት ም የ ኢትዮጵያ ን መንግስት ሊ ያዳክሙ የሚችሉ እርምጃ ዎችን ይወስዳ ል',\n", - " 'tr_153_tr02053': 'አገር እያስ ረከብ ን ነው ከ ወጣ ን ስ በኋላ ም ን ሰራ ን ስለ ስደት ና ስደተኞች ውይይታችን ን እን ቀጥል',\n", - " 'tr_154_tr02054': 'አንዳንድ ጊዜ እንደ ጮሌ ስለሚያ ደርገኝ ስለሚ ሞክረ ኝ እጄ ን አልሰጠ ሁም',\n", - " 'tr_155_tr02055': 'ዛሬ ብዙዎቻችን ማተባ ችንን በ ጥሰን ወይም ቆርጠን ጥለናል',\n", - " 'tr_156_tr02056': 'በ ኢትዮጵያ ም በኩል ተመሳሳይ እርምጃ ዎች እየ ታዩ ናቸው',\n", - " 'tr_157_tr02057': 'ይህ በዚህ እንዳለ ዋሽንግተን ዲሲ የ ሚገኘው የ ኢትዮጵያ ኤምባሲ ለ ቅስቀሳ ና ለ ፕሮፓጋንዳ ተግባር በር ከ ት ያሉ ሰዎች ለ መቅጠር ማስታወቂያ ዎችን በ ሬዲዮ እያ ሰማ ይገኛል',\n", - " 'tr_158_tr02058': 'የ ዋሽንግተን ዲሲ የ ጦቢያ ሪፖርተር እንደ ዘገበው ከ ዳላስ ቴክሳስ ሌሊት መኪና እየ ነዱ የ መጡ ኢትዮጵያውያ ን ነበሩ',\n", - " 'tr_159_tr02059': 'አንደኛ የ ጤና ና የ ተፈጥሮ ሳይንስ ተማሪዎች የሚ ገለገሉ ባቸው በተለይ ም የ ተፈጥሮ ሳይንስ ተማሪዎች ላቦራቶሪ ዎች ለ አንደኛ አመት ተማሪዎች ብቻ ሊ ያገለግሉ የሚችሉ ናቸው',\n", - " 'tr_160_tr02060': 'የ ሻእቢያ መንግስት ከ ሀገሩ የሚያስ ወጣቸው የ ኢትዮጵያውያ ን አብዛኞቹ የተ ደበደቡ የተ ገረፉ የ ተዘረፉ ና በተለይ ም ሴቶቹ የ ተደፈሩ መሆናቸው ን ዘመን አስ ታውቋል',\n", - " 'tr_161_tr02061': 'መንግስት በ ኢንቨስትመንት እንቅስቃሴ ላይ የ ተከሰቱ የ ፖሊሲ ና የ አሰራር ግድፈቶች ን ለ ማስወገጃ እርምጃ መውሰዱ ከ ግሉ ኢንቨስትመንት ፍሰት የ ሚገኘው ን ድርሻ እንደሚያ ሻሽለው ም ገለጹ',\n", - " 'tr_162_tr02062': 'እኔ ግን ነፍጠኛ ም መድፈኛ ም እንዳል ሆ ኩኝ ልንገራችሁ ብዬ እንጂ ፖለቲከኛ ሳል ሆን አሽሙረኛ ነኝ ብዬ እናንተ ን ላሳምናችሁ አል ሞክር ም',\n", - " 'tr_163_tr02063': 'ኮሎኔል በዛብህ ጴጥሮስ የ አማራጭ ሀይሎች ሊቀመንበር የ ዶክተር በየነ ጴጥሮስ ወንድም መሆናቸው ተያይዞ ተ ገልጿ ል',\n", - " 'tr_164_tr02064': 'የ መስተዳድሩ መግለጫ ከተማዋ ስር ነቀል ለውጥ እንደሚ ያስፈልጋት ገልጾ ህዝቡ በዚህ እንዲ ሳተፍ ቢ ጠይቅ ም ጊዜያዊ መስተዳድሩ የ መዋቅር ለውጡ ን ያስፈጽማል ተብሎ አይጠበቅ ም',\n", - " 'tr_165_tr02065': 'ለወደፊቱ በሚ ዘጋጀው ጉባኤ የ በ ኩሌን ሀሳብ ለ ካድሬው ይዤ አቀርባ ለሁ',\n", - " 'tr_166_tr02066': 'ኤኤፍፒ ከ ሶስት ሺ በላይ የኤርትራ ኩናማ ዎች ወደ ኢትዮጵያ ሸሽተው በ መግባት የኤርትራ ሰራዊት በ ሀይል እየ መለመላቸው ነው ሲሉ ውንጀላ ሰንዝ ረዋል',\n", - " 'tr_167_tr02067': 'ዋናው አላማችን አባሎቻችን ን በ ስፖርቱ ተሳታፊ እንዲሆኑ ና ለ ሀገራችን ስፖርት የ በኩላቸው ን አስተዋጽኦ እንዲ ያበረክቱ እንጂ እንደ አንዳንድ ክለቦች ድርጅት ን ለ ማስተዋወቅ አይደለም',\n", - " 'tr_168_tr02068': 'በ ማጠቃለያ ውም በ እርዳታ አ ሰባሰቡ ወቅት ኢህአዲግ በ በጐ አይ ን የማ ይመለከታቸው ና በ አሸባሪነት ጠርጥሬ ያ ቸዋለሁ የሚ ላቸው ኢትዮጵያውያ ን የ ህግ ታራሚዎች ሳይ ቀሩ በ እርዳታው ተሳትፎ ማድረጋቸው ን አመልክ ቷል',\n", - " 'tr_169_tr02069': 'ወረዳው በተ ለምዶ ገዳም ደጃች ው ቤ ና ጣሊያን ሰፈሮች የሚ ባሉት ን አካባቢዎች ያካተተ ነው',\n", - " 'tr_170_tr02070': 'ጉዳዩ አቶ መለስ ዘንድ እንዲደርስ ና ትእዛዝ እንዲሰጥ በት ተደርጓል',\n", - " 'tr_171_tr02071': 'እሱ ይቅር ና የ ዘበኞቹ ን ስራ እናውጋ ችሁ',\n", - " 'tr_172_tr02072': 'ኢህአዴግ የሚ ገዛቸው ተዋጊ ሄሊኮኘተሮች ከ ድል በኋላ ለ ተቃዋሚዎች እንደሚ ውሉ ተገለጠ',\n", - " 'tr_173_tr02073': 'ኢ ሰብአዊ ና ክብር ን የሚ ያዋርድ ቅጣት ተቀጡ',\n", - " 'tr_174_tr02074': 'የ ኢትዮጵያ ንግድ ባንክ የ ቦርድ አባላት ሊ ነሱ ነው',\n", - " 'tr_175_tr02075': 'በ ድርጅታችን ህገ ደንቡ ሶስት ማእከላዊ ተቋማት አሉ',\n", - " 'tr_176_tr02076': 'እነርሱ ን አባር ረን እናንተ ን በምት ካቸው እናስገባ ለ ን የሚሉ ማስፈራሪያ ዎችና ዛቻ ዎችም በ የ ስብሰ ዎቹ ላይ ቀርበዋል ተ ብሏል',\n", - " 'tr_177_tr02077': 'አንዳንድ ትኬት የ ቆረጡ ተማሪዎች ም እንዳይ ሳ ፈሩ ተከልክ ለዋል ሲሉ አ ማረሩ',\n", - " 'tr_178_tr02078': 'ኢትዮጵያ የተያዘ ባትን መሬት ለ ማስመለስ በ ሰላሙ መስክ ስላልተሳካ ላት የ ሀይል እርምጃ ተጠቅ ማለች',\n", - " 'tr_179_tr02079': 'የኤርትራ መንግስት ሰባ ዘጠኝ ኢትዮጵያውያ ን ን በ ግፍ አረደ',\n", - " 'tr_180_tr02080': 'ይህን እናንተ ም እኛ ም አሳ ም ረን እናውቃለን',\n", - " 'tr_181_tr02081': 'የ ኖርዌይ የ ማእድን ካምፓኒ ኢትዮጵያ ውስጥ እንዲ ሰራ ፈቃድ ተሰጠው',\n", - " 'tr_182_tr02082': 'በ ደጀን ሁለት መስጊዶች ይገኛሉ',\n", - " 'tr_183_tr02083': 'ኢትዮጵያ ቡና መድን ን በ ጨዋታ በልጦ ነው ያሸነፈ ው',\n", - " 'tr_184_tr02084': 'ይህንን ም ለ ቡድን መሪው ለ ጃን ፒየር ፍራን ኬን ሂስ ያስታው ቃሉ',\n", - " 'tr_185_tr02085': 'ቬንገር በተለይ አጥቂው ክፍል ሊ ያሳስባቸው ይገባል',\n", - " 'tr_186_tr02086': 'ቡቡ ኢትዮጵያ ቡና ሊገባ ነው የ ሚባለው ወሬ በ ሰፊው እየ ተወራ ነው',\n", - " 'tr_187_tr02087': 'ያሉት ን አባባል ለ መድገም ተገ ደናል',\n", - " 'tr_188_tr02088': 'እዚህ ሙኒክ ውስጥ ግን የማ ተኩረው ስራዬ ላይ ብቻ ነው',\n", - " 'tr_189_tr02089': 'ፕሬዚዳንት ነጋሶ አሁን ም በ ተጽእኖ ስር ናቸው',\n", - " 'tr_190_tr02090': 'እሺ እኔ ትግሬ ነኝ ኢትዮጵያዊ ም ነኝ',\n", - " 'tr_191_tr02091': 'የ ኢትዮጵያ ንግድ ባንክ አዲስ ቦርድ ተሾመ ለት',\n", - " 'tr_192_tr02092': 'ስራ አስፈጻሚው ም ጠቅላይ ሚኒስትሩ ም ውክልናው ለ ፓርላማው መሆን ሲ ገባው ለ ፓርቲው ነው',\n", - " 'tr_193_tr02093': 'አስተዳደግ አርቆ አስተዋይ ነት እንዲሁም ቀና የ ልማት አስተዋጽኦ ያጠና ክ ረዋል',\n", - " 'tr_194_tr02094': 'ለዚህ ም ነው የ ኢሀዴግ ሹሞች እየ ደጋገሙ ችጋር ን ማስ ወገዳቸው ንና አገሪቱ ን ወደ እህል ሻጭ ነት በ አጭር ጊዜ ውስጥ አደረሰ ን እያሉ የሚፎክሩት',\n", - " 'tr_195_tr02095': 'እንደ ኢህአፓ ከ መሳሰሉ ትናንሽ ድርጅቶች ጋር ግንኙነት ፈጥረው ከ ኢትዮጵያ መንግስት ጋር ያ ላቸውን ግንኙነት ማበላሸት አይ ሹም',\n", - " 'tr_196_tr02096': 'አንዱ ክፉ ኛ ቆስሎ ተመል ሷል',\n", - " 'tr_197_tr02097': 'ውስጥ አዋቂ ምንጮች እንደሚ ጠቁሙ ትም ኢትዮጵያ ውስጥ ያሉ ና እስካሁን ያል ተባረሩ ኤርትራውያን በ ጸረ ሻእቢያ ድርጅት እየ ተሰባሰቡ ናቸው',\n", - " 'tr_198_tr02098': 'የ ሻእቢያ መንግስት ከ ኢትዮጵያ ህዝብ ተለያይ ቷል',\n", - " 'tr_199_tr02099': 'በ አጥቂ መስመር ተሰልፎ የሚ ጫወተው አስራ ሁለት ቁጥሩ ከ አማካዮ ች የተሰጠ ውን ኳስ ያለምን ም ጭንቀት ያደርስ የነበረው ለ ጊዮርጊስ ተጫዋቾች ነበር',\n", - " 'tr_200_tr02100': 'ሁለቱ ባለስልጣናት በ ስብሰባው ላይ ድምጻቸው ን ከፍ አድርገው እስከ መጯጫህ ደርሰው እንደ ነበር የ ውስጥ አዋቂ ምንጮች ገልጸው ልናል',\n", - " 'tr_201_tr03001': 'የ ማስተር ስ ዲግሪ ዎን ካገኙ በኋላ በምን ስራ ተ ሰማሩ',\n", - " 'tr_202_tr03002': 'በ ኢትዮጵያ ና በ ሱዳን መካከል ያለውን ንግድ ና ኢንቨስትመንት ለ ማጠናከር የሚያስችሉ ተግባራት ይ ከናወ ና ሉ',\n", - " 'tr_203_tr03003': 'በውጭ ሀገር እያሉ በ ሞት በሚ ለዩ ባለመብት ኢትዮጵያውያ ንም መብታቸው ለ ወራሾቻቸው እንደሚጠበቅ አቶ ና ፖሊዮ ን ጨምረው ገልጸዋል',\n", - " 'tr_204_tr03004': 'ሱባኤ ገብቷል ትሉ ይሆናል',\n", - " 'tr_205_tr03005': 'መጋ ቤ ስርአት ግን በ መገኘታቸው ሰማይ መሬቱ ተደፋ ባቸው እና ም ምስኪን ዋን የ ሶስት ልጆች እናት ሚስት አላውቅ ሽም አይንሽ ን እንዳላ ይሽ የሚ ል መርዶ ይነግ ሯ ታል',\n", - " 'tr_206_tr03006': 'ለ ሱዳን መንግስት የ ገቡ አንጃዎች መሳሪያ ተነጠቁ',\n", - " 'tr_207_tr03007': 'በ ኤርትራ የሚገኙ ኢትዮጵያዊያ ን ወደ ሀገራቸው ለ መመለስ የሚያስ ች ሏቸው መንገዶች እየጠ በቡ መጥ ተዋል',\n", - " 'tr_208_tr03008': 'ኢሳያስ ኢትዮጵያ ን በ ሳኡዲ አሳ ቀሉ',\n", - " 'tr_209_tr03009': 'ከብሩ ሴል ጉባኤ የ አውሮፓ መንግስታት ኢትዮጵያ በ ጣሊያን መንግስት ስር እንድት ገዛ ሲ ስማሙ አጼ ምንሊክ ነገሩን በ ፌዝ አይ ተውታል',\n", - " 'tr_210_tr03010': 'ዋናው ፍላጐታቸው ንግድ ነው',\n", - " 'tr_211_tr03011': 'የ ኢትዮጵያ ንግድ ባንክ ን ማኔጅመንት ተ ረክበው እንዲ ያስተዳድሩ የ ተፈቀደላቸው ህንዶች እንደማይ መጡ በ ደብዳቤ አስ ታወቁ',\n", - " 'tr_212_tr03012': 'የሚ ያስፈልገን ነገር ቢኖር ኢን ፎሜሽን ነው',\n", - " 'tr_213_tr03013': 'የ ሶማሊያ አንጃ መሪ የ ኢትዮጵያ ጣልቃ ገብነት ተገቢ ነው አሉ',\n", - " 'tr_214_tr03014': 'ለ ተወካዮች ምክር ቤት ስድስት ለ ክክ ለ ክልል ምክር ቤት አስራ ስምንት እጩዎች አቅርቧ ል',\n", - " 'tr_215_tr03015': 'ከ ትናንት በስቲያ ም ኢትዮጵያ ብሩንዲ ን በ አምስት አምስት ም ቶች ሰባት ለ ስድስት የ ሩዋንዳ ሀ ኡጋንዳ ን ሶስት ለ ሁለት በሆነ ውጤት ረት ተዋል',\n", - " 'tr_216_tr03016': 'በ አቡነ ጢሞ ቲዎስ ምትክ አዲሱ የ ኢትዮጵያ ኦርቶዶክስ ተዋህዶ ቤተ ክርስቲያን ልማት ና ክርስቲያናዊ ኮሚሽን ኮሚሽነር ሆነው የ ተሾሙት ብጹእ አቡነ ኒምቆዲሞስ ናቸው ተ ብሏል',\n", - " 'tr_217_tr03017': 'ኢሪን እንደሚ ለ ው ዲፕሎማቱ ኢትዮጵያ የ ሶማሌ ሀይሎች ን የ ም ታሰለጥን በት ወይም ጣልቃ የምትገባ በት ምክንያት የ ለ ም በ ማለት ተናግረ ዋል',\n", - " 'tr_218_tr03018': 'የ ናይጄሪያ ው ፕሬዚዳንት ኦሉሴጉን አባ ሳንጆ እንደ ዚህ ሲሉ ለ ሮይተር ዜና ወኪል ተናግረ ዋል',\n", - " 'tr_219_tr03019': 'ገበሬዎች ን እያ ሰፈሩ ነው',\n", - " 'tr_220_tr03020': 'ለ ተከራካሪ ዎቹ መንግስታት ግን ይጠቅማ ቸዋል',\n", - " 'tr_221_tr03021': 'ኤርትራውያን በ ኢትዮጵያ ትልቅ ስፍራ ከፍተኛ ስልጣን ተሰጥቷ ቸዋል',\n", - " 'tr_222_tr03022': 'ሶማሊያውያን በ ዋሽንግተን ኢትዮጵያ ን በ መቃወም ሰልፍ ወጡ',\n", - " 'tr_223_tr03023': 'ክሱ ን እንዳላ ንቀሳቅስ ም የ ባህል ተጽእኖ ተደረገ ብኝ ት ላለች',\n", - " 'tr_224_tr03024': 'ይህንን የኤርትራ መንግስት እርምጃ በ ተባበሩት መንግስታት የ ኢትዮጵያ ና የኤርትራ ተልእኮ አንሚ እንዲሁም አደራዳሪ አካላት ሊ ያወግዙ ት ይገባል ሲሉ ጥሪ አቅርበ ዋል',\n", - " 'tr_225_tr03025': 'ሚድሮክ በተ ባለ ኩባንያ ሰፋ ያሉ የ ኢንዱስትሪ ግምባታ ዎችን እያደረጉ ናቸው',\n", - " 'tr_226_tr03026': 'ነገር ግን የ ዋስ መብት ተፈቅዶ ላቸዋል',\n", - " 'tr_227_tr03027': 'ከ ሚኒስትሮቹ ቀደም ብለው ከ የሀገሮቹ የሚውጣ ጡ የ ውሀ ሀብት ኤክስፐርቶች ና ባለሙያዎች የሚካፈሉ በት አውደ ጥናት ሶደሬ ውስጥ የሚካሄድ መሆኑ ም ተ ገልጿ ል',\n", - " 'tr_228_tr03028': 'አየር መንገዱ አዳዲስ አውሮፕላኖች ን የ መግዛት እቅዱ በ ኢትዮ ኤርትራ ጦርነት የ ተጨናገፈ ቢሆን ም በሚ ቀጥሉ ት ስድስት ወራት ውሳኔ እንደሚ ያገኝ ለማወቅ ተችሏል',\n", - " 'tr_229_tr03029': 'ሊያስ ቅ የሚ ቃጣው መልስ ሰጡ',\n", - " 'tr_230_tr03030': 'ከ ሊቨርፑል ህጻናት ማእከል ውስጥ የ ገባሁት ገና የ አስር አመት ልጅ እያለሁ ነው',\n", - " 'tr_231_tr03031': 'አንዳንዱ በ ቁመና ው አንዳንዱ በ ኳስ ችሎታው አንዳንዱ ጐል አግብቶ በሚ ያሳየው እንቅስቃሴ የ ተመልካች ን ልቦና ሰር ቋል',\n", - " 'tr_232_tr03032': 'ደሞዝ አነስተኛ ነው ኢንሴ ን ቲቩ ም እንዲ ሁ እና ም አን ፈርም ም እያሉ ነው',\n", - " 'tr_233_tr03033': 'ፊዮረንቲና ዎች ሮቢን እን ወድ ሀለን እያሉ በ እንባ ነበር የ ሸኙት',\n", - " 'tr_234_tr03034': 'የ ኦዌን ነገር የሚያ ሳስብ ነው እያሉ ነው',\n", - " 'tr_235_tr03035': 'የ ኦሮሚያ ው ሙገር ከ አዲስ አበባ ክለቦች በተ ቀነሱ ተጫዋቾች ተጠናክሮ ውጤት ማስ መዝገቡ ለ ክልሉ እግር ኳስ እድገት አመጣ ማለት አይደለም',\n", - " 'tr_236_tr03036': 'ማክሰኞ ምሽት በ ተደረጉት ግጥሚያ ዎች ባንኮች ብርሀን ና ሰላም ን ሁለት ለ አንድ ሲ ያሸንፍ ታክሲ ና ኒያላ ሳይ ሸ ና ገፉ ሶስት ለ ሶስት ተለያይ ተዋል',\n", - " 'tr_237_tr03037': 'ረዳት ና ዋናው ዳኛ በ ፈጸሙት ስህተት በ ስታዲየሙ ተገኝቶ የነበረ ተመልካች ተቃው ሟል',\n", - " 'tr_238_tr03038': 'እቅዱ ን ለ ጊዜው ተግባራዊ ለማድረግ እንዳል ተቻለ ለ መረዳት ች ለናል',\n", - " 'tr_239_tr03039': 'አቶ ስ ለምነው የመጀመሪያ ዲግሪ ያቸውን ያገኙ ት በ ሰውነት ማጐልመሻ ትምህርት ፊዚካል ኤዲ ኩዌሽ ን ሲሆን ማስተር ሳቸውን ደግሞ በ ፊዚዮቴራፒ ነው',\n", - " 'tr_240_tr03040': 'በ ትክክለኛ እድሜ ላይ የሚገኙት ን ወጣቶች ና ታዳጊዎች ን አቅርበ ን ውጤት ካመጣ ን በ ወርቅ ጽሁፍ ስማችን ን በ ታሪክ ማህደር ላይ ጻፍ ን ማለት ነው',\n", - " 'tr_241_tr03041': 'በ እርግጥ በ ውጪ ሁለቱ ክለቦች ተወዳጅ በ መሆናቸው ና በ መውረዳ ቸው ነው ክትትል እንዳይደረግ ባቸው ያደረገው',\n", - " 'tr_242_tr03042': 'ጐሉ ን ያገባ ው ሙሉ አለም ነው',\n", - " 'tr_243_tr03043': 'ኢትዮጵያ የሺ ላሎ እና ሸሸቢት መሬቶች ን መጠየቅ አለ ባት',\n", - " 'tr_244_tr03044': 'ፕሮጀክቶቹ ተግባራዊ ይሆናሉ ተብለው የሚ ጠበቁት በ ክልላዊ ደርጃ ነው',\n", - " 'tr_245_tr03045': 'ፈ ቲያ ሰኢድ ወይዘሪት አዲስ አበባ ተባለች',\n", - " 'tr_246_tr03046': 'ሰሞኑ ን ወደ ሱማሊያ ፑንትላንድ ከተማ ስለ ገባው የ ኢትዮጵያ ሰራዊት ሬዲዮው ሲ ዘረዝር የ ኢትዮጵያ ወታደሮች ወደ ፑንትላንድ ሲ ገቡ ይህ የመጀመሪያ አይደለም',\n", - " 'tr_247_tr03047': 'ተክለ ማርያም የተባለ ሌላ ተማሪ ም በ መሳሪያ አስገዳጅ ነት እንዳይ ንቀሳቀስ ከ ተደረገ በኋላ እንዳይ ሞት እንዳይ ድን ተደርጐ ተቀጥቅ ቷል',\n", - " 'tr_248_tr03048': 'የ ገብሩ አስራት ጠባቂዎች ታሰሩ',\n", - " 'tr_249_tr03049': 'ባለፉት ሶስት ሳምንታት በ ባህር የመን የ ገቡ የ ኢትዮጵያ ና የ ሶማሊያ ስደተኞች ቁጥር ስድስት መቶ እንደ ደረሰ የ ተባበሩት መንግስታት የ ስደተኞች ጉዳይ ድርጅት ገለጠ',\n", - " 'tr_250_tr03050': 'እንደ አሜሪካ እምነት ና መላ ም ት ኦሮሚያ ነጻነት ዋን ካወጀ ት ኢትዮጵያ ትገነጣጠ ላለች',\n", - " 'tr_251_tr03051': 'ለ ፕሬዚዳንቱ አዲስ መኖሪያ ቤት ና ጽፈት ቤት ሊ ገነባ ነው',\n", - " 'tr_252_tr03052': 'በ አንድ በኩል ከ ኢትዮጵያ ለ መገንጠል አጀንዳ ያ ላቸው ሀይሎች ኢህአዴግ ን አምርረው እንዲ ታገሉ ተጨማሪ ጽናት ያገኛ ሉ',\n", - " 'tr_253_tr03053': 'ከ ኢትዮጵያ የተሰደደ ው ና በ ብዙ ቁጥር ም የሚ ሰደደው አገሩ ን ሊ ገነባ የሚ ችለው ሀይል ነው',\n", - " 'tr_254_tr03054': 'አንዴ አንተ አንዴ አን ቱ እያ ልሁ ተቸገርኩ',\n", - " 'tr_255_tr03055': 'እሱ እንደ ነገረኝ ህግ ትምህርት ቤት በ አንድ ወቅት አብረን ተማሪዎች ነበር ን',\n", - " 'tr_256_tr03056': 'የምናውቀው የ እኛ ዎቹ ገዥዎች ግፊት ተጨምሮ በት ሪፍረንደ ም ተካሂ ዷል ተብሎ ኤርትራ ነጻ መንግስት መሆኗ ን ነው',\n", - " 'tr_257_tr03057': 'የኤርትራ መንግስት የውጭ ምንዛሬ ምንጭ በውጭ የሚገኙ ግማሽ ሚሊዮን ኤርትራውያን ወደ አገራቸው የሚያስ ገቡት የውጭ ምንዛሪ ነው',\n", - " 'tr_258_tr03058': 'ከ አትላንታ ብዙ ሰዎች ተገኝ ተዋል',\n", - " 'tr_259_tr03059': 'ሁለተኛ የ ጂኦግራፊ ና የ ታሪክ ተማሪዎች ም ከ አንድ አመት ተኩል በኋላ በ ዲግሪ እንደ ተፈጥሮ ሳይንስ ተማሪዎች ጓደኞቻቸው ለ መመረቅ እየ ተዘጋጁ ናቸው',\n", - " 'tr_260_tr03060': 'እኔ በ ሙያዬ ግጥም ገጣሚ ና ደራሲ ኢትዮጵያዊ ነኝ',\n", - " 'tr_261_tr03061': 'መንግስት በ ኢንቨስትመንት እንቅስቃሴ ላይ የ ተከሰቱ የ ፖሊሲ ና የ አሰራር ግድፈቶች ን ለ ማስወገድ ርምጃ መውሰዱ ከ ግሉ ኢንቨስትመንት ፍሰት የ ሚገኘው ን ድርሻ እንደሚያ ሻሽለው ም ገለጹ',\n", - " 'tr_262_tr03062': 'እኔ ግን ነፍጠኛ ም መድፈኛ ም እንዳል ሆኩ ልነ ልንገራችሁ ብዬ እንጂ ፖለቲከኛ ሳል ሆን አሽሙረኛ ነኝ ብዬ እናንተ ን ላሳምናችሁ አል ሞክር ም',\n", - " 'tr_263_tr03063': 'ኮሎኔል በዛብህ ጴጥሮስ የ አማራጭ ሀይሎች ሊቀመንበር የ ዶክተር በየነ ጴጥሮስ ወንድም መሆናቸው ተያይዞ ተ ገልጿ ል',\n", - " 'tr_264_tr03064': 'የ መስተዳድሩ መግለጫ ከተማዋ ስር ነቀል ለውጥ እንደሚ ያስፈልጋት ገልጾ ህዝቡ በዚህ እንዲ ሳተፍ ቢ ጠይቅ ም ጊዜያዊ መስተዳድሩ የ መዋቅር ለውጡ ን ያስፈጽማል ተብሎ አይጠበቅ ም',\n", - " 'tr_265_tr03065': 'ለወደፊቱ በሚ ዘጋጀው ጉባኤ የ በ ኩሌን ሀሳብ ለ ለ ካድሬው ይዤ አቀርባ ለሁ',\n", - " 'tr_266_tr03066': 'ኤኤፍፒ ከ ሶስት ሺ በላይ የኤርትራ ኩናማ ዎች ወደ ኢትዮጵያ ሸሽተው በ መግባት የኤርትራ ሰራዊት በ ሀይል እየ መለመላቸው ነው ሲሉ ውንጀላ ሰንዝ ረዋል',\n", - " 'tr_267_tr03067': 'ዋናው አላማችን አባላ ቶቻችን በ ስፖርቱ ተሳታፊ እንዲሆኑ ና ለ ሀገራችን ስፖርት የ በኩላቸው ን አስተዋጽኦ እንዲ ያበረክቱ እንጂ እንደ አንዳንድ ክለቦች ድርጅት ን ለ ማስተዋወቅ አይደለም',\n", - " 'tr_268_tr03068': 'በ ማጠቃለያ ውም በ እርዳታ አ ሰባሰቡ ወቅት ኢህአዲግ በ በጐ አይ ን የማ ይመለከታቸው ና በ አሸባሪነት ጠርጥሬ ያ ቸዋለሁ የሚ ላቸው ኢትዮጵያውያ ን የ ህግ ታራሚዎች ሳይ ቀሩ በ እርዳታ ተሳትፎ ማድረጋቸው ን አመልክ ቷል',\n", - " 'tr_269_tr03069': 'ከ ኢትዮጵያ ውጪ ም በ ጂዳ ና በ ሌሎች አገራት የሚገኙ ኢትዮጵያውያ ን ደስታቸው ን በ መግለጽ ላይ መሆናቸው ን ለማወቅ ተችሏል',\n", - " 'tr_270_tr03070': 'ጀርመን ኢትዮጵያውያ ን ስደተኞች ን ለ መመለስ ከ ስዬ አብርሀ ጋር መከረ ች',\n", - " 'tr_271_tr03071': 'አገሩ እንዳይገባ ም ወንዝ ይሞላ ል',\n", - " 'tr_272_tr03072': 'ባለፈው ሳምንት የ ኬንያው ዜና አገልግሎት ቁጥራቸው አንድ ሺ የሚሆኑ የ ኦነግ ሽምቅ ተዋጊዎች ኬንያ ውስጥ መግባታቸው ን ማሳወቁ የሚ ታወስ ነው',\n", - " 'tr_273_tr03073': 'ስለ ሲኖ ሲኖዶሱ አባላት ና ተቋቁ ሟል ስለ ተባለው ኮሚሽን ጉዳይ ሲናገሩ ም በ ጳጳሳት ና ኮሚሽን በ ተባለው እምነት የ ጣለበት ሰው ካለ በ እጅጉ ተሳስ ቷል',\n", - " 'tr_274_tr03074': 'በ ኢትዮጵያ ና ኤርትራ እስከዛሬ ሲ ሰሩ የቆዩት ን ወታደራዊ አታሼ ዎቿን አሜሪካ ልት ቀይር መዘጋጀቷ ን ታማኝ ዲፕሎማቲክ ምንጮች ገለጹ',\n", - " 'tr_275_tr03075': 'እነዚህ ተቋማት ወሳኝ ማእከላዊ ተቋማት ናቸው',\n", - " 'tr_276_tr03076': 'እስረኞች ከ አዲስ አባ ወደ አልታወቀ ስፍራ እየ ተወሰዱ ናቸው የ ዩኒቨርስቲ ተማሪዎች የ ይቅርታ ቅጽ እንዲ ሞሉ ተጠየቁ',\n", - " 'tr_277_tr03077': 'በ ሰማኒያ ጋዜጠኞች ላይ ክስ ተ መስርቷል እየተ ባለ በ ኢትዮጵያ የ ፕሬስ ነጻነት ተሻሽ ሏል ማለት አይቻል ም',\n", - " 'tr_278_tr03078': 'ይሄ ውሳኔ ውዝግቡ እንዳይ ፈታ ያደረገው አስተዋጽኦ ነው',\n", - " 'tr_279_tr03079': 'የኦሮሞ ተማሪዎች ከ አቶ ጁኔይዲ ጋር ተፋ ጠው ዋሉ',\n", - " 'tr_280_tr03080': 'ጄኔራሉ እስኪ ፈቱ ድረስ ተማጽኖ ና ተቃውሟቸው እንደሚ ቀጥል ም አስታውቀ ዋል',\n", - " 'tr_281_tr03081': 'ሌንጮ ከ ኢህአዴግ ሊ ደራደሩ ይሆን',\n", - " 'tr_282_tr03082': 'ኢስላም በ ልማት መስክ ከ ኢትዮጵያ መስሊሞች ብዙ ይጠበቃል ተ ባለ',\n", - " 'tr_283_tr03083': 'ተጫዋቾቹ ገንዘባቸው ን ከመክ ሰራቸው በ ተጨማሪ ከ ፌዴሬሽኑ ተጨማሪ ቅጣት ሊ ጣል ባቸው በ ዝግጅት ላይ እንደሆነ ለማወቅ ች ለናል',\n", - " 'tr_284_tr03084': 'ዶክተሩ ለ ቡድን መሪው ያስታወቁ ት ለ ብራዚል ፉትቦል ፌዴሬሽን ፕሬዚዳንት ሪ ካርዶ ቴክሴራ ጉዳዩ ን እንዲገልጹ ላቸው ነበር',\n", - " 'tr_285_tr03085': 'በ ጥቃቅን ስህተት ነው ለ ሽንፈት የሚ ጋለጠው',\n", - " 'tr_286_tr03086': 'እና ደስታዬ ን በ መትረየስ ተኩስ አሳ የ ሁት',\n", - " 'tr_287_tr03087': 'በ ቶሮንቶ ቆይታቸው ም ሻምበል ምሩጽ ይፍጠር ን እንዳገኙ ት አጫው ተውናል',\n", - " 'tr_288_tr03088': 'ግን ውስጡ ስገባ ውጪው ና ውስጡ ሊ ጣጣም ልኝ አልቻለ ም',\n", - " 'tr_289_tr03089': 'እነ አባተ ኪሾ ትናንት ፍርድ ቤት ቀረቡ',\n", - " 'tr_290_tr03090': 'ኢትዮጵያ ከ ሰላም አስከባሪ ው ሀይል እንዲ ነሱ ጥያቄ ያቀረበች ባቸው አዛዥ ሜጀር ጄኔራል ፓትሪክ ካማራት አሁን ም ድረስ በ ስራቸው ላይ እንደሚገኙ ተገለጸ',\n", - " 'tr_291_tr03091': 'የ ኢትዮጵያ ና የኤርትራ ብሄራዊ ቡድን ተጫዋቾች ተደባደቡ',\n", - " 'tr_292_tr03092': 'ቢ ያንስ እርስ በ ርሳቸው እንዳይ ተማመኑ አድርጓ ቸዋል',\n", - " 'tr_293_tr03093': 'እብሪት ና ማን አህሎ ብኝ ነት የ በታች ነት ስሜት ነጸብራቅ ናቸው',\n", - " 'tr_294_tr03094': 'የሚ ጠይቃቸው ካገኙ ም ችግራቸው ን ይናገራሉ',\n", - " 'tr_295_tr03095': 'ዞር በ ል ብ ያለሁ ይላል በ ችሎቱ ዙሪያ ያለውን ሰው',\n", - " 'tr_296_tr03096': 'አንዱ ምጽዋ ላይ በ ተደረገው ጦርነት ሞ ቷል',\n", - " 'tr_297_tr03097': 'አፍሪካውያን የ ደህንነት ዋስትና እንዲ ያገኙ ና በ ኢኮኖሚ በ ተሻለ ደረጃ ላይ እንዲ ደርሱ የ አፍሪካ ችግሮች በ ቅንነት ና ገንቢ በሆነ እርምጃ ሊፈቱ ይገባል ብለዋል',\n", - " 'tr_298_tr03098': 'አማራ ን ነጻ ለ ማውጣት ኦሮሞ ን ለ ማንገስ ነው እያ ለ ቀላል ጦርነት የሚ ያካሂድ መስሎ ት የ ኢትዮጵያ ን ድንበር ሊ ደፍር ችሏል',\n", - " 'tr_299_tr03099': 'የ ስፔን ኢንተርናሽናል ተከላካይ የ ሆነው ኢቫ ን ካምፖ የሆላንዱ ኢንተርናሽናል ክላሪየክላረን ሲ ሲ ዶር ፍ ና የ ጣልያኑ ኢንተርናሽናል ክሪስቲያን ፓኑቺ በ ሰጡት አስተያየት አሰልጣኙ ተማረ ዋል',\n", - " 'tr_300_tr03100': 'በ ኢትዮጵያ እንዳ የ ነው ኤርትራውያኑ ና አስተባባሪ ዎቻቸው እዚያ ም ህግ ና ስነ ስርአት ጥሰው የ አካባቢው ን ህዝብ ሰላም አደፍ ርሰው ስለ ተገኙ በ ፖሊሶች ና በ ሄሊኮፕተሮች እስከ መበተን ደርሰዋል',\n", - " 'tr_301_tr04001': 'ትምህርቴ ን እንደ ጨረስኩ ወገኖቼ ን ለ መርዳት ወደ ሀገሬ ተመለስኩ',\n", - " 'tr_302_tr04002': 'ሁለቱ ን አገሮች የሚያ ገናኘው መንገድ ግንባታ የ ንግድ ና ኢንቨስተ መንት እንቅስቃሴ ዎችን ለ ማካሄድ ምቹ ሁኔታ እንደሚፈጥር አስ ታውቋል',\n", - " 'tr_303_tr04003': 'የ ሀገር መከላከያ ሚኒስቴር ባዘጋጀ ው የ ዚሁ የ ሽልማት ስነ ስርአት የ ሀገሪቱ ከፍተኛ ባለስልጣናት የ ሀይማኖት መሪዎች አምባሳደሮች ና ዲፕሎማቶች እንዲሁም የ ተሸላሚ ዎች ቤተሰቦች ተገኝ ተዋል',\n", - " 'tr_304_tr04004': 'ኢታ ማዦር ሹም ና ጠቅላይ ሚኒስትር መለስ ተወዛግ በ ው ነበር',\n", - " 'tr_305_tr04005': 'በ ወቅቱ ኤርትራ የ ማክሮ ኢኮኖሚ ን ኢትዮጵያ ደግሞ የ ማይክሮ ኢኮኖሚ ፖሊሲ ይከተሉ ነበር',\n", - " 'tr_306_tr04006': 'የ እነ ዶክተር ካሱ ኢላላ ውንጀላ ደግሞ ከ ኦቦ ሀሰን አሊ ይልቅ በ ጠቅለይ ሚንስቴሩ በኩል ተሰሚነት አግኝቶ እንደ ነበረ ብዙዎቹ የሚ ያስታውሱ ት ነበር',\n", - " 'tr_307_tr04007': 'ከ አጣሪ ኮሚሽኑ ውጤት በኋላ ተቋ ው ሞ ተጠናክሮ እንደሚ ቀጥል ተገለጸ',\n", - " 'tr_308_tr04008': 'ኢትዮጵያ ድን በ ሯን ለ ማስከበር ሁለት አማራጮች እንዳ ሏት ተገለጠ',\n", - " 'tr_309_tr04009': 'ትብትብ ቋጠሮ ገመና ሚስጢ ሩን በሚያስ ደንቅ ግርማ ተንታኝ ጉዳ ጉድ ን',\n", - " 'tr_310_tr04010': 'ጥሩ ገበያ ሊ ገኝ የሚ ችለው የ ት አገር ነው የሚለው ነው',\n", - " 'tr_311_tr04011': 'ኤርትራዊው ካፒቴ ን ሲ ሰልል ተያዘ',\n", - " 'tr_312_tr04012': 'አዲስ መዋቅር እና ቅርብ ማለት ማበጣበጥ ነው',\n", - " 'tr_313_tr04013': 'አንዳንድ የ ሶማሊያ አንጃዎች ኦነግ ንና የ ኦጋዴን ብሄራዊ ነጻ አውጭ ግንባር ወደ ሶማሊያ አምጥተ ዋል',\n", - " 'tr_314_tr04014': 'በ ደቡብ ህዝቦች ክልል ሶስት መቶ አስራ ሶስት ሺ አማራ ዎች ሁለት መቶ ስድስት ሺ ኦሮሞዎች አሉ',\n", - " 'tr_315_tr04015': 'በዚህ መሰረት ዛሬ ኬንያ ከ ሩዋንዳ ኢትዮጵያ ከ ኡጋንዳ ለ ግማሽ ፍጻሜ ይጋጠማሉ',\n", - " 'tr_316_tr04016': 'ለ ትሪፖሊ ው ስብሰባ መክሸፍ ኢትዮጵያ ኤርትራ ን ስት ከ ስ ኤርትራ ም ኢትዮጵያ ን በ እንቅፋት ነት አቅርባ ለች',\n", - " 'tr_317_tr04017': 'በ ቤይሩት የ ኢትዮጵያዊ ቷ አስክሬን የ ደረሰበት ጠፋ',\n", - " 'tr_318_tr04018': 'የ ህብረቱ ን መመስረት አስመልክቶ በ ደርባን ከተማ ርችት ተተኩ ሷል ሄሊኮፍተሮች ም ትእይንት አሳይ ተዋል ሙዚቀኞች ና ዳን ሰኞች ጣእመ ዜማ ቸውን አ ሰምተዋል',\n", - " 'tr_319_tr04019': 'ስለ ባድመ ና ሽራሮ ም ስክርነታቸውን ሰጡ',\n", - " 'tr_320_tr04020': 'ኢዴ ፕ የ ተቃዋሚዎች ን ህብረት ተቀላቀለ',\n", - " 'tr_321_tr04021': 'ኢትዮጵያ የምት ፈልገው ን ድል ለ ማጠናቀቅ ተቃር ባለች',\n", - " 'tr_322_tr04022': 'ኢትዮጵያ ከ ጐረቤቶቿ ጋር ያላ ት ግንኙነት ኮረኮንች የ በዛበት መንገድ ነው',\n", - " 'tr_323_tr04023': 'የ አይኖቹ ንና የ አ ፍንጮች ቀዳዳ ዎች ትንንሾች መሆናቸው ም ተመልክ ቷል',\n", - " 'tr_324_tr04024': 'አምስት የ ውጪ ሀገር የ በረራ አስተማሪ ዎች ደብረ ዘይት ገቡ',\n", - " 'tr_325_tr04025': 'የ ኦሮቶዶክስ ና ካ ቶ ሊ ኩ ሱባኤ ተቃውሞ አረፈ በት',\n", - " 'tr_326_tr04026': 'ጃክሮስ ኢትዮጵያ አስራ ሰባት ሚሊየን ብር እንዲ ከፍል ተወሰነ በት',\n", - " 'tr_327_tr04027': 'በ ኢትዮጵያ የ አሜሪካ ኤምባሲ ከ አል ኢቲ ሀድ አል እስላሚያ ማስጠንቀቂያ እንደ ደረሰው ትናንት ተገለጸ',\n", - " 'tr_328_tr04028': 'አቶ ደበላ ይማ ሙ ና ወይዘሮ መሬ ማ ዋቁማ ስድስት አመት በ ትዳር ቆይ ተዋል',\n", - " 'tr_329_tr04029': 'አዳዲስ የ ነዳጅ ቦቴዎች ወደ ሀገር ውስጥ መግባት ጀመሩ',\n", - " 'tr_330_tr04030': 'እነርሱ ም የ ኤቨርተን ክለብ ወዳጆች ነበሩ',\n", - " 'tr_331_tr04031': 'ከ አንድ ሜትር ከ ሰማኒያ አምስት ቁመት ና ሰባ ዘጠኝ ኪሎ ክብደት ጋር የ ጸጉሩ አሰራር ተደም ሮ የ ስንቶቹ ን እህቶቻችን ን ትኩረት ስቧል',\n", - " 'tr_332_tr04032': 'ባለፉት ሶስት አመታት የ ደሞዝ ክፍያው ን ጣሪያ በ እጥፍ አሳድገ ናል',\n", - " 'tr_333_tr04033': 'ሚላን በ ሰማኒያ ሚሊዮን ብር ንብረቱ አደረገ ው',\n", - " 'tr_334_tr04034': 'ሰዎች ማወቅ ያለ ባቸው ሁልጊዜ ም እንደ አርጀንቲና ው ጐል አይነት ማግባት እንደማል ችል ነው',\n", - " 'tr_335_tr04035': 'በ እርግጥ በ አዲስ አበባ በሚገኙ ክለቦች መስዋእትነት የ ኢትዮጵያ እግር ኳስ ማደግ ከ ቻለ በጣም ደስተኞች ነን',\n", - " 'tr_336_tr04036': 'ኒያላ ከተ ቆጠሩ በት ጐ ሎች ሶስተኛው በ በረኛው በ ጸጋዬ ዜና ስህተት የተገኘ ች ና ት',\n", - " 'tr_337_tr04037': 'እያንዳንዱ ተመልካች ይህ ስለ ተደረገ ለት ጠጥቶ ተደስቶ ነበር ከ ሜዳ የ ወጣው',\n", - " 'tr_338_tr04038': 'ከ ኢትዮጵያ ኦሎምፒክ ጽፈት ቤት ባገኘ ነው መረጃ አቶ ፍቅሩ ኪዳኔ ታህሳስ አስራ አምስት ቀን አዲስ አበባ እንደሚ ገቡ በ ላኩት መልእክት ለማወቅ ች ለናል',\n", - " 'tr_339_tr04039': 'ሙያው ን ለ ሙያተኞች መተው አለ ባችው ብለዋል',\n", - " 'tr_340_tr04040': 'ሌሎች ክለቦች ግን ገንዘብ የ ሌላቸው ላብ መተኪያ ን እንኳ ን ማቅረብ የማይችሉ ናቸው',\n", - " 'tr_341_tr04041': 'በ ሀገር ውስጥ ግን ፉክክር እንደ ሞቀ ነው',\n", - " 'tr_342_tr04042': 'ኳስ ጨዋታ ኳስ ነው',\n", - " 'tr_343_tr04043': 'ጦርነቱ ን ለ መቋጨት ኢትዮጵያ ለ አፍሪካውያን ውሳኔ ትገዛ ለች',\n", - " 'tr_344_tr04044': 'ኤርትራውያን ሸቀጣ ቸውን ይዘው ወደ ኢትዮጵያ ይ ግቡ የ ኢትዮጵያ ንም ሸቀጥ ገዝተው ይውጡ',\n", - " 'tr_345_tr04045': 'ወይዘሪት አዲስ አበባ ፈ ቲያ ሰኢድ የ ሁለተኛ ደረጃ ተማሪ ስት ሆን የ አውሮፕላን አስተናጋጅ ሆስተን ስ የ መሆን እቅድ እንዳላ ት ገልጻ ለች',\n", - " 'tr_346_tr04046': 'የ ኢትዮጵያ ዲሞክራ ሳዊ ፓርቲ ኢዴፓ በ ነገው እ ለት በ መስቀል አደባባይ የሚያ ከናውነው ን የ ተቃውሞ ስብሰባ ዝግጅት ሙሉ በ ሙሉ ማጠናቀቁ ን አስ ታውቋል',\n", - " 'tr_347_tr04047': 'ወዴት እንደሚ ሄዱ ለማ ን እንደሚ ናገሩ ግራ የ ገባቸው ይመስ ላሉ',\n", - " 'tr_348_tr04048': 'አሁን ግን የ ኢትዮጵያ የድሮ ጠላት የ ሆነችው ና ራሷ በ ድርቅ የተመታች ው ኤርትራ ወደቦቹ ን ለ ኢትዮጵያ የሚ ላኩ እህሎች በ ነጻ እንዲ ገቡበት ፈቅዳ ለች',\n", - " 'tr_349_tr04049': 'የ አውሮፓ ህብረት ለ ኢትዮጵያ የሚያደርገው ን እርዳታ ያ ጢን',\n", - " 'tr_350_tr04050': 'እንደ ኦሮሞ ዎቹ እምነት ም አምላክ በ ሚሊዮኖች የሚ ቆጠር ውስብስብ ፍጡራን ን የ ፈጠረው በ ሀያ ሰባት ቀናት ነው',\n", - " 'tr_351_tr04051': 'እንደ ቤተ መንግስት አስተዳዳሪ ከ ሆኑ ጥናቱ እንደ ተጠናቀቀ የ እድሳት ግንባታው ወዲያ ው ይጀ መራል',\n", - " 'tr_352_tr04052': 'ነዳጅ ም በውጭ ምንዛሪ እንዲ ገዛ ተገደደ',\n", - " 'tr_353_tr04053': 'ወይም በ ቅርቡ እንደ ታዘብነው በ ጦሩ ሜዳ ገብ ተዋል የሚ ባሉት እንኳ ን ከ ታሪክ ሽሚያ ውስጥ ይገባ ሉ',\n", - " 'tr_354_tr04054': 'እዚህ አካባቢ ያለው ወገናችን ብዙ እውነት ይናገራል',\n", - " 'tr_355_tr04055': 'ጥናቱ ን የማ ደንቅ በት አንዱ ምክንያት ይኸው ነው',\n", - " 'tr_356_tr04056': 'ለ ዛሬ ማለት የሚ ቻለው ጥያቄ ውም እየገፋ ያለው ግንኙነቱ ስርአት ይያዝ የሚ ል ነው',\n", - " 'tr_357_tr04057': 'መድረኩ ን ያዘጋጀው ድርጅት ግን ሀሳቡ ን እንዳል ተቀበለው እንዲያ ን ኦ ሽን ነው ስ ሌተር በ ቅርብ ገልጿ ል',\n", - " 'tr_358_tr04058': 'ከ ሎስ አንጀ ልስ ከ ለንደን ከ ካናዳ ወዘተ የ መጡት አያሌ ናቸው',\n", - " 'tr_359_tr04059': 'ተመራቂ ዎች ተማሪዎች ወደፊት በ ከፍተኛ ትምህርት የ መሳተፍ እድ ላቸው አሁን ካ ላቸው እውቀት አንጻር ሲታይ ወደፊት አስቸጋሪ እንደሚሆን ባቸው የማን ጠራ ጠረው እውነት ነው',\n", - " 'tr_360_tr04060': 'እርስዎ ያሉት ን በ ትክክል ለ መጥቀስ ትግሬ ዎች አክሱም አ ላቸው',\n", - " 'tr_361_tr04061': 'መንግስት በ ኢንቨስትመንት እንቅስቃሴ ላይ የ ተከሰቱት የ ፖሊስ ና የ አሰራር ግድፈቶች ን ለ ማስወገድ እርምጃ መውሰድ ከ ግሉ እንቨስትመንት ፍ ስት በ ሚገኘው ን ድርሻ እንደሚያ ስ ሻሽል ገለጹ',\n", - " 'tr_362_tr04062': 'እኔ ግን ና ፍጠ ኛ ም መድፈኛ ም እንዳል ሆ ኩኝ ልንገራችሁ ብዬ እንጂ ፖለቲከኛ ሳል ሆን አሽሙረኛ ነኝ ብዬ እናንተ ን ላ ሰማችሁ አል ሞክር ም',\n", - " 'tr_363_tr04063': 'ኮሎኔል በዛብህ ጴጥሮስ የ አማራጭ ሀይሎች ሊቀመንበር የ ዶክተር በየነ ጴጥሮስ ወንድም መሆናቸው ተያይዞ ተ ገልጿ ል',\n", - " 'tr_364_tr04064': 'የ መስተዳድሩ መግለጫ ከተማው ስር ነቀል ለውጥ እንደሚ ያስፈልጋት ገልጾ ህዝቡ በዚህ እንዲ ሳተፍ ቢ ጠይቅ ም ጊዜያዊ መስተዳድሩ የ መዋቅር ለውጡ ን ያስፈጽማል ተብሎ አይጠበቅ ም',\n", - " 'tr_365_tr04065': 'ለወደፊቱ በሚ ዘጋጀው ጉባኤ የ በ ኩሌን ሀሳብ ለ ካድሬው ይዤ አቀርባ ለሁ',\n", - " 'tr_366_tr04066': 'ኤኤፍፒ ከ ሶስት ሺ በላይ የኤርትራ ኩናማ ዎች ወደ ኢትዮጵያ ሸሽተው በ መግባት የኤርትራ ሰራዊት በ ሀይል እየ መለመላቸው ነው ሲሉ ውንጀላ ሰንዝ ረዋል',\n", - " 'tr_367_tr04067': 'ዋናው አላማችን አባላ ቶቻችን በ ስፖርቱ ተሳታፊ እንዲሆኑ ና ለ ሀገራችን ስፖርት የ በኩላቸው ን አስታው ጽኦ እንዲ ያበረክቱ እንጂ እንደ እያንዳንዱ ክለቦች ድርጅቱ ን ለ ማስተዋወቅ አይደለም',\n", - " 'tr_368_tr04068': 'በ ማጠቃለያ ውም በ እርዳታ አ ሰባሰቡ ወቅት ኢህአዲግ በ በጐ አይ ን የማ ይመለከታቸው ን በ አሸባሪነት ጠርጥሬ ያ ቸዋለሁ የሚ ላቸው ኢትዮጵያውያ ን የ ህግ ታራሚዎች ሳይ ቀሩ በ እርዳታው ተሳትፎ ማድረጋቸው ን አመልክ ቷል',\n", - " 'tr_369_tr04069': 'በ ብዙ የ ማህበር ኢኮኖሚያዊ መስኮች አበር ታች ውጤቶች ን ማምጣት ጀም ሯል',\n", - " 'tr_370_tr04070': 'ዳዊት ዮናስ በ ፓር ስ ከሚገኙ ኢትዮጵያውያ ን ጋር ተነጋገሩ',\n", - " 'tr_371_tr04071': 'ያን ጊዜ ሚንሊክ ይህንን አዋጅ አስ ነገሩ',\n", - " 'tr_372_tr04072': 'አሁን ባለፈው ሳምንት ይሄው አርቲስት በ ፓሪስ ጐዳናዎች ላይ ከ ሶስት ኢትዮጵያውያ ን ጋር እየ ተጓዙ ሳ ለ ነው አደጋ የ ደረሰባቸው',\n", - " 'tr_373_tr04073': 'ሆዳቸው ን የሚ ያመልኩ መሆናቸው ን በ ተደጋጋሚ ስለ አ ረጋገጥኩ ነው',\n", - " 'tr_374_tr04074': 'ብዙ ጠመዝማዛ አቀ በት ና ቁልቁለት ያለው ጉዞ ነው',\n", - " 'tr_375_tr04075': 'ጉባኤ ዴሞክራሲያዊ ሊሆን የሚ ችለው ዴሞክራሲያዊ ያን ፍትሀዊ በሆነ መንገድ ሲ ዘጋጁ ብቻ ነው',\n", - " 'tr_376_tr04076': 'ከ ኢደፓ የተገኘው መረጃ እንደሚ ያስረዳ ው እስረኞች የ ት እንደ ተወሰዱ አይ ታወቅ ም',\n", - " 'tr_377_tr04077': 'እነ ተወልደ አዲስ ፓርት ያቋቁማሉ ተ ባለ',\n", - " 'tr_378_tr04078': 'ግን የ ኢትዮጵያ ህልውና ተ ደፍሮ አልቀረ ም',\n", - " 'tr_379_tr04079': 'የኦሮሞ ተማሪዎች ተቋማ ቸውን ከ ማቅረባቸው ባሻገር የኦሮሞ ፕሬዚዳንት የሆኑት ን አቶ ጁነዲ ን ሶዶ ን አነጋግሯ ቸዋል',\n", - " 'tr_380_tr04080': 'ይሁን ና መታሰር ና መጠየቅ ያለ ባቸው ከ ታገዱት ማእከላዊ ኮሚቴ አባላት ጋር ዝምድና ና ቅርበት ያ ላቸው ብቻ መሆን እንደሌለ ባቸውም ታዛቢዎች ያስገነዝ ባሉ',\n", - " 'tr_381_tr04081': 'ኢትዮጵያውያ ን ለ አንድ ቀን አዳር ይ ጨነቃ ሉ',\n", - " 'tr_382_tr04082': 'በ ኢትዮጵያ አስሀባ ዎች አ ሰሯቸው የሚ ባሉ ብዙ መስጊዶች እንደ ነበሩ አንዳንዶች ም አሁን ም እንዳሉ ይታወ ቃሉ',\n", - " 'tr_383_tr04083': 'እኛ አፍሪካውያን በ ኢትዮጵያውያ ን ኮራ ን',\n", - " 'tr_384_tr04084': 'በት ሪቡኑ ስር በ ሚገኘው ቦታ ላይ ም ጓደኞቹ የ ቡድን ተጫዋቾች ሰውነታቸው ን እያ ሟሟ ቁ ነበር',\n", - " 'tr_385_tr04085': 'ሳምንት በ ኦልድ ትራ ፎርድ ሊድስ ን አስተናግ ዶ ሶስት ለ ሁለት አሸን ፏል',\n", - " 'tr_386_tr04086': 'የ ሪያል ማ ዲ ርድ ኮንትራ ቴ የሚያበቃ ው በ ሁለት ሺ ነው',\n", - " 'tr_387_tr04087': 'በ እርግጥ የ ኢትዮጵያ ፉትቦል ፌዴሬሽን ሀላፊዎች ይህንን በ ማድረጋቸው ሊ ደነቁ ይገባል',\n", - " 'tr_388_tr04088': 'በተለይ በ ዋ ና ከተማዋ ለንደን ቢሆን ደስተኛ ነን',\n", - " 'tr_389_tr04089': 'ወደ ሀያ ስድስት ሺህ የሚሆኑ ኢትዮጵያውያ ን አይሁዶች እስካሁን ኢትዮጵያ መቅረታቸው ይገመ ታል',\n", - " 'tr_390_tr04090': 'ክሱ ም ን እንደሆነ ም አያውቁ',\n", - " 'tr_391_tr04091': 'ሁለቱ ም ቡድኖች ከ ሌሎች የ ኡጋንዳ የ ሩዋንዳ የ ሱዳን ቡድኖች ጋር በ ኮሌጅ ኦፍ ኮሚኬሽን ቴክኖሎጂ ውስጥ እንደሚ ኖሩ ይ ታውቋል',\n", - " 'tr_392_tr04092': 'ቁልፍ ችግሮች እነማን ናቸው ተብለው መታየት ነበረ ባቸው',\n", - " 'tr_393_tr04093': 'ተቃዋሚዎች ን ግን በ አድራጐታቸው ሊ ሳለቁ ባቸው ይሞ ክራሉ',\n", - " 'tr_394_tr04094': 'የ አህያ ዘመዶች ማን እንደሆኑ ተናግራ ለች',\n", - " 'tr_395_tr04095': 'የ ት እንሂድ የ ደንበኞቻችን ን ጉዳይ እንዴት እናስ ረዳ ወደ ፍርድ ቤት ሲ ገቡ እንዴት እን ይ ይላሉ ጠበቆች',\n", - " 'tr_396_tr04096': 'ኤርትራ የ ኢትዮጵያ አካል ና ት',\n", - " 'tr_397_tr04097': 'ትግራዮች ወደ ብሄራዊ ትግሉ ይ ግቡ',\n", - " 'tr_398_tr04098': 'አቶ ታምራት በ እለቱ የመንግስት ሚዲያ ዎችን አፈ ንጉሶች በ ማለት ጥሩ ስ ም ሰጥ ቷቸዋል',\n", - " 'tr_399_tr04099': 'ሀገራችን ን የ ገጠማት ግን የዚህ ተቃራኒ ነው',\n", - " 'tr_400_tr04100': 'እ ስኮትላንዶች ስን መራቸው ቆይ ተ ን አቻ የ ም ታደርጋ ቸውን ጐል አግብ ተዋል',\n", - " 'tr_401_tr05001': 'የ ሂሳብ ና የ ቴክኒክ ችሎታ ም ነበረኝ ሊ ያስቸግር የሚ ችለው ሎጅ ክ ና ማቀናጀት ነው',\n", - " 'tr_402_tr05002': 'ኢትዮጵያ ና ሌሎች አስራ ስ ባት የ አፍሪካ አገሮች ም የ ሀሳቡ ን ተፈጻሚ ነት ይከታተ ላሉ',\n", - " 'tr_403_tr05003': 'ከ ቡና ሽያጭ ሀምሳ ስምንት ሚሊዮን ዶላር ተገኘ',\n", - " 'tr_404_tr05004': 'ይልቁኑ ሳሞራ ግንባር የ ቀሩት ለ ማስትሬት ዲግሪ እየ ተማሩት ያለው የ ተልእኮ ትምህርት የ መጨረሻው ፈተና ደርሶ ባቸው ነው',\n", - " 'tr_405_tr05005': 'ሶስት የ ደብሩ ሀላፊዎች ከስራ ተባ ረዋል',\n", - " 'tr_406_tr05006': 'ይህ በ እንዲ ህ እንዳለ መሳሪያ የ ደገኑ ወታደሮች ወደ ትምህርት ቤት ውስጥ በ መግባት ተማሪዎች ደብተራቸው በ ክፍል ውስጥ ተቆልፎ በት በ ግዳጅ እንዲ ወጡ ተደርጓል',\n", - " 'tr_407_tr05007': 'ጃክሮስ ኢትዮጵያ ከ ደንበኞቹ የ ሰበሰበው ን ገንዘብ ለ መመለስ አቅም የ ለውም ተ ባለ',\n", - " 'tr_408_tr05008': 'ፓትሪያርኩ በ በኩላቸው ከ እናንተ መካከል ሀጢያት የ ሌለበት ይውገረኝ በሚል አቋማቸው እንደ ጸኑ እንደሆነ እየተነገረ ነው',\n", - " 'tr_409_tr05009': 'ምትክ አልባ ህትመት ው ዲ ቷ ስጦታ ሁሉን ያዥ ኮሮጆ ው ብ ነሽ ፊያሜታ',\n", - " 'tr_410_tr05010': 'ዴንማርክ በ ኢትዮጵያ ቆን ስል ሲ ኖራት በ ኤርትራ ግን ያላ ት ኤምባሲ ነው',\n", - " 'tr_411_tr05011': 'በ ኢትዮ ኤርትራ ድንበር ኮንትሮባንድ ተስፋፍ ቷል',\n", - " 'tr_412_tr05012': 'ከዚህ ስብስባ ውጭ ያሉት ሰዎች እስከዚያ ው ከ መጡ ጥሩ',\n", - " 'tr_413_tr05013': 'ሁሴን ቦድ ኤርትራ ለ ራሷ ስትራቴጂካዊ ምክንያቶች ስትል የ አማጽያኑ ን ስምሪት በ ሶማሌ እንደምታ ስተ ባብር ም አስረድ ተዋል',\n", - " 'tr_414_tr05014': 'ብ እ ዴን ማለት ኢህአዲግ ነው',\n", - " 'tr_415_tr05015': 'የ ኢትዮጵያ የ ኢኮኖሚ ችግር የ ውስጥ እንጂ የ ግሎባላይዜሽን አይደለም',\n", - " 'tr_416_tr05016': 'ተቃዋሚዎች ና ገዥው ፓርቲ ሲ ከራከሩ ዋሉ',\n", - " 'tr_417_tr05017': 'ፓርላማው የ ኢንቨስትመንት ረቂቅ አዋጅ ን አጣ ጣለው',\n", - " 'tr_418_tr05018': 'ኢትዮጵያዊ ቷን ገድ ሏል የ ተባለው ቻይና ዊ በ ቁጥጥር ስር ነው',\n", - " 'tr_419_tr05019': 'የ ኢሳያስ መንግስት የ ሁሴን አይዲድ ን ተዋጊዎች ን ሊ ያሰለጥን ነው',\n", - " 'tr_420_tr05020': 'አሁን በ መጨረሻ ም የ ኢትዮጵያዊ ና ዲሞክራሲያዊ ፓርቲ በ ህብረቱ እንቅስቃሴ እንደ ገባ ተ ገልጿ ል',\n", - " 'tr_421_tr05021': 'ፍልሚያው የ ሚካሄደው በ ተለያዩ ግንባሮች ነው',\n", - " 'tr_422_tr05022': 'ኢትዮጵያ ወታደሮ ቿን ከ ግዛቴ አላስ ወጣች ም ስትል ኤርትራ ክስ አቀረበች',\n", - " 'tr_423_tr05023': 'ስለ ተገደሉት ሰዎች ግን የ ገለጹት ነገር የ ለ ም',\n", - " 'tr_424_tr05024': 'የኦሮሞ ነጻነት ግንባር አደጋው ን ያደረስ ኩት ባቡሩ ወታደሮች ን ጭኖ ወደ ምስራቃዊ ው የ አገሪቱ ክፍል ሲያ መራ ነው ይላል',\n", - " 'tr_425_tr05025': 'ጾመ ፍልሰታ ን አስመልክቶ የ ኢትዮጵያ ኦርቶዶክስ ተዋህዶ ቤተ ክርስቲያን ና የ ካቶሊክ ቤተ ክርስቲያን በ ጋራ ያደረጉት ሱባኤ በ ኦርቶዶክስ መንፈሳዊ አማኞች ዘንድ የ በረታ ተቃውሞ አርፎ በታል',\n", - " 'tr_426_tr05026': 'የ ነጻ ሚዲያ ዎች አዋጅ በ ምክር ቤት ጸድቆ ተግባራዊ ሊሆን ነው',\n", - " 'tr_427_tr05027': 'ኢምባሲ ው ጨምሮ ም ለ ኢትዮጵያ መንግስት የ ጸጥታ ክፍል ማስታወቁ ን ተያይዞ ገልጿ ል',\n", - " 'tr_428_tr05028': 'አብረው ገበያ ወጥተ ው ለ ጓዳቸው የሚሆን ቁሳቁስ ሊሸ ም ቱ ተስማሙ',\n", - " 'tr_429_tr05029': 'ቆሎ ሸጠው ኑሯቸው ን በሚ ደጉ ሙ ና ጫማ ጠርገው ደብተር ና እርሳስ በሚ ገዙ ለ ፍቶ አዳሪ ዎች መካከል እራሱ ን አ ነገሰ',\n", - " 'tr_430_tr05030': 'እኔ ግን ራሴ ን በሚገባ አውቀ ዋለሁ',\n", - " 'tr_431_tr05031': 'ሀያ ስምንት አመቱ ነው',\n", - " 'tr_432_tr05032': 'ኢንቨስትመንቱ ም እ ኮ አነስተኛ ነው ይላሉ',\n", - " 'tr_433_tr05033': 'ቺሊ ዎች እ ኮ ፔናሊቲ ው ትክክለኛ አይደለም በሚል ተቃውመ ዋል',\n", - " 'tr_434_tr05034': 'በሰባ ሶስተኛው ደቂቃ ላይ ነው ተ ቀይሮ የ ገባው',\n", - " 'tr_435_tr05035': 'የ አዲስ አበባ መስተዳድር ፕሬዚዳንት አቶ አሊ አብዶ የ ስፖርት ምክር ቤቱ ፕሬዚዳንት ናቸው',\n", - " 'tr_436_tr05036': 'ባጠቃላይ የ ውድድሮች ጫና መብዛት ስሜታቸው ን ቀንሶ ባቸዋል',\n", - " 'tr_437_tr05037': 'ከሚ ያስገኙ ት ገቢ ኮሚሽን ያገኛ ሉ',\n", - " 'tr_438_tr05038': 'የ ውድድሩ ታዛቢ ኮሚሽነሮ ችም ምደባ ተጠና ቋል',\n", - " 'tr_439_tr05039': 'ጀግናው ሻለቃ ሀይሌ ገብረስላሴ ከ አዳዲስ ኩባንያ ጋር ያለውን ግንኙነት በ ማጠናከር በ ሀገራችን የ አዳዲስ ኩባንያ ምርቶች የሚመረቱ በትን ሁኔታዎች እ ያመቻቸ ይገኛል',\n", - " 'tr_440_tr05040': 'ሆድ ሲ ያውቅ ዶሮ ማታ ይ ባል የ ለ',\n", - " 'tr_441_tr05041': 'ሊጋው ን በ ቁንጮ ነት የሚ መራው የ ማዮርካ ቡድን ነው',\n", - " 'tr_442_tr05042': 'ይህም ተጋጣሚው ብዙ ጨዋታዎች ን ያደረገ ና ከፍተኛ ልምድ ና ዝና ያለው ተወዳዳሪ ሮጀር ቶማስ የተባለ ተወዳዳሪ ነው',\n", - " 'tr_443_tr05043': 'አምነስቲ በ እስረኞቹ ዙሪያ ስለሚ ያገኙ ት ህክምና ና ስለሚ ገጥማቸው ቶር ቸር የተሰማ ውን ስጋት ገልጿ ል',\n", - " 'tr_444_tr05044': 'ሻእቢያ በ ተቆጣ ጠራት ኢትዮጵያ ውስጥ ትንሽ ስልጣን መያዝ ብቻ ነው ፍላጐታቸው',\n", - " 'tr_445_tr05045': 'ነገር ግን ሌላ አስተዳዳሪ ተሹሞ ቢመጣ ም በ አቡነ ጳውሎስ የ ተሾመ አስተዳዳሪ ን እንደማይቀበሉ የቤተ ክርስቲያ ኗ ተወካዮች ገልጿ ል',\n", - " 'tr_446_tr05046': 'ጅቡቲ ኤርትራውያን ን እ ያባረረ ች ነው',\n", - " 'tr_447_tr05047': 'የ ተማሪዎች ዲን ሁኔታው ን ለ ትምህርት ቤቱ ያሳውቃ ል',\n", - " 'tr_448_tr05048': 'ከ ሁለቱ ወደቦች ወደ ኢትዮጵያ የሚ ገቡት መንገዶች ጥሩ ይዞታ ያ ላቸው ናቸው',\n", - " 'tr_449_tr05049': 'ኢትዮጵያውያ ን በ ኒውዮርክ የ ተቃውሞ ሰልፍ ያደርጋሉ',\n", - " 'tr_450_tr05050': 'ለ ነዚህ ድርጊቶች ም ኦሮሞዎች ለ እያንዳንዳቸው ስ ም ስ ም አ ሏቸው',\n", - " 'tr_451_tr05051': 'ነገር ግን በውጭ የሚገኙ ኤምባሲዎች ባደረጉ ት ጥረት ፍላጐት ያ ላቸው ሶስት የውጭ ድርጅቶች ተገኝ ተዋል',\n", - " 'tr_452_tr05052': 'ሰሙ ደግሞ አገራዊ ገጽታ ው ነው',\n", - " 'tr_453_tr05053': 'ስደተኛ ተብሎ የ ተመዘገበው ና ያል ተመዘገበው ቁጥር በ እኔ ይሁን ባችሁ ከ ሶስት ሚሊዮን አ ያንስ ም',\n", - " 'tr_454_tr05054': 'እኛ ም ስህተቱ ን ስህተት ለማ ለት እንኳ እንፈራ ለ ን',\n", - " 'tr_455_tr05055': 'እኔ እስከ ማውቀው እንዲ ህ ነበር',\n", - " 'tr_456_tr05056': 'የ ቴክኖሎጂ ልቀት አለ የ ሚባለው ም አንዱ ይኸው ነው',\n", - " 'tr_457_tr05057': 'ሌላው የ ሱዳን ን ጉዳይ ለ ኤርትራ አስቸጋሪ እንዲሆን ያደረገው የ ኢትዮጵያ አቋም መለሳለስ ነው',\n", - " 'tr_458_tr05058': 'ይህ ባለፈው እሁድ በ ቨርጂኒያ ፓቶ ማክ ሚልስ በ ሂይልተን ቤተ ክርስቲያን የተ ከናወነው ዋናው ጸሎተ ፍትሀ ት ና ኦፊሴላዊ የ ፕሮፌሰር አስራት አስከሬ ን አሸኛኘት ፕሮግራም ነው',\n", - " 'tr_459_tr05059': 'በተለይ ብሄራዊ እርቅ ና ተቃዋሚዎች ን የ ፕሬስ ጉዳይ ን የሚ መለከቱት ወሳኝ የ አገራችን ጉዳዮች ናቸው',\n", - " 'tr_460_tr05060': 'በ ደቡብ ሶማሊያ እጅግ ከተ ከ በሩት ሁለት ጐሳዎች አንዱ የ ሆነው ባህጊሪ የ ተወለደው ከ ኦሮሞ እናት ነው',\n", - " 'tr_461_tr05061': 'መንግስት በ ኢንቨስትመንት እንቅስቃሴ ላይ የ ተከሰቱ የ ፖሊሲ ና የ አሰራር ግድፈቶች ን ለ ማስወገድ እርምጃ መውሰዱ ከ ግሉ ኢንቨስትመንት ፍሰት የ ሚገኘው ን ድርሻ እንደሚያ ሻሽለው ም ገለጹ',\n", - " 'tr_462_tr05062': 'እኔ ግን ነፍጠኛ ም መድፈኛ ም እንዳል ሆ ኩኝ ልንገራችሁ ብዬ እንጂ ፖለቲከኛ ሳል ሆን አሽሙረኛ ነኝ ብዬ እናንተ ን ላሳምናችሁ አል ሞክር ም',\n", - " 'tr_463_tr05063': 'ኮለኔል በዛብህ ጴጥሮስ የ አማራጭ ሀይሎች ሊቀመንበር የ ዶክተር በየነ ጴጥሮስ ወንድም መሆናቸው ተያይዞ ተ ገልጿ ል',\n", - " 'tr_464_tr05064': 'የ መስተዳድሩ መግለጫ ከተማዋ ስር ነቀል ለውጥ እንደሚ ያስፈልጋት ገልጾ ህዝቡ በዚህ እንዲ ሳተፍ ቢ ጠይቅ ም ጊዜያዊ መስተዳድሩ የ መዋቅር ለውጡ ን ያስፈጽማል ተብሎ አይጠበቅ ም',\n", - " 'tr_465_tr05065': 'ለወደፊቱ በሚ ዘጋጀው ጉባኤ የ በ ኩሌን ሀሳብ ለ ካድሬው ይዤ አቀርባ ለሁ',\n", - " 'tr_466_tr05066': 'ኤኤፍፒ ከ ሶስት ሺ በላይ የኤርትራ ኩናማ ዎች ወደ ኢትዮጵያ ሸሽተው በ መግባት የኤርትራ ሰራዊት በ ሀይል እየ መለመላቸው ነው ሲሉ ውንጀላ ሰንዝ ረዋል',\n", - " 'tr_467_tr05067': 'ዋናው አላማችን አባላ ቶቻችን ን በ ስፖርቱ ተሳታፊ እንዲሆኑ ና ለ ሀገራችን ስፖርት የ በኩላቸው ን አስተዋጽኦ እንዲ ያበረክቱ እንጂ እንደ አንዳንድ ክለቦች ድርጅት ን ለ ማስተዋወቅ አይደለም',\n", - " 'tr_468_tr05068': 'በ ማጠቃለያ ውም በ እርዳታ አ ሰባሰቡ ወቅት ኢህአዲግ በ በጐ አይ ን የማ ይመለከታቸው ና በ አሸባሪነት ጠርጥሬ ያ ቸዋለሁ የሚ ላቸው ኢትዮጵያውያ ን ን የ ህግ ታራሚዎች ሳይ ቀሩ በ እርዳታው ተሳትፎ ማድረጋቸው ን አስመል ክቷል',\n", - " 'tr_469_tr05069': 'በ አዲስ አበባ ስቴዲዮም መብራት ሀይል ባንኮች ን ሁለት ለ ዜሮ ኒያላ ትራንስ ኢትዮጵያ ን አራት ለ ሶስት አሸንፈ ዋል',\n", - " 'tr_470_tr05070': 'የ አውሮፓ ፓር ሊያ ሜንት በ ኢትዮጵያ ዲሞክራሲያዊ ሂደት ላይ ያለውን ጥርጣሬ ገለጸ',\n", - " 'tr_471_tr05071': 'አሁን ግን እ ዚሁ እ ከተማችን ጠንቋይ ተገኘ',\n", - " 'tr_472_tr05072': 'እንደ ተመስገን ገለጻ ከሆነ በጣም አስገራሚ ው ነገር የ ፖሊሶቹ ነው',\n", - " 'tr_473_tr05073': 'ክተት ሰራዊት ም ታ ነጋሪት በተ ባለ ማግስት አርበኛ ው ተመመ',\n", - " 'tr_474_tr05074': 'በ ሂደት ደሞ እነዚህ ኑ ጥልቅ እያደረገ ና እያሰፋ ተጉ ዟል',\n", - " 'tr_475_tr05075': 'ጉባኤ ያንድ ወገን አመለካከት ብቻ እንዲያ ንጸባርቅ ተደርጐ መዘጋጀት ይችላል',\n", - " 'tr_476_tr05076': 'ደጋፊ ዎቻችን ን ለ ማሳጣት የተደረገ መሆኑን እናውቃለን',\n", - " 'tr_477_tr05077': 'የ ህወሀት ማእከላዊ ኮሚቴ መደበኛ ስብሰባ ትናንትና ተጀመረ',\n", - " 'tr_478_tr05078': 'እንዲያ ደናቅፈ ንም እንደማ ን ፈቅድ ሊያ ደናቅፈ ን ቢ ሞክር ደግሞ ል ና ሸንፍ የምን ችልበት ደረጃ ላይ እየ ደረስ ን ስለሆነ የ ልማቱ ን እንቅስቃሴ እገሌ ያደ ፈረስ ብናል ያስቆ መናል የሚ ል ስጋት የ ለ ንም',\n", - " 'tr_479_tr05079': 'ተማሪዎቹ ባካሄ ዱት ህገ ወጥ እንቅስቃሴ በ ተሽከርካሪዎች ና በ ትምህርት ቤቶች ላይ ጥፋት ደርሷ ል',\n", - " 'tr_480_tr05080': 'በ ኢትዮጵያ የሚገኙ ኤርትራውያን ም ሻእቢያ እ ደርስ ላችኋለሁ በ ማለት ተንፍሶ የነበረው ን እብሪታቸውን እንደ ገና እ ያፋፋመ መሆኑን ም መረዳት ተችሏል',\n", - " 'tr_481_tr05081': 'የ ኢትዮጵያ ሬዲዮ ታሽጓል ብሎ ወሬ ማ ና ፈሱ ፍጹም እንዳሳ ዘናቸው ለ ሪፖርተራችን አስታውቀ ዋል',\n", - " 'tr_482_tr05082': 'ግን ታሪካቸው ተረ ስ ቷል አስታዋ ሽ አጥ ተዋል',\n", - " 'tr_483_tr05083': 'በ ሲዲኒ ኦሎምፒክ አስር ሺ ስምንት መቶ ተወዳዳሪ ዎች እና ሀያ አንድ ሺ ጋዜጠኞች ተገኝ ተዋል',\n", - " 'tr_484_tr05084': 'እና ተስማምተን ነው ል ና ሰልፈው የ ቻልነው ብለዋል',\n", - " 'tr_485_tr05085': 'ቪላ ፓርክ ዛሬ ት ደም ቃለች',\n", - " 'tr_486_tr05086': 'ይህ ትልቁ ምኞቴ ነው',\n", - " 'tr_487_tr05087': 'ምክንያቱ ም እውቀት ያለው ባለሙያ መጥቶ ለ አሰልጣኞቻችን ና ለ ተጫዋቾቻችን ከሚ ያውቀው ቆን ጥሮ ካስተማረ ስህተት ን እንድና ርም ያደርገ ናል',\n", - " 'tr_488_tr05088': 'ግን ስ ሄድ እንደ ትልቅ ቁም ነገር ተይዞ አይደለም',\n", - " 'tr_489_tr05089': 'የ ኢትዮጵያ ና የ አልጀርስ ልኡካን አልጀርስ ገቡ',\n", - " 'tr_490_tr05090': 'ክስ ገና እየ ተፈለገ ነው ያለው',\n", - " 'tr_491_tr05091': 'አርባ ስምንት የመንግስት ኩባንያዎች ኪሳራ ውስጥ ገብ ተዋል',\n", - " 'tr_492_tr05092': 'ችግሩ ን ተንበርካኪ ነትና ውጫዊ ነው ነው የሚሉት',\n", - " 'tr_493_tr05093': 'ጥገኛ ካፒታሊ ስቶች ፓለቲካ ዊ ኢኮኖሚያዊ ና ወታደራዊ ሀይ ላቸው ተዳክ ሟል ጸረ ህዝብ ቢሮክራሲ ያቸው ተደምስ ሷል',\n", - " 'tr_494_tr05094': 'ፕሬዚዳንቱ ለ ኢትዮጵያ አንድነት ለ ዋሉት ውለታ የ ኢትዮጵያ ህዝብ የ እጃቸው ን ይ ስጣቸው ብሎ ከ መመረቅ ሌላ ም ን ማለት ይችላል',\n", - " 'tr_495_tr05095': 'ለ ነገሩ ማ ለሰው መብት ለ መሟገት አይደል እዚያ ያሉት የ ራሳቸው መብት ሲ ዳጥ እንዴት ያስችላቸው ጠበቆች አጃቢ ፖሊሶች ባለ ጉዳዮች እስረኞች ችሎቱ ን ይሞ ሉታል',\n", - " 'tr_496_tr05096': 'ይሁን ና ኢትዮጵያ ፊቷ ን ወደ ልማት ስታ ዞር እስከ አፍንጫ ዬ ያስታጠቀች ኝ ኢትዮጵያ በ ኢኮኖሚው ም ት ደግፈ ኛለች የሚለው ተስፋ ብሩህ ነበር',\n", - " 'tr_497_tr05097': 'ተቃዋሚ ሀይሎች እንደሚ ሉት የ ፕሬዚዳንት ኢሳይያስ መንግስት ወደ አንድ ፓርቲ አገዛዝ በ መንሸራተት አምባገነን ነትን የ ኢኮኖሚ ውድቀት ንና ማሀበራዊ ቀውስ ን እ ያመቻቸ ነው',\n", - " 'tr_498_tr05098': 'ይህን ያል ኩት ያለ ምክንያት አይደለም',\n", - " 'tr_499_tr05099': 'ይህ ማስፈራሪያ በ ሁለት ምክንያቶች መሰረተ ቢስ ነው',\n", - " 'tr_500_tr05100': 'አንድ ለ አንድ ሆነ ን',\n", - " 'tr_501_tr06001': 'ከ ሁሉም የሚያስ ደን ቀኝ የተለያዩ ሙያ ዎች እንደ ሀገሩ ባህል ኢኮኖሚ ና እድገት ይለያ ያል',\n", - " 'tr_502_tr06002': 'ኤርትራ ና ኢትዮጵያ ለ ድንበር ኮሚሽኑ የ ይገባኛል ጥያቄዎቻቸው ንና ማስረጃ ዎቻቸውን የ ያዙ ማመልከቻ ዎች ማቅረባቸው ን የውጭ ጉዳይ ሚኒስትር አስረድ ቷል',\n", - " 'tr_503_tr06003': 'እርዳታ ያላገኙ ወረዳ ዎች መኖር ቸውንም ጠቁ መዋል',\n", - " 'tr_504_tr06004': 'ለ ሉአላዊነት ሲ ባል ነገ ደግሞ ለ መልሶ ማቋቋም እንደ ገና መዋጮ ቶንቦላ ልን ጠየቅ እንደምን ችል ማን ያው ቃል',\n", - " 'tr_505_tr06005': 'ዳግም ፈርኦን በ ኦርቶዶክስ ቤተ ክርስቲያን ተወለደ',\n", - " 'tr_506_tr06006': 'በ ተለያዩ አጋጣሚ ዎች በ እጃቸው የገባ ውን ገንዘብ በ ሳኡዲ ባንክ ማስቀመጣቸው ን በ እርግጠኝ ነት የሚናገሩ ት እነዚሁ ምንጮች አያይዘው እንደ ገለጹት ከ ትግል በኋላ ጥያቄ ው ተነስቶ ነበር',\n", - " 'tr_507_tr06007': 'በሌላ በኩል ግን የ ደረሱት ን ምንጮች እንደሚ ያመለክቱት ከሆነ ጃክሮስ ኢትዮጵያ የ ደንበኞቹ ን ገንዘብ የ መክፈል አቅም እንደሌለ ው ተ ገልጿ ል',\n", - " 'tr_508_tr06008': 'ማህበሩ ን ያቋቋሙ ት በስራ ገበታ ቸው ላይ ሆነው እንደሆነ የ ማህበሩ ን አላማ የሚያ ትተው ጽሁፍ ያስረዳ ል',\n", - " 'tr_509_tr06009': 'ቋንቋዎች ን አዋህ ዶ አንድ መልክ በ ማስያዝ ተማሪዎች በዚህ አዲስ ቋንቋ እንዲ ማሩ እቅድ ይይዛ ል',\n", - " 'tr_510_tr06010': 'ትውውቁ ከ አገር ደረጃ ይልቅ እንደ ግል ትውውቅ የሚ ቆጠር ነው',\n", - " 'tr_511_tr06011': 'በ ኢትዮ ኤርትራ ወሰን የ ኮንትሮባንድ ንግድ በስፋት እየተካሄደ መሆኑ ተገለጸ',\n", - " 'tr_512_tr06012': 'አጀንዳ ችን ም ሀቁ ንና እቅጩን ለ ካድሬው ማሳወቅ ነው',\n", - " 'tr_513_tr06013': 'ወደ ህትመት እስከ ገባ ን ድረስ ስለ ታሰሩበት ምክንያት ማስረጃ ባ ና ገኝም በ ኢትዮጵያ ንግድ ባንክ የስራ ዘመናቸው ወቅት ጋር በ ተዛ መደ ሁኔታ ሳይሆን እንደማይ ቀር ተገምቷል',\n", - " 'tr_514_tr06014': 'ምናልባት የ ዲፕሎማቲክ ኮሚኒቲ ው ታዛቢ ነት ተፈር ቷል ሀያ ስምንት የግል ተወዳዳሪ ዎች አሉ',\n", - " 'tr_515_tr06015': 'ጥሩነሽ ና ወርቅነሽ ከ ማረሚያ ቤቶች ና ከ ባንኮች ስፖርት ክለብ የ ተገኙ አትሌቶች ናቸው',\n", - " 'tr_516_tr06016': 'ወይዘሮ አልማዝ ኢህአዴግ ን እንዲ ከዱ ያስ ቻላቸው ፖለቲካዊ ምክንያት ጓደኞቻቸው አንድ ም ከ ስልጣን መወገዳቸው ሁለት ም ከ ሀገር መውጣታቸው ነው',\n", - " 'tr_517_tr06017': 'ቴሌኮሙኒኬሽን በ መንግስት በ ሞኖፖል ተይዞ እንዲቀጥል የሚያደርግ ና ኢንቨስትመንት ን የሚ ያበረታታ ነው ተ ብሏል',\n", - " 'tr_518_tr06018': 'የኤርትራ መንግስት አብያተ ክርስትያ ን ን ዘጋ',\n", - " 'tr_519_tr06019': 'በ ሺህ ዎች የሚ ቆጠሩ የ መቀሌ ነዋሪዎች በ ኢዴፓ ስብሰባ ተገኙ',\n", - " 'tr_520_tr06020': 'የ ትግል ስል ቶቻቸው ም እንደ ዚሁ የተለያዩ ናቸው',\n", - " 'tr_521_tr06021': 'በ ግንባር ቀደምትነት የ ገቡት ን የኤርትራ ወታደሮች አስክሬን በ ብዛት ተመልክተ ናል በ ማለት የ እማኝነት ዘገባው ን አጠና ቋል',\n", - " 'tr_522_tr06022': 'በ ኢትዮጵያ ና ኬንያ ድንበር በሚገኙ አሸባሪዎች ላይ ኬንያ ጠንካራ እርምጃ ልት ወስድ ነው',\n", - " 'tr_523_tr06023': 'አንድ ኢንጂነር ን ጨምሮ አምስት ሰዎች ተገደሉ',\n", - " 'tr_524_tr06024': 'አስክሬኑ ን የ መለየቱ ስራ ከ ጥርስ ብሩ ሽ ና ከ ማበጠሪያ ላይ በ ተገኙ ናሙና ዎች የሚ ፈጸሙ መሆኑን ባለሙያዎች ይናገራሉ',\n", - " 'tr_525_tr06025': 'ኢትዮጵያ በ ግብጽ ቤተ ክርስቲያን ስር የ ኖረች ና መንፈሳዊ አባቶች ም ከ ዚያው ሲ ሾሙ ላት የ ነበረች ና ት',\n", - " 'tr_526_tr06026': 'የ ሜትሮ ሎጂ ትንበያ ችግር እየፈጠረ ነው',\n", - " 'tr_527_tr06027': 'ኢትዮጵያ ከ ሻእቢያ ጋር መደራደር እንደማት ችል ጀ በሀ አስ ታወቀ',\n", - " 'tr_528_tr06028': 'እቃው ን የሚ ያውቁት ሰው ቤት አ ኑረው ትንሽ ውሀ ለመቀ ማመስ ተስማሙ',\n", - " 'tr_529_tr06029': 'እና ም ዙሪያ ገባው ን መ ገላ መጥ መደበኛ ሙያው ሆነ',\n", - " 'tr_530_tr06030': 'ሊቨርፑል ትልቅ ፕሮፌሽናል ክለብ ነው',\n", - " 'tr_531_tr06031': 'ወቅቱ ገና ትኩስ ጊዜ ነበር',\n", - " 'tr_532_tr06032': 'ኢንሴንቲቭ ማለት ም ን ማለት ነው ዝም ብሎ ኢንሴንቲቭ ኢንሴንቲቭ ማለት ብቻ አይደለም',\n", - " 'tr_533_tr06033': 'ስለ ክሪስ ት ያን ቪዬሪ ም ን ት ላለህ',\n", - " 'tr_534_tr06034': 'ወትሮ ኦዌን በ ትሬይኒንግ ሜዳ ላይ ባለው ትኩረት ና ንቁ ነት አሰልጣኞች ይ ደነቁ በት ነበር',\n", - " 'tr_535_tr06035': 'ሀኪም ቤት ሄጄ ኢንፌክሽን አለ ብህ ተባልኩ',\n", - " 'tr_536_tr06036': 'እግር ኳስ ለዚህ ነው ተወዳጅ ሊሆን የ ቻለው',\n", - " 'tr_537_tr06037': 'የ አዲስ አባ እግር ኳስ ፌዴሬሽን ለ ውድድር ኳስ ማቅረብ ተስኖት በ ራሳቸው ኳስ ነው የሚ ጫወቱ ት',\n", - " 'tr_538_tr06038': 'ባለፈው ሳምንት ቅዳሜ የ አዲስ አባ እግር ኳስ ፌዴሬሽን ጠቅላላ ጉባኤ በ አራት ኪሎ ስፖርት ማእከል ተካሂ ዷል',\n", - " 'tr_539_tr06039': 'ስምምነቶች ንም እንደ ተፈራረመ ከ ዜና ምንጮቻችን ለ መረዳት ች ለናል',\n", - " 'tr_540_tr06040': 'በ በጀት ስለሚ በ ል ጧቸው ትንሹ አሳ በ ትልቁ አሳ መዋጡ ግልጽ ነው',\n", - " 'tr_541_tr06041': 'በሚገባ የተደራጀ ና ጠንካራ ታክቲክ ያለው ቡድን ነው እስከ ማለት ደርሰዋል',\n", - " 'tr_542_tr06042': 'የ ጉና ቡድን ደግሞ ከዛ ንዚባሩ ፖሊስ ጋር ለሚ ያደርገው ግጥሚያ ሀሙስ እ ለት ወደ ስፍራው ሄ ዷል',\n", - " 'tr_543_tr06043': 'ኢትዮጵያ የ ተሰጣት ን የ ቴክኒክ ማብራሪያ እያ ጤነ ችው ነው',\n", - " 'tr_544_tr06044': 'የ ሻእቢያ ስትራቴጂ ም እንደ ፈለጋቸው የሚ ያዙት ና የ ነሱ ጥገኛ የሆነ መንግስት ኢትዮጵያ ውስጥ ማስቀመጥ ነው',\n", - " 'tr_545_tr06045': 'የሚያገኙ ት የ ወር ደመወዝ ፈጽሞ ኪሳቸው እንደማይገባ ና ቤተ ክርስቲያ ኗን በ ነጻ ለሚ ያገለግሉ ሰዎች ና ለ ነዳያን ይ ከፋፈል እንደ ነበር ለማወቅ ች ለናል',\n", - " 'tr_546_tr06046': 'ለዚህ የ አሸባሪዎች እንቅስቃሴ ም ኤርትራውያን ን በ ግንባር ቀደምትነት ስለ ተጠራጠረ ች እንደሆነ ዘገባው ገልጿ ል',\n", - " 'tr_547_tr06047': 'ይህ ች ላ ባይነት ነው ዛሬ ተማሪዎች ትምህርታቸው ን አቁመው ለ ስቃይ እንዲ ዳረጉ የጋበዛቸው',\n", - " 'tr_548_tr06048': 'የ ጣልያን ና የ ኢትዮጵያ ግንኙነት እ የተበላሸ ነው',\n", - " 'tr_549_tr06049': 'በዚህ እ ለት በ ብዙ ሺህ የሚ ቆጠሩ ኢትዮጵያዊያ ን ኒውዮርክ በ ሚገኘው የ ተባበሩት መንግስታት ድርጅት ጽፈት ቤት ፊት ለፊት ይሰበሰባሉ ና ተቃውሞ ያሰማ ሉ',\n", - " 'tr_550_tr06050': 'እነዚህ ኢንቬስተ ሮች ደግሞ ኦሮሞዎች አይደሉም',\n", - " 'tr_551_tr06051': 'ድርጅቶቹ በ ተጨማሪ በዛ ያሉ የ ዲዛይን የ ታሪክ ና የ ፎቶ ሰነዶች ን እንዲ ላክ ላቸው ጥያቄ ማቅረባቸው ንም አቶ ጌታቸው ጨምረው ገልጸዋል',\n", - " 'tr_552_tr06052': 'አገራዊ አንድምታ ውን ስን መለከት ሁለት ተጻራሪ የሆኑ ክስተቶች ን ያዘ ለ ሂደት ሆኖ እና የ ዋለን',\n", - " 'tr_553_tr06053': 'ይኸ ጣጣ ነው ሁላችን ንም ያስቸገረ ን',\n", - " 'tr_554_tr06054': 'ም ን ማለት ነው አንድ ነገር ላይ ብቻ እንስማ ማለን',\n", - " 'tr_555_tr06055': 'ዶክተር ፍቅሬ መኢሶን ነበር',\n", - " 'tr_556_tr06056': 'እነዚህ የ ጦር ወንጀለኞች ተብለው በ እስር የሚ ማቅቁ ፓይለ ቶቻችን የማን እስረኞች ናቸው የሚለው የ ህዝብ ጥያቄ ግን ዛሬ ም እንዳለ ነው',\n", - " 'tr_557_tr06057': 'ሬውተር እንደ ዘገበው ማስጠንቀቅ ያውን ለ ኤርትራ መንግስት የ ላከው የ የመን የውጭ ጉዳይ ሚኒስቴር ነው',\n", - " 'tr_558_tr06058': 'አንዱ ና ዋነኛው ምክንያት መንግስት በ ተለያዩ መንገዶች በ ማህበሩ ላይ ሲፈ ጥራቸው የ ነበሩት ጫና ዎች ናቸው',\n", - " 'tr_559_tr06059': 'መንግስት በውጭ በሚ ኖሩ ኢትዮጵያውያ ን ዘንድ ሙሉ ድጋፍ እንዳለው ሊ ያሳየን ፈልጓል',\n", - " 'tr_560_tr06060': 'ኢ ሳቅ የ ተባለው ሌላው የ ሶማሌ ጐሳ ምንጭ ኢ ሳቅ ኢ ብን አህመድ የተባለ ሶማሌ ና ኢትዮጵያዊ ት እናት ናቸው',\n", - " 'tr_561_tr06061': 'መንግስት በ ኢንቨስትመንት እንቅስቃሴ ላይ የ ተከሰቱ የ ፖሊሲ ና የ አሰራር ግድፈቶች ን ለ ማስወገድ ርምጃ መውሰዱ ከ ግሉ ኢንቨስትመንት ፍሰት የ ሚገኘው ን ድርሻ እንደሚያ ሻሽለው ም ገለጹ',\n", - " 'tr_562_tr06062': 'እኔ ግን ነፍጠኛ ም መድፈኛ ም እንዳል ሆ ኩኝ ል ነግራችሁ ብዬ እንጂ ፖለቲከኛ ሳል ሆን አሽሙረኛ ነኝ ብዬ እናንተ ን ላሳምናችሁ አል ሞክር ም',\n", - " 'tr_563_tr06063': 'ኮሎኔል በዛብህ ጴጥሮስ የ አማራጭ ሀይሎች ሊቀመንበር ዶክተር በየነ ጴጥሮስ ወንድም መሆናቸው ተያይዞ ተ ገልጿ ል',\n", - " 'tr_564_tr06064': 'የ መስተዳድሩ መግለጫ ከተማዋ ስር ነቀል ለውጥ እንደሚ ያስፈልጋት ገልጾ ህዝቡ በዚህ እንዲ ሳተፍ ቢ ጠይቅ ም ጊዜያዊ መስተዳድሩ የ መዋቅር ለውጡ ን ያስፈጽማል ተብሎ አይጠበቅ ም',\n", - " 'tr_565_tr06065': 'ለወደፊቱ በሚ ዘጋጀው ጉባኤ የ በ ኩሌን ሀሳብ ለ ካድሬው ይዤ አቀርባ ለሁ',\n", - " 'tr_566_tr06066': 'ኤኤፍፒ ከ ሶስት ሺ በላይ የኤርትራ ኩናማ ዎች ወደ ኢትዮጵያ ሸሽተው በ መግባት የኤርትራ ሰራዊት በ ሀይል እየ መለመላቸው ነው ሲሉ ውንጀላ ሰንዝ ረዋል',\n", - " 'tr_567_tr06067': 'ዋናው አላማችን አባላ ቶቻችን ን በ ስፖርቱ ተሳታፊ እንዲሆኑ ና ለ ሀገራችን ስፖርት የ በኩላቸው ን አስተዋጽኦ እንዲ ያበረክቱ እንጂ እንደ አንዳንድ ክለቦች ድርጅት ን ለ ማስተዋወቅ አይደለም',\n", - " 'tr_568_tr06068': 'በ ማጠቃለያ ውም በ እርዳታ አ ሰባሰቡ ወቅት ኢህአዲግ በ በጐ አይ ን የማ ይመለከታቸው ና በ አሸባሪነት ጠርጥሬ ያ ቸዋለሁ የሚ ላቸው ኢትዮጵያውያ ን የ ህግ ታራሚዎች ሳይ ቀሩ በ እርዳታው ተሳትፎ ማድረጋቸው ን አመልክ ቷል',\n", - " 'tr_569_tr06069': 'የ ኢትዮጵያ ን የ ተፈጥሮ ሀብት ለ ማስተዋወቅ የ ሚያስችል የ መረጃ ስርአት ሊ ዘረጋ ነው ተ ባለ',\n", - " 'tr_570_tr06070': 'ይሁን እንጂ የ ፕሬሱ ን እድገት ለ ማሽመድመድ ብዙዎቹ እንዲ ቀጥሉ አልተደረገ ም ሲሉ ነጻው ፕሬስ ለ ዲሞክራሲያዊ ስርአት ግንባታ የሚያደርገው ን ሚና አሳቅ ለዋል',\n", - " 'tr_571_tr06071': 'ይህንን ም ያደረገ መንግስቱ ን መውደዱ በዚህ ያስታው ቃል',\n", - " 'tr_572_tr06072': 'ቀጥሎ ሙሉው ን መልእ ከ ት እንደሚ ከተለው እና ቀር ባለ ን',\n", - " 'tr_573_tr06073': 'ጆሮ ያለው ይስማ አእምሮ ያለው ም ያስተውል',\n", - " 'tr_574_tr06074': 'እንዴት እንሂድ በት መድረኩ ን እንዴት እን ሻገር በ ሚለው መጭው ጉዟችን ን በሚያ ቅደው ጉዳይ ም ሶስት ጽሁፎች ቀርበዋል',\n", - " 'tr_575_tr06075': 'ከ ጉባኤ ቀጥሎ የሚ መጣው ማእከላዊ ተቋም ማአከላዊ ኮሚቴ ነው',\n", - " 'tr_576_tr06076': 'ምክንያቱ ም እነርሱ ኮሚኒስቶች እኛ ዲሞክራ ቶች ነን',\n", - " 'tr_577_tr06077': 'የ ናይል ተፋሰስ የ ትብብር ሂደት አባላት ኢትዮጵያ ሱዳን ኬንያ ግብጽ ታንዛኒያ ሩዋንዳ ኮንጐ ኡጋንዳ ና ቡሩንዲ ሲ ሆኑ ኤርትራ በ ታዘ ቢ ነት ትሳተፋ ለች',\n", - " 'tr_578_tr06078': 'ፎረሙ ለ ሁለተኛ ጊዜ የሚ ሰጠው ን ሽልማት ለ አላሙዲ ን የሚያ በረክተው ዛሬ በ ዋሽንግተን ዲሲ ከተማ ነው',\n", - " 'tr_579_tr06079': 'የ ኦሮሚያ ተማሪዎች እንቅስቃሴ ና ተቃውሞ ከ ኦነግ ጋር የ ተያያዘ ነው ያሉት አቶ ጁነዲ ን ኦነግ ወጣቱ ን መጠቀሚያ እያደረገ ው ነው ሲሉ ም ውንጀላ አ ሰምተዋል',\n", - " 'tr_580_tr06080': 'ከ መንገድ የ ተመለሱ ኢትዮጵያውያ ን በ አስመራ ዩኒቨርስቲ ተጠልለው እንደሚገኙ ም የ ጀርመን ድምጽ ሬድዮ ከ ትናንት በስቲያ ዘግ ቧል',\n", - " 'tr_581_tr06081': 'የሚ ሞቱ ላትን ማግኘት ደግሞ እድለኛ ነት ነው',\n", - " 'tr_582_tr06082': 'መስጊዱ ዛሬ ጫካ ውስጥ ነው ያለው',\n", - " 'tr_583_tr06083': 'የ አለም ታዋቂ ስፖርት ሙያተኞች ፊታቸው ን ወደ እኛ ለ ማዞር ተገ ደዋል',\n", - " 'tr_584_tr06084': 'ሮናልዶ ም ቢሆን ናይክ ኩባንያ ሌሎች የ ቡድኑ ቴክኒክ ኮሚቴ አባላት ዛጋሎ ም ሆኑ ዚኮ ማ ንም እንድ ጫወት አላስ ገደዱ ኝም ብሏል',\n", - " 'tr_585_tr06085': 'አሰልጣኝ ጆን ግሮ ጐሪ በማ እ ዳቸው ዝና ካ ላቸው ክለቦች መካከል ሊቨርፑል ብቻ ነው ያስተናገዱት',\n", - " 'tr_586_tr06086': 'በ ዝግ ስታዲየም ጨዋታዎች ከተ ከናውነው ያውቃሉ ለተ ወዳጆቹ ኢን ተሮች እንደ ተለመደው በ ቅድሚያ ሰላምታ ዬን እ ያቀረብኩ እ ጀምራ ለሁ',\n", - " 'tr_587_tr06087': 'ሙሉ ስማቸው ዣን ሚ ሼል ቤኔዜ ይባላል',\n", - " 'tr_588_tr06088': 'እንደሚ ገባኝ የ ም ኖረው የዛሬ ን በ ማሰብ ነው',\n", - " 'tr_589_tr06089': 'የ ሶማሊያ ስደተኞች ወደ ኢትዮጵያ እየ ጐረፉ ነው',\n", - " 'tr_590_tr06090': 'በ ህገ መንግስታችን ላይ እንደ ሰፈረው ማንኛውም ሰው ዋስትና የ ማግኘት መብት አለ ው',\n", - " 'tr_591_tr06091': 'ሌሎች ተጨማሪ ሶስት መቶ የ ጣ ና ገበያ ሰራተኞች ም እንዲ ሁ ተመሳሳይ አደጋ አንዣብቦ በ ቸዋል',\n", - " 'tr_592_tr06092': 'የ ኢትዮጵያ መንግስት የ ማስፈጸም አቅሙ ሊ ጠነክር ና ሊ ጐለብት ይችላል',\n", - " 'tr_593_tr06093': 'ዛሬ ደግሞ ያ እ ርእዮት ተናጋ',\n", - " 'tr_594_tr06094': 'ሰዎቹ አእምሮ ውስጥ ዘወትር ያለው ም ጠመንጃ ነው',\n", - " 'tr_595_tr06095': 'መደማመጥ እጅግ አስቸጋሪ ነው',\n", - " 'tr_596_tr06096': 'እኒህ ኢትዮጵያዊ ከ ዚያች ቀን ጀምሮ በ ጠላትነት የ ተፈረጁ ና ዛሬ ም በ አዛውንት እድሜ አቸው በ ደካማ ጤናቸው በ እስር የሚ ማቅቁ ት ፕሮፌሰር አስራት ወልደየስ ናቸው',\n", - " 'tr_597_tr06097': 'አንዳንድ ታዛቢዎች እንደሚ ሉት አቶ ኢሳይያስ የ ደጋው ክርስቲያን ህዝብ ተወካይ ተብለው ተ ፈርጀ ዋል',\n", - " 'tr_598_tr06098': 'ለዚህ ም ሶስት ምክንያቶች ን አቅርበ ዋል',\n", - " 'tr_599_tr06099': 'የ መንገደኞች አውሮፕላን ለ መጥለፍ የ ተደረገው ሙከራ ከሸፈ',\n", - " 'tr_600_tr06100': 'ምክንያቱ ም ስኮትላንዶች ያገቡ ትን ጐል በ ዝግታ ያስተላልፍ ነበር ይላል የዛሬ ተ ጋባዣችን ማይክል ኦ ይ ን',\n", - " 'tr_601_tr07001': 'ስራው ንም አያገኝ ም ምክንያቱ ም እነሱ ባላቸው ደረጃ ና ዲስፒሊን የተወሰነ ብቃት ሊ ኖረው ይገባል',\n", - " 'tr_602_tr07002': 'የ ኢትዮጵያ ብሄራዊ ቡድን ጊኒ ን በ ማሸነፍ ደረጃው ን አ ሻሻለ',\n", - " 'tr_603_tr07003': 'ግንባሩ ና አባል ድርጅቶቹ ከ ኢህአዴግ ጉባኤ በኋላ በ የ ደረጃው የሚገኙ አባላት ዘንድ የ ተሀድሶ ውን አስተሳሰብ ለ ማስረጽ ና ለ ማጐልበት የሚያስችሉ እንቅስቃሴ ዎች ማካሄዳቸው ን አስ ታውቋል',\n", - " 'tr_604_tr07004': 'ግን አዲስ የ ተሾሙ አምባሳደሮች ም ሆኑ ተሰናባ ቾቹ አምባሳደሮች ለ ፕሬዝዳንት ነጋሶ ኤርትራውያን ከ ሀገር እንዲ ባረሩ የ ተደረገበት እርምጃ ን መንግስት ሊ መረምረው ይገባል ብለዋ ቸዋል',\n", - " 'tr_605_tr07005': 'የ ኢትዮጵያ ኦርቶዶክስ ተዋህዶ ቤተ ክርስቲያን ካህናት ና ምእመናን መከራ የ ገጠማቸው በ ሀገራቸው በ ቤታቸው ነው',\n", - " 'tr_606_tr07006': 'ጥያቄ ውን ያነሱት ስለ ጉዳዩ በሚገባ የሚያውቁ የ ጦር መኮንኖች ናቸው',\n", - " 'tr_607_tr07007': 'የ ኢሳያስ አስተዳደር ለ ኢትዮጵያዊያ ን ህጻናት የ ዝመቱ ጥሪ ማቅረቡ ተጋለጠ',\n", - " 'tr_608_tr07008': 'ክርስቶስ ከ ሙታን እንደ ተነሳ በ ሀዋርያት ተ ጽፏል',\n", - " 'tr_609_tr07009': 'አንዳንድ የ ን አካባቢው ምንጮች እንደ ገለጹት ከሆነ ከዚህ ቀደም ቋንቋው ን በ መቃወማቸው ታስረው የነበሩ ሰዎች ን እስከ ማስፈታት ደረጃ ተደረሰ',\n", - " 'tr_610_tr07010': 'ስዊዘርላንድ ከ ኢትዮጵያ ይልቅ ወደ ኤርትራ ስት ን ሸራተት የምት ታይ አገር ነች',\n", - " 'tr_611_tr07011': 'ሁሴን አይዲድ በ ተሸናፊ ነት አዲስ አበባ ናቸው',\n", - " 'tr_612_tr07012': 'ቅድሚያ እድሉ ን እንዲ ሰጠን እየ ጠየቅ ን ነው',\n", - " 'tr_613_tr07013': 'ኢትዮ ፕስ አርት ወደ ጃፓን ሄደ',\n", - " 'tr_614_tr07014': 'በዚህ ላይ እጩዎች ን ለ ማስተዋወቅ ብዙ መድረኮች አሉት',\n", - " 'tr_615_tr07015': 'ዘመናዊ ስታዲየም እን ገነባ ለ ን ብለው ነበር ፕሬዚዳንት መንግስቱ ሀይለ ማርያም',\n", - " 'tr_616_tr07016': 'ም ንም እንኳ ን ኢህአዴግ በ ፌዴሬሽን ምክር ቤት ውስጥ አለ ኝ ብሎ የሚመካ ባቸው ቢሆን ም ውሎ አድሮ ሊፈ ነቅ ላቸው እንደሚ ችል ገም ተዋል',\n", - " 'tr_617_tr07017': 'ኢትዮጵያውያ ን ታጣቂዎች በ ሰላም አስከባሪ ዎች ላይ ተኩ ሰዋል',\n", - " 'tr_618_tr07018': 'የኤርትራ መንግስት ከ ኦርቶዶክስ ተዋህዶ ሮማን ካቶሊክ ና ከ ወንጌላዊ ት መካነ ኢ የሱስ ቤተ ክርስቲያና ት በስተቀር ሌሎች አብያተ ክርስትያናት ን መዝጋቱ ታወቀ',\n", - " 'tr_619_tr07019': 'የ ተናገሩት እኛ እየ ለመን ን ነበር',\n", - " 'tr_620_tr07020': 'ለ አለም ዋንጫ ማጣሪያ በ መጀመሪያ ው ዙር ኢትዮጵያ ቡርኪናፋሶ ን አሸነፈ ች',\n", - " 'tr_621_tr07021': 'የ ኦጋዴን ነጻ አውጪ ግምባር በ ምስራቅ ኢትዮጵያ ሽምቅ ውጊያ ከፈት ኩ አለ',\n", - " 'tr_622_tr07022': 'ካናቢስ ተጠቅ መዋል የተባሉ ኢትዮጵያዊ ገበሬ ና አንድ አሜሪካዊ ተያዙ',\n", - " 'tr_623_tr07023': 'ለ ኢትዮጵያ ወደብ ይገባ ታል ባለ ማለቴ ተጠያቂ ነኝ አሉ ገብሩ አስራት በ ለንደን',\n", - " 'tr_624_tr07024': 'በ ጀርመን ለምን ገኝ ኢትዮጵያውያ ን ስደተኞች በሚል የ ተላለፈው ሪፖርት ከ ስደተኝነት መብት አኳያ የ ሚከተለው ን መብት ይ ዟል',\n", - " 'tr_625_tr07025': 'ኤርትራ ወራሪ ና ት',\n", - " 'tr_626_tr07026': 'ኢትዮጵያውያኑ ኤርትራውያኑ ን እንደሚ ቀጡ ያ ም ና ሉ',\n", - " 'tr_627_tr07027': 'በ ሶስት ስትራቴጂ ያዊ ወታደራዊ ቀጠና ዎች ሀያ ሺ የ ኢሮብ ነዋሪ ተገዶ ወደ ማጐሪያ ካምፕ ተከማች ቷል',\n", - " 'tr_628_tr07028': 'ንዴት ከ አረቄ ው ጋር ተባብሮ ቢያ ነደው ም እቃው ን ተሸክሞ ጉዞ ጀመረ',\n", - " 'tr_629_tr07029': 'እንደ ገላመጣት አልቀረ ም ቆሎ ዋን ሸጣ ወደ ቤቷ ስት ኳት ን ከ ዙፋኑ ተነስቶ ተ ከተ ላት',\n", - " 'tr_630_tr07030': 'በዚያ ክለብ ውስጥ የሚ ሰሩት በ ሙሉ ስራቸው ን ያውቁ ታል',\n", - " 'tr_631_tr07031': 'ስለዚህ ብዙ ያስተዋል ኳቸው ነገሮች የ ሉም',\n", - " 'tr_632_tr07032': 'እስከሚ ገባ ን ኢንሴንቲቭ ና ቦነስ ይለያ ያሉ',\n", - " 'tr_633_tr07033': 'እርሱ ድንቅ ነው',\n", - " 'tr_634_tr07034': 'ይህን አይነት ክትትል ነው ኦዌን የሚ ያስፈልገው እየተ ባለ ነው',\n", - " 'tr_635_tr07035': 'ግን ከዚያ በኋላ እንዴት ልት ቀንስ ቻልክ',\n", - " 'tr_636_tr07036': 'በሚ ሰጣቸው ፕሮግራም ና እረፍት ይ እራሳቸው ን አዝና ን ተው ይ መጣሉ',\n", - " 'tr_637_tr07037': 'ነገሩ ግን አስገራሚ ሆኗል',\n", - " 'tr_638_tr07038': 'ሻምበል ማሞ ወልዴ እንደ ማንኛውም ኢትዮጵያዊ በ ህግ ይዳ ኛል',\n", - " 'tr_639_tr07039': 'አዲዳስ ደግሞ የ ጀርመን ነው',\n", - " 'tr_640_tr07040': 'ስለዚህ ይህን አውቀ ን ባይሆን ክ ለ ክልሎች ስፖርት እድገት የሚ ጠቅመው ን እንስራ',\n", - " 'tr_641_tr07041': 'እንዲያ ውም የ ሪያል ማድሪድ ክለብ እየጐተጐተ ው መሆኑን በ ስፔን የሚ ና ፈሱ ወሬ ዎች አሉ',\n", - " 'tr_642_tr07042': 'ቡድኑ አስራ ስምንት ተጨዋቾች ን ይዞ ነው የሚ ሄደው',\n", - " 'tr_643_tr07043': 'ሌላኛው ም የ ኢትዮጵያ መሰረታዊ ጥያቄ በ ግጭቱ ስፍራ የ ኢትዮጵያ ሲቪላ ዊ አስተዳደር እና የ ፖሊስ ተቋማት እንዲ ቋቋሙ ያቀረበች ውን አቋሟ ን እስከ አሁን ድረስ አል ለወጠች ውም',\n", - " 'tr_644_tr07044': 'ታዛቢዎች እንደሚ ሉት ደግሞ እህል ከ ኢትዮጵያ ወደ ኤርትራ በ ጅቡቲ በኩል እንደሚ ሄድ ይናገራሉ',\n", - " 'tr_645_tr07045': 'ዶክተር ነጋሶ ማን ናቸው ከ እርስዎ በላይ የሚ ቀርባቸው ሰው የ ለ ም',\n", - " 'tr_646_tr07046': 'ዶክተር በየነ ጴጥሮስ በ ተወዳደሩ ባቸው ዞኖች ውጤቱ እንዳይ ነገር ታገደ',\n", - " 'tr_647_tr07047': 'ነገር ግን ተዘዋው ሬ እንደ ተመለከትኩ ት ህመሙ የ ጠና ባቸው ና በልዩ ስፍራ ተ ከልለው አይ ሶሌ ሽን የ ተገኙት ተማሪዎች ብዛት ወደ አራት መቶ ይጠ ጋል',\n", - " 'tr_648_tr07048': 'በ ጉዳዩ ዙሪያ አስተያየታቸው ን የ ጠየቅናቸው ታዛቢዎች እንዳሉት ከሆነ ጣሊያን ና ኢትዮጵያ በ ኢትዮ ኤርትራ ጦርነት ጊዜ ና በ ሱማሊያ ጉዳይ ዙሪያ አለመግባባቶች አ ሏቸው',\n", - " 'tr_649_tr07049': 'በ ዋሽንግተን ና አካባቢ ዋ የሚኖሩ ኢትዮጵያውያ ን አስራ ሁለት አውቶቡሶች የ ተከራዩ ሲሆን በ እለቱ ወደ ኒውዮርክ ከተማ ተቃውሟቸው ን ለ ማሰማት ይገሰግ ሳሉ',\n", - " 'tr_650_tr07050': 'የ ነጻው ፕሬስ ህልውና አስጊ ሆኗል',\n", - " 'tr_651_tr07051': 'የ ትልማ ፕሬዚዳንት በ አቶ ገብሩ ምክንያት ወረዱ',\n", - " 'tr_652_tr07052': 'ይህ እንግዲህ የ ፖሊሲው አንደኛው ገጽታ ነው',\n", - " 'tr_653_tr07053': 'ፕሮፌሰር አክሊሉ የ ኢትዮጵያ መንግስት ልዩ አማካሪ በ ነበሩ ጊዜ ም የ ኢትዮጵያ የ ሳይንስ ና የ ቴክኖሎጂ ኮሚሽን እንዲ ቋቋም አድርገዋል',\n", - " 'tr_654_tr07054': 'ቋንቋ አዳጊ ስለሆነ የ ስ የ ስ ነገሩ ገብቶ ናል ብለን ልናል ፈው እንችላ ለ ን',\n", - " 'tr_655_tr07055': 'ለኔ ሞት ሞት ነው',\n", - " 'tr_656_tr07056': 'ኤርትራ የ ታጠቀ ችው ሚግ ሀያ ዘጠኝ በ ሩሲያ ውስጥ ካሉ ት ምጡቅ የ ኤሮ ኖ ቲክስ ቴክኖሎጂ ውጤት አንዱ ነው',\n", - " 'tr_657_tr07057': 'በሚ ሆን መንገድ እልባት ካላገኘ ይህ የ ታሪክ እንቆቅልሽ ሊ ቀጥል እንደሚ ችል መገመት ም አ ያስቸግር ም',\n", - " 'tr_658_tr07058': 'አስራ ሶስት ሺ ያህል ተፈናቅ ለዋል',\n", - " 'tr_659_tr07059': 'ህዝብ ና የ መረጣቸው ወኪሎቹ የማያውቋቸው ተግባሮች በ መንግስት ባለስልጣናት በ ጓዳ እንዳይ ፈጸሙ ይፈልጋል',\n", - " 'tr_660_tr07060': 'እስረኞቹ ም እንዲ ለቀቁ የ ሚመለከታቸው ኢትዮጵያውያ ን እና ተቃዋሚ ቡድኖች ጠንካራ ዘመቻ እያ ካሄዱ ናቸው',\n", - " 'tr_661_tr07061': 'መንግስት በ ኢንቨስትመንት እንቅስቃሴ ላይ የ ተከሰቱ የ ፖሊሲ ና የ አሰራር ግድፈቶች ን ለ ማስወገድ እርምጃ መውሰዱ ከ ግሉ ኢንቨስትመንት ፍሰት የ ሚገኘው ን ድርሻ እንደሚያ ሻሽለው ም ገለጹ',\n", - " 'tr_662_tr07062': 'እኔ ግን ነፍጠኛ ም መድፈኛ ም እንዳል ሆ ኩኝ ልንገራችሁ ብዬ እንጂ ፖለቲከኛ ሳል ሆን አሽሙረኛ ነኝ ብዬ እናንተ ን ላሳምናችሁ አል ሞክር ም',\n", - " 'tr_663_tr07063': 'ኮ ኖሬ ል በዛብህ ጴጥሮስ የ አማራጭ ሀይሎች ሊቀመንበር የ ዶክተር በየነ ጴጥሮስ ወንድም መሆናቸው ተያይዞ ተ ገልጿ ል',\n", - " 'tr_664_tr07064': 'የ መስተዳድሩ መግለጫ ከተማዋ ስር ነቀል ለውጥ እንደሚ ያስፈልጋት ገልጾ ህዝቡ በዚህ እንዲ ሳተፍ ቢ ጠይቅ ም ጊዜያዊ መስተዳድሩ የ መዋቅር ለውጡ ን ያስፈጽማል ተብሎ አይጠበቅ ም',\n", - " 'tr_665_tr07065': 'ለወደፊቱ በሚ ዘጋጀው ጉባኤ የ በ ኩሌን ሀሳብ ለ ካድሬው ይዤ እ ቀር ባለሁ',\n", - " 'tr_666_tr07066': 'ኤኤፍፒ ከ ሶስት ሺ በላይ የኤርትራ ኩናማ ዎች ወደ ኢትዮጵያ ሸሽተው በ መግባት የኤርትራ ሰራዊት በ ሀይል እየ መለመላቸው ነው ሲሉ ውንጀላ ሰንዝ ረዋል',\n", - " 'tr_667_tr07067': 'ዋናው አላማችን አባላ ቶቻችን በ ስፖርቱ ተሳታፊ እንዲሆኑ ና ለ ሀገራችን ስፖርት የ በኩላቸው ን አስተዋጽኦ እንዲ ያበረክቱ እንጂ እንደ አንዳንድ ክለቦች ድርጅት ን ለ ማስተዋወቅ አይደለም',\n", - " 'tr_668_tr07068': 'በ ማጠቃለያ ውም በ እርዳታ አ ሰባሰቡ ወቅት ኢህአዲግ በ በጐ አይ ን የማ ይመለከታቸው ና በ አሸባሪነት ጠርጥሬ ያ ቸዋለሁ የሚ ላቸው ኢትዮጵያውያ ን የ ህግ ታራሚዎች ሳይ ቀሩ በ እርዳታው ተሳትፎ ማድረጋቸው ን አመልክ ቷል',\n", - " 'tr_669_tr07069': 'በ ኢትዮጵያ የ ተከሰተው የ ምግብ እጥረት ወደ ተባባሰ ደረጃ ሊ ሸጋገር እንደሚ ችል ስጋት መኖሩ ተነገረ',\n", - " 'tr_670_tr07070': 'ፕሮፌሰር አስራት ሆስፒታል እንደ ተኙ ነው',\n", - " 'tr_671_tr07071': 'አንተ ግን ውስጥ ለ ውስጥ መሸጥ ህን ና መግዛት ህን የማት ተው ሆንክ',\n", - " 'tr_672_tr07072': 'የ ሚከተለው ም እምነት ክርስትና ነው',\n", - " 'tr_673_tr07073': 'እንዲሁም ሀብታሙ ሰው ሞተ ና ተቀበረ',\n", - " 'tr_674_tr07074': 'ጥያቄዎች አንስተ ን የመሰለ ን ን አቋም እንወስ ዳለን',\n", - " 'tr_675_tr07075': 'አባላቱ በ ጉባኤ የ ተመረጡ ናቸው',\n", - " 'tr_676_tr07076': 'በ አዲስ አበባ ዩኒቨርስቲ የሚማሩ ተማሪዎች መሰባሰብ ጀምረ ዋል',\n", - " 'tr_677_tr07077': 'ኢትዮጵያ በ አብዛኛው የ ኢኮኖሚ ነጻነት ያል ሰፈነ ባት አገር ተባለች',\n", - " 'tr_678_tr07078': 'ፎረሙ ሁለተኛው ን ስብሰባው ን ትላንት በዚያ ችው ከተማ ጀም ሯል',\n", - " 'tr_679_tr07079': 'ዛሬ ወገኖቻችን በ ማዳበሪያ ና በ ግብር እዳ እየተ ሰቃዩ ነው',\n", - " 'tr_680_tr07080': 'በ ስደት የሚገኙ ተማሪዎች ን ለ መመለስ በ መንግስት የተላከ ው ስምንት አባላት ያለው ቡድን ያለ ውጤት ተመለሰ',\n", - " 'tr_681_tr07081': 'ከ ሀያ የሚበልጡ ት ደግሞ ተ ሰደዋል',\n", - " 'tr_682_tr07082': 'ታዲያ ይህ ታላቅ የ ታሪክ ቅርስ እንደምን እንዲ ህ ተረስቶ ና ተዳፍ ኖ የቀረ የሚ ል ሊ በዛ ነው የሚ ከጀለ ው ዛሬ',\n", - " 'tr_683_tr07083': 'ገዛ ኸኝ አባራ በ ማራቶን ባሸነፈ ማግስት ሁለት ሺ ማራቶን ማ ጂክ በሚል ርእስ ሰፊ ዘገባ ቀርቧል',\n", - " 'tr_684_tr07084': 'ከዚህ ሌላ የ ሀገሪቱ ፕሬዚዳንት ፌርናንዶ ሄን ሪኬ ካርዶ ዞ ኤርፖርት ተገኝተው የ እንኳ ን ደህ ና መጣችሁ አበባ አበርክ ተው ላቸዋል',\n", - " 'tr_685_tr07085': 'ወደ ጣልያን ስ ና መራ ባለፈው እሁድ መሪው ፊዮሬንቲና ወደ ባሪ ተ ጉዞ ሁለት ነጥብ ጥሎ እና ገኘ ዋለን',\n", - " 'tr_686_tr07086': 'እና ም አንተ የዚህ ሰለባ እንደ ሆንክ ነው የሚ ሰማኝ',\n", - " 'tr_687_tr07087': 'አንዳንዴ ም እስከ ሶስት ጨዋታ ለ መመልከት ች ያለሁ',\n", - " 'tr_688_tr07088': 'እንዲያ ውም ያ ወቅት ብዙ አልቆ የ ም',\n", - " 'tr_689_tr07089': 'የ ሶማሊያ ስደተኞች ሊ ሰደዱ የ በቁት ድርቅ ደቡባዊ ሶማሊያ ን ክፉ ኛ ስለ መታው እንደሆነ ተመልክ ቷል',\n", - " 'tr_690_tr07090': 'ምክንያት ሲ ያጡ እኔን በ እስር ቤት ለ ማቆየት ብቻ ምክንያት እየ ፈጠሩ ብኝ ነው',\n", - " 'tr_691_tr07091': 'ጉዳዮች ውድቅ እንደሚ ያደረጉ እኔ ና ሌሎቹ ተከሳሾች አስቀድመ ን አ ም ተ ን ነበር',\n", - " 'tr_692_tr07092': 'አላማችን ን እንስ ታለን የሚ ል ሀሳብ ነው ያ ላቸው',\n", - " 'tr_693_tr07093': 'የ ኛ ም መንገዳችን ያው ይመ ስላል',\n", - " 'tr_694_tr07094': 'ይህ ሁሉ ከ አባቶቻችን ና ከ እናቶቻችን የ ወረስ ነው ነው',\n", - " 'tr_695_tr07095': 'ወደ እስር ቤታቸው ተመለሱ',\n", - " 'tr_696_tr07096': 'ምናልባት ይሄን ን እናንተ ም ሳት ሰሙት የ ቀራ ችሁት አይመስ ለ ንም',\n", - " 'tr_697_tr07097': 'ሌላው የ አሜሪካኖች ን ትኩረት የ ሳበው የ ተቃዋሚዎች ን እንቅስቃሴ ነው',\n", - " 'tr_698_tr07098': 'የ ፕሮፌሰር መስፍን ህመም መንስኤ የ ሳምባ ም ች ኒሞኒያ እንደሆነ ለማወቅ ተችሏል',\n", - " 'tr_699_tr07099': 'የ አክሱም ሀውልት እንዲ መለስ ኢትዮጵያ ያቀረበች ው ረቂቅ ውሳኔ አአድ አ ጸደቀው',\n", - " 'tr_700_tr07100': 'ምክንያቱ ም ባለ ኝ ኳሊቲ ዎች እ ተማ መ ና ለሁ',\n", - " 'tr_701_tr08001': 'ያን ን ለ ሟሟላት ትምህርት መቅሰም ና የተለያዩ ፈተና ዎችን ማለፍ ይገባ ዋል',\n", - " 'tr_702_tr08002': 'በ ሱዳን የ ተጀመረው ን የ ሰላም ሂደት ተግባራዊ ለማድረግ መንግስት ና ተቃዋሚ ድርጅቶች የ ተኩስ አቁም እንዲያደርጉ ና ህዝቡ ን ከ ስቃይ ለማዳ ን እንዲ ጥሩ አሳስቧ ል',\n", - " 'tr_703_tr08003': 'ልዩ የ ንግድ ስምምነቱ የ ኢትዮ ሱዳን ን ኢኮኖሚያዊ ና ፖለቲካዊ ትስስር ወደ ላቀ ደረጃ የሚ ያሸጋግር ነው',\n", - " 'tr_704_tr08004': 'ተግባባን አሉ ብሎ አንዱ ነገረኝ',\n", - " 'tr_705_tr08005': 'እስራኤላውያን መከራው ሲ ጸና ባቸው ከ ተሰደዱ በት አገር በ ስንት መከራ ወደ አገራቸው ተመለሱ',\n", - " 'tr_706_tr08006': 'አብዛኞቹ ቃኘው ግቢ ውስጥ የሚገኙ ሲሆን ለ እያንዳንዳቸው ስድስት ሺ ብር ሰጥቶ ሸኝቷ ቸዋል',\n", - " 'tr_707_tr08007': 'ሁሴን አይዲድ በ ኢትዮጵያ ላይ ጦርነት ለሚያ ውጅ ማንኛውም አሸባሪ አገራቸው ምሽግ እንደማት ሆን ቃል ገቡ',\n", - " 'tr_708_tr08008': 'ሽብርተኞች ና ወንጀለኞች ም ሊ ያውቁት የሚገባው ይሄን ን ነው',\n", - " 'tr_709_tr08009': 'የ አካባቢው ነዋሪዎች ቢ ያንስ ሶስት ሰው እንደ ሞተ ነው የሚናገሩ ት',\n", - " 'tr_710_tr08010': 'እስከ አሁን ከ ኢትዮጵያ አንጻር የ ቆመው ሀቅ ብቻ ነው',\n", - " 'tr_711_tr08011': 'እንደ ምንጮቻችን ገለጻ ሁሴን አይዲድ ከውጭ ጉዳይ ሚኒስቴር ጋር እንደ ተነጋገሩ ግምት አሳድ ሯል',\n", - " 'tr_712_tr08012': 'ምክንያቱ ም ስለ ስብሰባው አስተያየት ሊ ኖረን ይችላል',\n", - " 'tr_713_tr08013': 'አስራ አምስት አርቲስቶች ን ያካተተ ው የ ኢትዮ ፕስ አርት ባህላዊ የ ሙዚቃ ቡድን ከ ጃፓን በ ተደረገ ለት ጥሪ መሰረት ጃፓን ገብቷል',\n", - " 'tr_714_tr08014': 'ላቁ አ ተ አንድ ለቆ ራሽ ራቁ አ ተ ይላሉ ቆራ ሽ እሳቸው ናቸው',\n", - " 'tr_715_tr08015': 'ከ ሽግግሩ መንግስት ማግስት ጀምሮ ክቡር ጠቅላይ ሚኒስትር ፕሬዚዳንት እንደ ነበሩ መለስ ዜናዊ ዛሬ ም ብዙ ሰዎች የሚ ያነሱት ና የሚ ያስታውሱ ት ነው',\n", - " 'tr_716_tr08016': 'የ ትግል ተሳትፎ የ አገልግሎት ሪቫ ን ሜዳይ ካገኙ ት ጄኔራሎች መሀከል ባለ አምስት ሪቫ ን በ ማግኘት ቅድሚያ የ ያዙት ብርጋዴር ጄኔራል ካሳ ደሜ ናቸው',\n", - " 'tr_717_tr08017': 'የ ጠቅላይ ሚኒስትሩ ወቀሳ ተ ተቸ',\n", - " 'tr_718_tr08018': 'መንግስት ለ ኢትዮጵያውያ ን ስደተኞች የሚ ጠቅም አሰራር እንዲ ዘረጋ ተጠየቀ',\n", - " 'tr_719_tr08019': 'የ ተጠቀሙ ት ወያኔ ና ጥቂት ካድሬዎች ብቻ ናቸው',\n", - " 'tr_720_tr08020': 'የ ኢትዮጵያ ንግድ ባንክ እነዚህ እጥረት ላለ ባቸው ባንኮች በ ሁለት አመት ውስጥ ሀያ ሚሊዮን ብር ብድር እንደ ሰጣቸው ም የ ውስጥ አዋቂ ምንጮቹ ገልጸዋል',\n", - " 'tr_721_tr08021': 'በተለይ ወታደራዊ ክንፋ ችንን እያ ጠናከር ን እንገ ኛለን',\n", - " 'tr_722_tr08022': 'አቶ ሀሰን በ ሪፖርታቸው እንደ ገለጹት ወደ አረብ ሀገሮች በ ህገ ወጥ መንገድ የሚ ሰደዱ ኢትዮጵያውያ ን ን ለ መርዳት በ ዮርዳኖስ የ ኢትዮጵያ ቆንስላ ጽፈት ቤት ተከፍ ቷል',\n", - " 'tr_723_tr08023': 'የኤርትራ ተቃዋሚ መሪ ኢሳያስ ን ዘለፉ',\n", - " 'tr_724_tr08024': 'በ ሀዲያ ትምህርት ቤቶች ተ ዘግ ተዋል የ ሰራተኞች ም ደሞዝ ተቋር ጧል',\n", - " 'tr_725_tr08025': 'ዛሬ ዩጐዝላቪያ በ ና ቶ የ ጦር ጀቶች እየ ተደበደበ ች ነው',\n", - " 'tr_726_tr08026': 'ይሁን ና የ ፈለገ ነገር ቢ ያጡ ና መስዋእት ነቱ ቢ ከፋ ም ኢትዮጵያውያኑ ኤርትራውያኑ ን እንደሚ ቀጡ ና እንደሚ ያሸንፉ ሙሉ በ ሙሉ እ ርግጠ ኞች ናቸው',\n", - " 'tr_727_tr08027': 'ኢትዮጵያ በ አንቶኖቭ ጀት ተጠቅ ማለች ሲል ም የኤርትራ መንግስት ክስ አቅርቧ ል',\n", - " 'tr_728_tr08028': 'አምሮ ባቸው እንደ ወጡ ፍጻሜ ያቸው ተበላሽቶ ዛሬ ባል ፍርዱ ን እየ ጠበቀ ነው',\n", - " 'tr_729_tr08029': 'ጨለማ ቦታ ስት ስ ደርስ ጩቤ ውን አውጥቶ አስፈራራ ት',\n", - " 'tr_730_tr08030': 'ያን እ ለት እንደማ ልጫወት ሲ ነግረኝ ተናድጄ ነበር',\n", - " 'tr_731_tr08031': 'በ አብዛኛው ጥሩ እውቀት ያ ላቸው ናቸው',\n", - " 'tr_732_tr08032': 'ኢንሴንቲቭ እ ኮ የሚ ታሰበው በ የ ጨዋታው ነው',\n", - " 'tr_733_tr08033': 'እስካሁን ሀያ ስድስት ደር ሻለሁ',\n", - " 'tr_734_tr08034': 'አሰልጣኝ ጋሪ ፍራን ሲ ስ ስፐርስ እያሉ ተጫዋቾች ን ብዙ ኪሎ ሜትሮ ች እያስ ሮጡ ከባድ የ ፊትነስ ትሬይኒንጐ ችን የሚያ ሰሩት በ ማክሰኞ ቀን ነበር',\n", - " 'tr_735_tr08035': 'እኔ እ ኮ ጥሩ እንዳል ሆንኩ አውቀ ዋለሁ',\n", - " 'tr_736_tr08036': 'ቡድናችን በ ተሸነፈ ቁጥር ተጫዋቾች ን ከ ዲስፕሊን ጋር በ ማገናኘት ተጠያቂ ማድረጉ ተገቢ አ ይመስለኝ ም',\n", - " 'tr_737_tr08037': 'ሎንስ በዚህ በ ቻምፒየንስ ሊግ ጨዋታ ላይ በ የ ጨዋታው ድል ካደረገ እያንዳንዱ ተጫዋች ሀያ አምስት ሺ ብር እንደሚ ያገኝ ታውቋል',\n", - " 'tr_738_tr08038': 'ውሳኔው ን ማግኘት የሚ ችለው ከ ህግ ፊት ነው',\n", - " 'tr_739_tr08039': 'በ አፍሪካ የ አዳዲስ ትጥቆች የሚመረቱ ባቸው ሀገሮች ሞሮኮ ና ቱኒዚያ ናቸው',\n", - " 'tr_740_tr08040': 'ሌሎቹ ግን እንደ ወትሮው አልነበሩ ም',\n", - " 'tr_741_tr08041': 'እስካሁን መሪው ፊዮሬንቲና ደረጃው ን ይዞ ጉዞው ን ተያይዞ ታል',\n", - " 'tr_742_tr08042': 'ቅዱስ ጊዮርጊስ በ አዳማ ሶስት ለ ዜሮ ተሸን ፎ በ አራተኛው ቀን ደግሞ መቀሌ ላይ ትራንስ ን ሶስት ለ አንድ ረ ቷል',\n", - " 'tr_743_tr08043': 'ስለ እኚህ ኢጣሊያ ዊ ዲፕሎማት ጀርባ ም ሆነ ስለ ሽምግልናው በ ኢትዮጵያ መንግስት በኩል እስከ አሁን ድረስ አስተያየት አልተሰጠ በት ም',\n", - " 'tr_744_tr08044': 'ስለሆነ ም የ ከተማው አስተዳደር ና ህዝብ ከተማው ን በምን አቅጣጫ እንደሚያ ደሙት እያወ ቁም ነበር',\n", - " 'tr_745_tr08045': 'ዶክተር ነጋሶ ማን እንደሆኑ ይግለጹ ሉን ተብሎ ለ ቀረበላቸው ጥያቄ ነጋሶ የኦሮሞ ባህላዊ ሀይማኖት የ ፕሮቴስታንት እምነት ተጽእኖ ዎች ያሳደሩ በት ሰው ነው በ ማለት መልሰዋል',\n", - " 'tr_746_tr08046': 'በሌላ በኩል ፕሬዚዳንት ኢሳያስ በ አሜሪካ ቆይታቸው ከ ፕሬዚዳንት ክሊንተን ጋር ለ መገናኘት ያደረጉት ጥያቄ ውድቅ እንደሆነ ባቸው ተ ገልጿ ል',\n", - " 'tr_747_tr08047': 'ጩኸታቸው በ ሆስፒታል የ ተኙ ትን ሌሎች ህሙማን ያስ በ ረግ ጋል',\n", - " 'tr_748_tr08048': 'በ ኢትዮጵያዊ ነታቸው የሚ ኮሩ ና በ ኢትዮጵያ አንድነት የሚያምኑ ነበሩ',\n", - " 'tr_749_tr08049': 'ለንደን ና ኒውዮርክ በ ኢትዮጵያዊያ ን ተቃዋሚ ሰልፈኞች ተጥለቀለቁ',\n", - " 'tr_750_tr08050': 'አንተነህ አላምረው በ ፕሮፌሽናል ነት በ መጫወት በ ታሪክ የመጀመሪያ ው ኢትዮጵያዊ ተጫዋች ሆነ',\n", - " 'tr_751_tr08051': 'ኢትዮጵያ ሰባ ሺህ ወታደሮ ቿን አሰናብ ታለች',\n", - " 'tr_752_tr08052': 'በ ኤርትራ የተለየ መንግስት ተቋቋመ',\n", - " 'tr_753_tr08053': 'ጥያቄ ው የዛሬ ሰላሳ አመት ገደማ ለጋ የ ኢትዮጵያ ተማሪዎች እንቅስቃሴ ን አ ና ቆረ አ ና ከሰ አ ራኮተ',\n", - " 'tr_754_tr08054': 'ያለ አንዳች ጥያቄ ከተ ባለ ደግሞ ያከራ ክራል',\n", - " 'tr_755_tr08055': 'እርምጃ ተወስዶ ባቸዋል ነበር የ ሚባለው',\n", - " 'tr_756_tr08056': 'ይህ ለምን እንደሆነ እንደሚ ከተለው እን የ ው',\n", - " 'tr_757_tr08057': 'ሻእቢያ ግን የኤርትራ ሀብት ለ ኤርትራውያን ብቻ የ ኢትዮጵያ ን ሀብት ግን ፖሊሲ ሳያ ግደን እን ጠቀም በት ባይ ነው',\n", - " 'tr_758_tr08058': 'ኤርትራ ነጻ አገር ና ት ተባለች',\n", - " 'tr_759_tr08059': 'ሀቁ ን ግን ታሳሪዎቹ ም እኛ ም እናውቀ ዋለን',\n", - " 'tr_760_tr08060': 'እንዲሁም ተገቢ የ ገንዘብ ድጋፍ እንዲ ያገኙ በ ብዙሀን መገናኛ ዎች ያለምን ም ገደብ እንዲ ጠቀሙ ና ከ ህዝብ ጋር እንዲ ገናኙ አድርጉ',\n", - " 'tr_761_tr08061': 'መንግስት በ ኢንቨስትመንት እንቅስቃሴ ላይ የ ተከሰቱ የ ፖሊሲ ና የ አሰራር ግድፈቶች ን ለ ማስወገድ ርምጃ መውሰዱ ከ ግሉ ኢንቨስትመንት ፍሰት የ ሚገኘው ን ድርሻ እንደሚያ ሻሽለው ም ገለጹ',\n", - " 'tr_762_tr08062': 'እኔ ግን ነፍጠኛ ም መድፈኛ ም እንዳል ሆ ኩኝ ል ነገራችሁ ብዬ እንጂ ፖለቲከኛ ሳል ሆን አሽሙረኛ ነኝ ብዬ እናንተ ን ላሳምናችሁ አል ሞክር ም',\n", - " 'tr_763_tr08063': 'ኮሎኔል በዛብህ ጴጥሮስ የ አማራጭ ሀይሎች ሊቀመንበር የ ዶክተር በየነ ጴጥሮስ ወንድም መሆናቸው ተያይዞ ተ ገልጿ ል',\n", - " 'tr_764_tr08064': 'የ መስተዳድሩ መግለጫ ከተማዋ ስር ነቀል ለውጥ እንደሚ ያስፈልጋት ገልጾ ህዝቡ በዚህ እንዲ ሳተፍ ቢ ጠይቅ ም ጊዜያዊ መስተዳድሩ የ መዋቅር ለውጡ ን ያስፈጽማል ተብሎ አይጠበቅ ም',\n", - " 'tr_765_tr08065': 'ለወደፊቱ በሚ ዘጋጀው ጉባኤ የ በ ኩሌን ሀሳብ ለ ካድሬው ይዤ አቀርባ ለሁ',\n", - " 'tr_766_tr08066': 'ኤኤፍፒ ከ ሶስት ሺ በላይ የኤርትራ ኩናማ ዎች ወደ ኢትዮጵያ ሸሽተው በ መግባት የኤርትራ ሰራዊት በ ሀይል እየ መለመላቸው ነው ሲሉ ውንጀላ ሰንዝ ረዋል',\n", - " 'tr_767_tr08067': 'ዋናው አላማችን አባላ ቶቻችን ን በ ስፖርቱ ተሳታፊ እንዲሆኑ ና ለ ሀገራችን ስፖርት የ በኩላቸው ን አስተዋጽኦ እንዲ ያበረክቱ እንጂ እንደ አንዳንድ ክለቦች ድርጅት ን ለ ማስተዋወቅ አይደለም',\n", - " 'tr_768_tr08068': 'በ ማጠቃለያ ውም በ እርዳታ አ ሰባሰቡ ወቅት ኢህአዲግ በ በጐ አይ ን የማ ይመለከታቸው ና በ አሸባሪነት ጠርጥሬ ያ ቸዋለሁ የሚ ላቸው ኢትዮጵያውያ ን የ ህግ ታራሚዎች ሳይ ቀሩ በ እርዳታው ተሳትፎ ማድረጋቸው ን አመልክ ቷል',\n", - " 'tr_769_tr08069': 'የ ኦክስፋም ኢንተርናሽናል ልኡካን ቡድን ን በ መወከል የ ካናዳ ኦክስፋም ዳይሬክተር ሚስ ጆ አን እንደ ተናገሩት አባል ድርጅቶች ችግሩ ን በ ቅንጅት ለ መቅረፍ የ ተቻላቸውን ጥረት ያደርጋሉ',\n", - " 'tr_770_tr08070': 'በ ተለያዩ የ ሀገራችን ክፍሎች ውስጥ እንግልት ድብደባ ግድያ ና እስራት ተፈጸመባቸው ያ ላቸውን የ አማራው ተወላጆች ን ስ ም ዝርዝር አውጥ ቷል',\n", - " 'tr_771_tr08071': 'በ አደባባይ ም ባሪያዬ ነው እያ ልክ አት ሟገት',\n", - " 'tr_772_tr08072': 'የ ውጪ ጋዜጠኞች ወደ ውጊያ ግንባር እንዲ ሄዱ ተፈቀደ',\n", - " 'tr_773_tr08073': 'አባቶቻችን እንደሚ ተርቱ ት የ እንጨት ምንቸት እራሱ አይድ ን በ ውስጡ ም ያለውን አ ያድኑ ብለዋል',\n", - " 'tr_774_tr08074': 'እራሳቸው ን ወደ ገዢ መደብ ያ ሸጋገሩ ስለሆነ ለዚህ አዲስ መደባዊ ጥቅማቸው ሲሉ ነው',\n", - " 'tr_775_tr08075': 'በ ድርጅት ማእከላዊ ኮሚቴ ውስጥ ምልአተ ጉባኤ በሚ ታጣበት ጊዜ መ ኬድ ያለበት ወደ ኦዲት ኮሚሽን ነው',\n", - " 'tr_776_tr08076': 'የ ጦማር ዘጋቢ ትናትና ተዘዋው ሮ የ ተመለከታቸው ን ሁኔታዎች እንደሚ ከተለው ገልጿ ል',\n", - " 'tr_777_tr08077': 'ጋዜጦቹ በተለይ በውጭ አገር ያሉ ኢትዮጵያውያ ን ን በ ማስተባበር በኩል ትልቅ ሚና ተጫውተ ዋል',\n", - " 'tr_778_tr08078': 'ፎረሙ በ ዋሽንግተን ለ ስድስት ቀናት በሚ ያደርገው ሁለተኛ ስብሰባ ላይ ሀያ ኢትዮጵያውያ ን ተ ጋብዘው በ መካፈል ላይ ናቸው',\n", - " 'tr_779_tr08079': 'ሰብ ላቸው ረክ ሶ የሚ ገዛቸው እያ ጡ ነው በ ማለት ከ ገለጹ በኋላ እኛ ጥያቄ ያችን ና ተቃውሟችን የ ደህንነት ና የ ዋስትና ጥያቄ ነው',\n", - " 'tr_780_tr08080': 'በ ስደት ያሉት ተማሪዎች መምህራኖ ቻቸውን አድር ባዮች ሲሉ መኮነናቸው ንም መረዳት ተችሏል',\n", - " 'tr_781_tr08081': 'ምርጥ የ ኢትዮጵያ ልጆች ተሰኙ',\n", - " 'tr_782_tr08082': 'የ ኢትዮጵያ የ ታሪክ ጥበቃ ክፍል ና የ ኢትዮጵያ ቱሪስት ኮሚሽን ለዚህ ጥንታዊ ና ታሪካዊ ቦታ ና መስጊድ ትኩረት ሊሰጥ እንደሚ ገባ ለማስታወስ እንወዳ ለ ን',\n", - " 'tr_783_tr08083': 'በ ማእረጉ ማግኘት የሚ ገባቸው ን የ ደሞዝ ጭማሪ እና እድገት አግኝተ ዋል',\n", - " 'tr_784_tr08084': 'የ ተጫዋቹ ጤንነት ሙሉ ለ ሙሉ ጥሩ እንደሆነ ዶክተሩ ገልጸው ላቸው ለ ሮናልዶ ም ከ እንግዲህ ጥሩ እረፍት እንደሚ ያስፈልገው ይ ነገረ ዋል',\n", - " 'tr_785_tr08085': 'ቦሎኛ ባለፈው ሳምንት ጁቬንትስ ን ሶስት ለ ዜሮ በሆነ ሰፊ ውጤት አሸን ፏል',\n", - " 'tr_786_tr08086': 'ይህን አስተያየት የሚሰጡ ወገኖች ስለ ሙያው ም ንም እውቀት ና ግንዛቤ የ ሌላቸው ናቸው',\n", - " 'tr_787_tr08087': 'ሁለተኛው ከ ስፖርት ሚኒስቴሩ ፕሮጀክት ጋር በ እግር ኳስ እድገት ላይ ያደረግ ነው ስራ ነው',\n", - " 'tr_788_tr08088': 'ወዲያ ው ጣልያኖች ፔናልቲ ሊ ስቱ ችለዋል ና',\n", - " 'tr_789_tr08089': 'እስካሁን ኢትዮጵያ ወደ አንድ መቶ ሺ የሚሆኑ የ ሶማሊያ ስደተኞች ን በ ማስተናገድ ላይ ትገኛ ለች',\n", - " 'tr_790_tr08090': 'ከ ሞት የተ ረፍ ን አራት ወንድማማቾች ታፍ ነናል እስከ ሚቀጥለው ቀጠሮ ላንደር ስ እንችላ ለ ን ልን ሞት እንችላ ለ ን',\n", - " 'tr_791_tr08091': 'ግም ታችን ግን ትክክል ሆኗል',\n", - " 'tr_792_tr08092': 'ያኛው ቡድን ትራዲሽና ሊስት ነው',\n", - " 'tr_793_tr08093': 'እንግዲህ ደደቢቶች አብዮታዊ ዲሞክራሲ ን አንግ በ ው ብሄርተኝ ነትን አ ራምደው ኢምፔሪያሊዝም ን ሸውደው እጣ ፋንታ ቸው አስራ ሰባት አመት የ ዳ ከርን በትን ርእዮት በ ኦሞ ከ ማጽዳት አያልፍ ም',\n", - " 'tr_794_tr08094': 'ምክንያቱ ም የምን ጋራ ቸውን ግቦች የምናከብራቸው ን ብሄራዊ እ ሴቶች ተገንዝበ ን ተገንዝበ ው ለ ተፈጻሚ ነታቸው ፈቃደኞች መሆናችን ን እስካሁን አላ ረጋገጥ ንም',\n", - " 'tr_795_tr08095': 'ብቻ ሰዎቹ ን አስሮ ማቆየት ፈልጓል',\n", - " 'tr_796_tr08096': 'ኤርትራ የ አድኑ ኝ ጩኸት እያስ ተጋባች ነው',\n", - " 'tr_797_tr08097': 'ዜናው አክሎ እንደ ገለጸው የኤርትራ ተወላጆች የ ተጠቀሱት ን ንብረቶች ና እንስሳት እንዳያ ሸጋግሩ ቢ ታገዱ ም ንብረታቸው ን ሸጠው በ ገንዘብ መልክ ይዘው ለ መውጣት ግን አልተ ከለከሉ ም',\n", - " 'tr_798_tr08098': 'ሲፒጄ ዘንድሮ ም መለስ ዜናዊ ን የ ፕሬስ ጠላት አ ላቸው',\n", - " 'tr_799_tr08099': 'በ ኢትዮጵያ ያለው የ ሀይማኖ ቶች መቻቻል እንደ ምሳሌነት እንደሚ ጠቀስ ተጠቆመ',\n", - " 'tr_800_tr08100': 'ማ ንም እንደሚ ያውቀው ሮናልዶ አለ',\n", - " 'tr_801_tr09001': 'ነገር ግን በ ሁሉም መስክ ተቀባይነት ያለው የ ኮምፒውተር ቴክኖሎጂ ነው',\n", - " 'tr_802_tr09002': 'በ አሜሪካ ዋሽንግተን ና ኒውዮርክ በ ኬንያ ናይሮቢ ና በ ታንዛኒያ ዳሬሰላም በ ሽብርተኝነት የተ ፈጸሙት ን ጥቃቶች ም እንደሚ ያወግዙ ት መሪዎቹ ባሳለፉ ት ውሳኔ አመልክ ተዋል',\n", - " 'tr_803_tr09003': 'በ ሚስተር ኬን ዞ ኦ ሾማ የተ መራው የ ተመድ የ ልኡካን ቡድን አዲስ አባ ገባ',\n", - " 'tr_804_tr09004': 'በ ጅቡቲ ኢትዮጵያውያ ን ሹፌሮች ግልምጫ ና ቁጣ እንዳይደርስ ባቸው በ ፈገግታ ና በ እንግዳ ተቀባይነት ጸባይ ተ ቀበሏቸው ሲሉ ኢትዮጵያውያ ን ባለስልጣናት ጅቡቲ ያውያን ባለስልጣናት ን አ ሳሰቡ አሉ',\n", - " 'tr_805_tr09005': 'ዳንኤል ና ስለ ስቱ ደቂቅ ደግሞ በ ጾም ትምህርት ን ጥበብ ን እውቀት ን ማስተዋል ን አግኝተ ዋል',\n", - " 'tr_806_tr09006': 'ሶስቱ ሊቃነ ጳጳሳት በ ሲኖዶሱ ጉባኤ እንዳይ ቀመጡ እየተ ዶ ለተ መሆኑ ተነገረ',\n", - " 'tr_807_tr09007': 'በ አፍሪካ አንድነት ድርጅት አደራዳሪ ነት የ ተዘጋጀው የ ስምምነት ማእቀፍ በ ኢትዮጵያ ና በ ኤርትራ ተቀባይነት ማግኘቱ እንደሚ ደገፍ ፕሬዚደንት ክሊንተን አስ ታወቁ',\n", - " 'tr_808_tr09008': 'ጠንክረን ስለምን ታገ ላችው ም የ ጥቃታቸው ን ኢላማ እንደሆ ን ን እናውቃለን',\n", - " 'tr_809_tr09009': 'አመት አልፎ አመት በ ተተካ ቁጥር ፓትርያርኩ ና ተቃውሞ ተለያይ ተው አያውቁ ም',\n", - " 'tr_810_tr09010': 'ምክንያቱ ም ኢሳያስ የ ኢትዮጵያ ን ምድር ለቀው እንዲ ወጡ ከ መጨነቅ ይልቅ ሱዳን ገብተው አልቱራቢ ን እንዴት ሊ ያጠፉ ላቸው እንደሚ ችሉ ነው የሚያ ልሙት',\n", - " 'tr_811_tr09011': 'ሁለት ኢትዮጵያውያ ን አርቲስቶች የ ዩኤስ ፌሎው ሺፕ አሸናፊ ሆኑ',\n", - " 'tr_812_tr09012': 'አቶ ተወልደ እኔ ትናንት ስላል ነበርኩ ኦዲት ኮሚሽን ትናንት ያቀረበ ው ሀሳብ ም ን እንደሆነ እንዲ ገለጽ ልኝ እፈልጋ ለሁ አሉ',\n", - " 'tr_813_tr09013': 'ተመላሽ ኢትዮጵያውያ ን ስለሚያ ስገቧቸው ቁሳቁስ የ ተሻሻለ መመሪያ ወጣ',\n", - " 'tr_814_tr09014': 'ሁለተኛው ላቁኦተ ለ አደላዳይ ራቁኦ ተ ይላሉ አደላዳይ እሳቸው ናቸው',\n", - " 'tr_815_tr09015': 'የ ኢትዮጵያ ብሄራዊ የ እግር ኳስ ቡድን ን እንዲ ያሰለጥኑ የተመረጡት ሚስተር ስኮቺቭ ባለፈው ቅዳሜ አዲስ አበባ ገብ ተዋል',\n", - " 'tr_816_tr09016': 'ለ ሜዳይ ና ሪቫ ን ኮሚቴ ቅርብ ከ ሆኑ ወገኖች የተገኘው መረጃ እንደሚ ያስረዳ ው አንድ የ አገልግሎት ሪቫ ን ማለት አምስት የ አገልግሎት አመታት ን ይወ ክላል',\n", - " 'tr_817_tr09017': 'እኛ በ ፓርላማው የተቀ መጥነው እ ኮ ተቃዋሚዎች ን ወክለ ን እንጂ የ ኢህአዴግ እጩዎች ሆነ ን አደለ ም',\n", - " 'tr_818_tr09018': 'የ ኢትዮጵያ መንግስት ብሄራዊ ፓሊሲ ዎቹን ህግ ና የ ስደተኞች ስራ አመራር መዋቅሮቹ ን እንደ ገና በ መፈተሽ ና በ ማሻሻል ለ ኢትዮጵያ ስደተኞች የሚ ጠቅም አሰራር እንዲ ዘረጋ ተጠየቀ',\n", - " 'tr_819_tr09019': 'ይህን እኛ አንስተው ም ሀ ዜብ ዛሬ እንደ ፈለገች የምታ ሽክረ ክረው ድርጅት ና ክልል እንዳገኘ ች ማለት ነው',\n", - " 'tr_820_tr09020': 'ባንኩ ይህን ብድር ለግል ባንኮቹ የ ሰጠው የ ጥሬ ገንዘብ ችግራቸው ን እንዲ ቋቋሙ ለ መርዳት ነው',\n", - " 'tr_821_tr09021': 'ከ ኢትዮጵያ ወታደሮች ጋር እንዋጋ ለ ን',\n", - " 'tr_822_tr09022': 'ሱዳን ይኖሩ የነበሩ አራት መቶ ሰባ አምስት ኢትዮጵያውያ ን ስደተኞች ጐንደር ገቡ',\n", - " 'tr_823_tr09023': 'ኤም ቢ ሲ የ ሚባለው ና ከ ለንደን የሚ ተላለፈው ቴሌቪዥን ጣቢያ ባለፈው ቅዳሜ አል ከ ሊድ መጽሄት ን ጠቅሶ እንደ ዘገበው የኤርትራ ተቃዋሚዎች በ ፕሮፖጋንዳ ብቻ የተ ገደቡ አይ ሆኑ ም',\n", - " 'tr_824_tr09024': 'የተገኘው ዜና እንደሚ ያስረዳ ው የ ወረዳው ፖሊሶች ወደ ተጠቃሹ ቦታ እንዲ መጡ ህዝቡ አስቀድሞ መረጃ ደርሶ ት ነበር',\n", - " 'tr_825_tr09025': 'የ ኢትዮጵያ ን አንድነት እንደ ገና መመለስ ይቻላል',\n", - " 'tr_826_tr09026': 'እነሱ ኢትዮጵያውያ ን መንግስቱ ን በ ጦር ወንጀለኛ ነት ማየት ይችላሉ',\n", - " 'tr_827_tr09027': 'በ ባህሬን የ ሀያ አመት ኢትዮጵያዊ ት ላይ የ ሞት ፍርድ ተፈረደ ሁለቱ ም ኢትዮጵያዊ ድምጹ ን ሊያ ሰማ ይገባል',\n", - " 'tr_828_tr09028': 'ምክንያቱ ስውር ቢሆን ም ተማጽ ኗቸው ን በ ቅን መንፈስ ለ መመለስ ሳይ ስማሙ ቀሩ',\n", - " 'tr_829_tr09029': 'ጸጥ እንድት ል አስ ጠንቅቆ አስገድዶ ደፈራት',\n", - " 'tr_830_tr09030': 'ግን ዘንድሮ ራሱ ስንት እንዳ ገባሁ አላ ቀውም',\n", - " 'tr_831_tr09031': 'በ እውነት ነው የ ም ልህ እሱ እውነተኛ ፕሮፌሽናል ስራው ን አክባሪ ነው',\n", - " 'tr_832_tr09032': 'እንዲያ ውም እኛ ስህተት አድርገ ናል',\n", - " 'tr_833_tr09033': 'ረጅም መንገድ እንዲ ጓዝ የሚ ያስችለው ችሎታ አለ ው',\n", - " 'tr_834_tr09034': 'በ ሊቢያ ው መሪ ስ ም ማለት ነው',\n", - " 'tr_835_tr09035': 'ቦታው እ ኮ ከባድ ነው',\n", - " 'tr_836_tr09036': 'አቶ ጸሀዬ ከ ችሎታቸው ና ከ እ ው ጥቀ ታቸው በላይ የ ተሰጣቸው ን ሀላፊነት እንዲ ወጡ ውክልናው ን የ ሰጠው የ ትግራይ ስፖርት ኮሚሽን ነው',\n", - " 'tr_837_tr09037': 'በተለይ ረዳት አርቢትሮች የሚፈጽሟቸው ስህተቶች የ ጨዋታው ው በት እንዳ በላሹት በ ተመልካቹ አንደ በት ሲ ነገር ተደም ጧል',\n", - " 'tr_838_tr09038': 'የ ኢትዮጵያ መንግስት በ ነጻ ቢያሰ ና ብተው ወንጀል የ ተፈጸመባቸው ቤተሰቦች ተቃውሟቸው ን ሊ ያቀርቡ ይችላሉ',\n", - " 'tr_839_tr09039': 'ለ መስሪያ ቤታቸው ይህን ምክንያት ያቅርቡ እንጂ ዳግመኛ ወደ ኢትዮጵያ እንደማይ መለሱ ለሚ ያቀርቧቸው ወገኖች በ ሚስጥር ገልጸው ነበር',\n", - " 'tr_840_tr09040': 'ግብ ጠባቂ ው የሚ ደነቅ ነው',\n", - " 'tr_841_tr09041': 'ኤሲ ሚላን ሀያ አምስት ኢንተር ሚላን ሀያ አራት ሮማ ላዚዮ ሀያ ሰባት ቦሎኛ ና ጆ ቪ ሀያ አንድ ነጥብ አ ላቸው',\n", - " 'tr_842_tr09042': 'የመጀመሪያ ውን ጐል በረኛው ሲ ተፋ ደርሶ ያገባ ሲሆን ሁለተኛ ዋን ግን ተከላካዮቹ ን አብዶ ሰርቶ ነው ያገባ ው',\n", - " 'tr_843_tr09043': 'የ ኢትዮጵያ ጦር ማክሰኞ እ ለት የ ሶማሊያ ሁለት ከተሞች ን ያዘ',\n", - " 'tr_844_tr09044': 'ኬንያ ወደ ኢትዮጵያ ድንበር ሰራዊቷ ን ላከች',\n", - " 'tr_845_tr09045': 'አባቱ የ ፕሮቴስታንት እምነት ቄስ ነበሩ',\n", - " 'tr_846_tr09046': 'አሜሪካ ዲፕሎማቶ ቿ ወደ ኢትዮጵያ እንዲመለሱ ወሰነች',\n", - " 'tr_847_tr09047': 'ተማሪዎቹ እንደሚ ናገሩት ምግብ በ ሰአቱ አይ ሰጣቸው ም',\n", - " 'tr_848_tr09048': 'እነሱ በ ባዶ እግራቸው መጥተው ዛሬ ባለ ማርቸዲስ ናቸው በ ቁምጣ መጥተው ዛሬ ሚሊ የ ነሮች ናቸው',\n", - " 'tr_849_tr09049': 'ሶማሊያ በ ኢትዮጵያ ላይ ማእቀብ እንዲ ጣል ጠየቀች',\n", - " 'tr_850_tr09050': 'ባ ሁኑ ወቅት አቶ ሰ ዬ ከ ታሰሩበት ክፍል ማ ንም ሰው እንደማያ ያቸው ምንጮቻችን አክለው ገልጸዋል',\n", - " 'tr_851_tr09051': 'ኢትዮጵያ ና ኤርትራ የ ሰራዊት ቅነሳ ለማድረግ እንቅስቃሴ እንደ ጀመሩ በ መንግስታቱ ድርጅት የ ኢትዮ ኤርትራ ልዩ ልኡክ አስ ታወቁ',\n", - " 'tr_852_tr09052': 'ዛሬ ያ መልካም ጉርብትና ና ትስስር ታሪክ ሆነ',\n", - " 'tr_853_tr09053': 'ዛሬ ም ልክ እንደ ትናንቱ እያ ና ቆረ እያ ና ከሰ እያ ራኮተ ነው',\n", - " 'tr_854_tr09054': 'አንድ ኢትዮጵያዊ ልጅ ዎ ሊ ጠይቅ ዎት መጥቶ ነበር',\n", - " 'tr_855_tr09055': 'ኢህአፓ ዎች ሊ ገደሉ ሲ ሄዱ እየ ዘመሩ እንደ ሄዱ ነገሩኝ',\n", - " 'tr_856_tr09056': 'ያረፈ በት ምክንያት ከ ወዲያ ከ ኤርትራ ሚጐች ወጥ ተዋል ተብሎ ነው',\n", - " 'tr_857_tr09057': 'በ ትግራይ ውስጥ ከ ባድመ ጀምሮ ደደቢት ን ጓል ደደቢት ን ሸራሮ ን ወሀ ደን በ ሙሉ እስከ መ ንጠባጠብ ያለውን ይይዛ ል',\n", - " 'tr_858_tr09058': 'ሰዎች ና ድርጅቶች ከ እነሱ ም ጋር የ ተያያዙ ፖሊሲዎች አላፊ ዎች ናቸው',\n", - " 'tr_859_tr09059': 'አዘጋጅ ኮሚቴው ለ ሪፖርተራችን እንደ ገለጸው ዝግጅቱ ን ከ ተለያዩ የ አሜሪካ ግዛቶች የሚ መጡ ኢትዮጵያውያ ን ይ ስተናገዱ በታል',\n", - " 'tr_860_tr09060': 'የ ሀገራችን ቁስል ም እንዲ ሽር ያደርጋሉ',\n", - " 'tr_861_tr09061': 'መንግስት በ ኢንቨስትመንት እንቅስቃሴ ላይ የ ተከሰቱ የ ፖሊሲ ና የ አሰራር ግድፈቶች ን ለ ማስወገድ ርምጃ መውሰዱ ከ ግሉ ኢንቨስትመንት ፍሰት የ ሚገኘው ን ድርሻ እንደሚያ ሻሽለው ም ገለጹ',\n", - " 'tr_862_tr09062': 'እኔ ግን ነፍጠኛ ም መድፈኛ ም እንዳል ሆ ኩኝ ልንገራችሁ ብዬ እንጂ ፖለቲከኛ ሳል ሆን አሽሙረኛ ነኝ ብዬ እናንተ ን አ ላሳምናችሁ አል ሞክር ም',\n", - " 'tr_863_tr09063': 'ኮሎኔል በዛብህ ጴጥሮስ የ አማራጭ ሀይሎች ሊቀመንበር የ ዶክተር በየነ ጴጥሮስ ወንድም መሆናቸው ተያይዞ ተ ገልጿ ል',\n", - " 'tr_864_tr09064': 'የ መስተዳድሩ መግለጫ ከተማዋ ስር ነቀል ለውጥ እንደሚ ያስፈልጋት ገልጾ ህዝቡ በዚህ እንዲ ሳተፍ ቢ ጠይቅ ም ጊዜያዊ መስተዳድሩ የ መዋቅር ለውጡ ን ያስፈጽማል ተብሎ አይጠበቅ ም',\n", - " 'tr_865_tr09065': 'ለወደፊቱ በሚ ዘጋጀው ጉባኤ የ በ ኩሌን ሀሳብ ለ ካድሬው ይዤ እ ቀር ባለሁ',\n", - " 'tr_866_tr09066': 'ኤኤፍፒ ከ ሶስት ሺ በላይ የኤርትራ ኩናማ ዎች ወደ ኢትዮጵያ ሸሽተው በ መግባት የኤርትራ ሰራዊት በ ሀይል እየ መለመላቸው ነው ሲሉ ውንጀላ ሰንዝ ረዋል',\n", - " 'tr_867_tr09067': 'ዋናው አላማችን አባላ ቶቻችን በ ስፖርቱ ተሳታፊ እንዲሆኑ ና ለ ሀገራችን ስፖርት የ በኩላቸው ን አስተዋጽኦ እንዲ ያበረክቱ እንጂ እንደ አንዳንድ ክለቦች ድርጅት ን ለ ማስተዋወቅ አይደለም',\n", - " 'tr_868_tr09068': 'በ ማጠቃለያ ውም በ እርዳታ አ ሰባሰቡ ወቅት ኢህአዲግ በ በጐ አይ ን የማ ይመለከታቸው ና በ አሸባሪነት ጠርጥሬ ያ ቸዋለሁ የሚ ላቸው ኢትዮጵያ ን የ ህግ ታራሚዎች ሳይ ቀሩ በ እርዳታው ተሳትፎ ማድረጋቸው ን አመልክ ተዋል',\n", - " 'tr_869_tr09069': 'በ የመን ግዛቶች ውስጥ ም ሀያ ቅርንጫፍ ጽህፈት ቤቶች ማቋቋሙ ን ተናግረ ዋል',\n", - " 'tr_870_tr09070': 'ስልጣን ኦጋዴን ን ለማስ ገንጠል ለሚ ሹ ወገኖች ሊሰጥ ነው',\n", - " 'tr_871_tr09071': 'እኔ ና እናንተ መገናኛ የ ለ ንም',\n", - " 'tr_872_tr09072': 'የቤተ ክርስቲያን ሀብት እንዳይ ባክን ስልት ተ ቀየሰ',\n", - " 'tr_873_tr09073': 'ስለዚህ በ አር እስቴ እንደ ገለጽኩ ት ሰሚ ጆሮ ያለው ይስማ አስተዋይ አእምሮ ያለው ም ያስተውል እ ላለሁ',\n", - " 'tr_874_tr09074': 'ካድሬው እነዚህ ን ውይይቶች ሊ ወያይ ባቸው ይገባል',\n", - " 'tr_875_tr09075': 'ካለ ፍርድ ቤት ውሳኔ መስሪያ ቤቶቻችን ን ለ መፈተሽ ና ለ ማሸግ ፖሊስ ና ደህንነት ን አሰማር ተዋል',\n", - " 'tr_876_tr09076': 'ሪፖርተራችን ያ ነጋገራቸው ተማሪዎች እንደ ገለጹት ወደ ሰንዳፋ ፖሊስ ማሰልጠኛ ስን ገባ በ ፖሊሶች ላይ የሚ ታየው እልክ ና ቁጭት ነበር',\n", - " 'tr_877_tr09077': 'የ ትግራይ ነዋሪ ቁጣው ን እየ ገለጸ ነው',\n", - " 'tr_878_tr09078': 'አረጋሽ የ ባንክ አካውንት እንዲ ያስረክቡ ተጠየቁ',\n", - " 'tr_879_tr09079': 'የ ተማሪዎቹ ተወካዮች ከ ኦሮሚያ ባለስልጣናት ጋር አምስት ሰአት የፈጀ ውይይት ማድረጋቸው ታውቋል',\n", - " 'tr_880_tr09080': 'ወይዘሮዋ ም በ አምባሳደር ነት ሊ ሾሙ ነው የሚ ል ፍንጮች ም እየ ተደመጡ ነው',\n", - " 'tr_881_tr09081': 'ዶክተር ታዬ ወልደሰማያት አውሮፓ እያሉ ጽፈት ቤትዎ እየ ተፈተሸ ነው',\n", - " 'tr_882_tr09082': 'ወንዶች ና ሴቶች እኩል ሳይ ሆኑ ተደጋጋፊ ዎች ናቸው',\n", - " 'tr_883_tr09083': 'አንዳንዶቹ ም የ ብሄራዊ ውትድርና ስልጠና የ ወሰዱ ናቸው',\n", - " 'tr_884_tr09084': 'አሰልጣኙ ም በ ጉዳዩ ማብራሪያ ሲሰጡ ዋናው ትኩረ ቴ የ ሮናልዶ ን ተክለ ሰውነት ማስተካከል ነው ብለዋል',\n", - " 'tr_885_tr09085': 'ላዚዮ እንዲ ሁ ፕሮቲ ን ን በ ው ሰት ለ ሬጂ ያ ና ክለብ ሰጥ ቷል',\n", - " 'tr_886_tr09086': 'ማሸነፍ ንና መሸነፍ ጠንቅ ቄ አውቀ ዋለሁ',\n", - " 'tr_887_tr09087': 'ሶስተኛው በ ታዳጊ ፕሮጀክቶች ላይ ያተኮረ ነበር',\n", - " 'tr_888_tr09088': 'ፈረንሳይ ውስጥ የሚ ጫወተው የ ኮትዲቭዋር ኢብራሂም ባካዮኮ ያለው ፐርፎርማንስ ከ እ ለት ወደ እ ለት ልዩ እየ ሆነ ይገኛል',\n", - " 'tr_889_tr09089': 'በ እለቱ ተጋባዥ ተናጋሪዎች ዶክተር ማሞ ሙጬ ና ዶክተር ግርማ ይ ስለ ኤርትራ ና ኢትዮጵያ የፖለቲካ ና የ ኢኮኖሚ ውስብስብ ችግሮች በስፋት አብራር ተዋል',\n", - " 'tr_890_tr09090': 'ፖሊስ የተለያዩ ክሶች ን ሊያመጣ ይችላል',\n", - " 'tr_891_tr09091': 'የ ዴር ሱልጣን ገዳም የ ባለቤትነት ጥያቄ ግብጽ ን ኢትዮጵያ ንና እስራኤል ን እያ ነታረ ከ ነው',\n", - " 'tr_892_tr09092': 'ምክንያቱ ም እነሱ ም እራሳቸው እንቅ ሳቄ ሳችን ተገድ ቧል ግንኙነታችን ተዳክ ሟል እያሉ ነው',\n", - " 'tr_893_tr09093': 'ገንዘብ ሲ ያዋጡ እጅ ከፍ ን ጅ የተያዙ ና በ ስለላ ስራ የተሰማሩ የኤርትራ ዜጐች እየ ተያዙ ወደ ሀገራቸው ሊ ባረሩ ነው',\n", - " 'tr_894_tr09094': 'ከዚህ በኋላ ነው እነዚህ ትሮትስኪ ን ያጠፉ ለትን አብዮተኞች በሌላ ስልት የ ዞረ ባቸው',\n", - " 'tr_895_tr09095': 'ታሳሪዎቹ ም ወደ ምርመራ ማስተባበሪያ እስር ቤት ተመለሱ',\n", - " 'tr_896_tr09096': 'ከርሞ ጥጃ አድሮ ቃሪያ ነን',\n", - " 'tr_897_tr09097': 'ከ ኢትዮጵያ የተለያዩ ሸቀጦች ጭነው ወደ ኤርትራ ይጓዙ የነበሩ በመቶ ዎች የሚ ቆጠሩ ካሚዮኖች በ ራማ ና ዛላንበሳ በሮች እንደ ተ ኮለኮሉ ናቸው',\n", - " 'tr_898_tr09098': 'ለ ኛ የ ጥንት የ ጠዋቱ የ አባቶቻችን ባንዲራ ያለው የ ቃል ኪዳን አርማ ችን ነው',\n", - " 'tr_899_tr09099': 'በ ኢትዮጵያ ና በ ቻይና መካ ካል ያለውን ወዳጅነት የሚ ያጠናክር ስምምነት ተፈረመ',\n", - " 'tr_900_tr09100': 'ኤቨርተን ደግሞ እኔ የ ም ወደው ክለብ ነው',\n", - " 'tr_901_tr10001': 'ብዙ ነገሮች ን ማገናዘብ ይፈልጋል',\n", - " 'tr_902_tr10002': 'ተሳታፊ ዎቹ በ ውይይቱ ላይ እንደ ተናገሩት እንደ ማንኛውም አገር ሁሉ በ ኢትዮጵያ ለ ባለስልጣናት የሚ ከፈለው ክፍያ ከ ገበያ ዝቅ ያለ ነው',\n", - " 'tr_903_tr10003': 'የ ፖሊዮ ቫይረስ እንዳለ ባቸው በ ታወቁ በ እነዚህ አካባቢዎች የ ጤና ባለሙያዎች የ ቤት ለ ቤት ክትባት ለ መስጠት ለ ሚያደርጉት እንቅስቃሴ እንደሚ ያግዝ ገልጸዋል',\n", - " 'tr_904_tr10004': 'ም ነው አሽሙረኛ ው ስለ ሽያጭ ና ስለ ዱቤ ማውጋት አበዛ',\n", - " 'tr_905_tr10005': 'እንዲሁም የ ቀደሙ ነገስታት ና መኳንንት አገር የሚ ያስተዳድሩ በት ህሊናቸው ማስተዋል ን ጥበብ ን እንዳ ያጣ በ ጾመ ፍልሰታ ወደ እመቤታችን ቀርበው የሚ ማጸኑ በት ነው',\n", - " 'tr_906_tr10006': 'ሀሰን አልቱራቢ ወደ ስራቸው እንዲመለሱ የ ሱዳን ፓርላማ ማስ ገደዱ ታወቀ',\n", - " 'tr_907_tr10008': 'የበለጠ የ ጥ ፈት መልእክተኞች ን ለ ማጥፋት እንድን ተጋ ያደርገ ናል',\n", - " 'tr_908_tr10009': 'የ ኢትዮጵያ ተዋጊ አውሮፕላኖች አብራሪዎች ራሺያ ኖች ነበሩ',\n", - " 'tr_909_tr10010': 'ኤርትራ ን አውግዘ ው ኢትዮጵያ ን ከ ደገፉ አገሮች ም ጋር ተደ ባለቁ',\n", - " 'tr_910_tr10011': 'ሱዳን የ ኢትዮጵያ ዲፕሎማሲ ያዊ ውክልና ወደ አምባሳደር ደረጃ እንዲ ያድግ ጠየቀች',\n", - " 'tr_911_tr10012': 'ስለዚህ ትናንት የተባለ ውን ማወቅ እ ፈለጋ ለሁ',\n", - " 'tr_912_tr10013': 'በውጭ አገር እንዳሉ የሚ ሞቱ ኢትዮጵያውያ ን ህጋዊ ወራሾች ም የሟቾ ቹ መብቶች እንዲ ጠበቅ ላቸው መመሪያው ያዛል',\n", - " 'tr_913_tr10014': 'ሶስተኛው ላቁኦተ ለ እኔ ራቁኦ ተ ይላሉ እሳቸው እሳቸው ናቸው',\n", - " 'tr_914_tr10015': 'ኢትዮጵያ ቡና በ ብርሀን ና ሰላም ሶስት ለ አንድ ተረ ቷል',\n", - " 'tr_915_tr10016': 'እነ ኩማ ደመቅሳ ስ ልኮ ቻቸውን ተነጠቁ',\n", - " 'tr_916_tr10017': 'ጄኔራሎች በ ጠክለይ ሚንስትር ቢሮ ተሰብስ በዋል',\n", - " 'tr_917_tr10018': 'ቢል ጌት ስ ለ ኢትዮጵያ ሰባት ሚሊዮን ዶላር ለገሱ',\n", - " 'tr_918_tr10019': 'በ አንዱ ክስ ሰባት ተከሳሾች ያሉበት ነው',\n", - " 'tr_919_tr10020': 'መለስ ዜናዊ የ ሚኒስትሮች ሹም ሽር ሊያደርጉ ነው',\n", - " 'tr_920_tr10021': 'ስለሆነ ም ኤርትራውያን ወዳጆቻችን ናቸው',\n", - " 'tr_921_tr10022': 'ይህንኑ የ ገንዘብ ሽልማት በ ስጦታ ያበረከቱ ት የ ኢትዮጵያ ፈዴራላዊ ዴሞክራሲያዊ ሪፐብሊክ ፕሬዝ ደን ት ዶክተር ነጋሶ ጊዳዳ ናቸው',\n", - " 'tr_922_tr10023': 'የ አረብ ሊግ ኢትዮጵያ ን አወ ገዘ',\n", - " 'tr_923_tr10024': 'የ ሌሎች መንግስታዊ መስሪያ ቤቶች እንቅስቃሴ ም ተዳክ ሟል',\n", - " 'tr_924_tr10025': 'የ ሻእቢያ እብሪተኛ ቡድን የ ኢትዮጵያ ን ግዛት ዘልቆ ገብቷል',\n", - " 'tr_925_tr10026': 'ኤርትራ የ ማባረር ዘመቻ እንደምት ጀምር ገለጸች',\n", - " 'tr_926_tr10027': 'ከውጭ የ መጡ ስልሳ ኢትዮጵያውያ ን መለስ ን ሊያናግሩ ነው',\n", - " 'tr_927_tr10028': 'አባት ደግሞ አባት ናቸው ና ከ ሀገር ሽማግሌ ጋር መክረው ልጅቱ ን እንዲያ ገባት ተማመኑ',\n", - " 'tr_928_tr10029': 'ረዳት ቧንቧ ጠጋ ኝ ነው',\n", - " 'tr_929_tr10030': 'ገና ብዙ ጐል እንደማ ገባም አውቀ ዋለሁ',\n", - " 'tr_930_tr10031': 'እንደሚ ታወቀው ስብስቡ ከ ተለያየ የ ትውልድ ቦታ የተገኘ ነው',\n", - " 'tr_931_tr10032': 'እንዴ ም ን እያሉ ነው ኢንሴንቲቭ እ ኮ የሚ ታሰብ ላቸው በ የ ጨዋታው ና ባ ሸነፉ ቁጥር ነው',\n", - " 'tr_932_tr10033': 'ም ን እንደሚ ሰማው በ ደንብ አውቀ ዋለሁ',\n", - " 'tr_933_tr10034': 'በ መጀመሪያ ዎቹ አስራ ስድስት ጨዋታዎች ሶስት ብቻ ነው ያሸነፉ ት',\n", - " 'tr_934_tr10035': 'አሁን ትንሽ ከ እ ለት ወደ እ ለት እየ ተሻለኝ ነው',\n", - " 'tr_935_tr10036': 'ስለ እኚሁ የ ኢትዮጵያ ፉትቦል ፌዴሬሽን ምክትል ፕሬዚደንት የ ሁለት አመት የ ስልጣን ዘመን ብዙ ብዙ ተ ብሏል',\n", - " 'tr_936_tr10037': 'ፖሊሲው ን ተግባራዊ ለማድረግ እንዲ ያስችል የ ስፖርት ኮሚሽን ሙያተኞች ወደ ተለያዩ ክልሎች በ መዘዋወር መግለጫ ሰጥተዋል',\n", - " 'tr_937_tr10038': 'በ ወር ሶስት መቶ ዶ ራል ለ ሻምበል ማሞ ወልዴ ባለቤት ለ ወይዘሮ አበራሽ ኢንተርናሽናል ኦሎምፒክ ኮሚቴው እንደሚ ልክ ባገኘ ነው መረጃ ለማወቅ ች ለናል',\n", - " 'tr_938_tr10039': 'ባለፈው እትማችን ላይ የ ኢትዮጵያ አትሌቲክስ ፌዴሬሽን የ ፋይናንስ ና የ አስተዳደር ሀላፊ የሆኑት ወይዘሮ ፍቃደ ተገኝ ለ እረፍት ወደ አውሮፓ መጓዛቸው ን መግለጻ ችን አይ ዘነጋ ም',\n", - " 'tr_939_tr10040': 'ቀደም ሲል የ ፈጸማቸው ን ስህተቶች እንዳይ ደግም ና እርም ት እንዲያደርግ የሚ ገስጸው ሀይል ካልተገኘ ወደፊት ም በ ማወቅ ወይም ባለ ማወቅ ከ ስህተት የ ጸዳ ሊሆን አይችልም',\n", - " 'tr_940_tr10041': 'ጉዞው ን እንደ ያዘ ይቀጥላል ማለት ነው',\n", - " 'tr_941_tr10042': 'ሶስተኛ ዋ ኳስ ትራንሶ ች ኦፍሳይድ ብለው ሲ ወጡ ቴዎድሮስ አምልጦ በ መሄድ ያገኘው ን ኳስ መትቶ በ ማስቆጠር ሶስት ለ አንድ አሸንፈ ዋል',\n", - " 'tr_942_tr10043': 'የ ኢትዮጵያ የ መከላከያ ሰራዊት በ ቅርቡ የ ገብረ ሀሬ እና ቡርዳሀቦ ከተሞች ን በ ሶማሊያ ብሄራዊ ግንባር ስር የሚገኙት የ ጌዶ ከተሞች ን እንደሚ ያጠቃቸው ስጋቱ አለ',\n", - " 'tr_943_tr10044': 'አንዳንድ ለጋሾች የ ጦርነቱ ን ውጤት እየተ ጠባበቁ ናቸው',\n", - " 'tr_944_tr10045': 'ኢትዮጵያዊያ ን ን በ ብሄር ና በ ሀይማኖት ሳይ ለያይ ይወዳ ቸዋል',\n", - " 'tr_945_tr10046': 'ትምህርታቸው ን እየ ተዉ ለወጡት ተማሪዎች እልባት ባል ተበጀለት በዚህ ወቅት በ ዩኒቨርስቲ ው ለሚገኙ ተማሪዎች የሚ ሰጠው ትምህርት እንዲ ቀል ነው',\n", - " 'tr_946_tr10047': 'ዛሬ ጓደኛው ን ሲያስ ታ ም ም የ ዋ ለ በ ማግስቱ ተኝቶ ያቃስ ታል',\n", - " 'tr_947_tr10048': 'ሌሎቹ ም ያው የምና ያቸው ናቸው',\n", - " 'tr_948_tr10049': 'የ ፊታችን ቅዳሜ የ ቦስተን ነዋሪ ኢትዮጵያውያ ን ታላቅ ስብሰባ ያ ካሄዳ ሉ',\n", - " 'tr_949_tr10050': 'የ ሉ ሲ ቅሪት አሜሪካ ተወስዶ እንደሚ ጐበኝ ተገለጸ',\n", - " 'tr_950_tr10051': 'ሀያ አራት ክትትል ደህንነቶች እርስ በርስ ተገማግመው ከስራ ገበታ ቸው ተነሱ',\n", - " 'tr_951_tr10052': 'ይህ ሁኔታ በ ኮንጐ ዴሞክራቲክ ሪፐብሊክ የተፈጠረ ውን ችግር ሊ ያወሳስበው እንደሚ ችል ብዙዎቹ ገም ተዋል',\n", - " 'tr_952_tr10053': 'ሌኒን እንዳስ ተማረው ደግሞ ቲዮሪ ደብ ዛዛ ና ት',\n", - " 'tr_953_tr10054': 'ማ ንም ቤተሰብ እንደሚ ገናኘው እኔ ም ከ ቅርብ ቤተሰብ ጋር ለ መገናኘት ይህን ያህል አስቸጋሪ ሆኖ እንዴት እንደ ታያቸው አላውቅ ም',\n", - " 'tr_954_tr10055': 'የ ውስጥ ጭን ቄ ን ባይ ረዱ ልኝ ነው',\n", - " 'tr_955_tr10056': 'ይህም ማለት የ ስንቅ ና ትጥቅ አቅርቦቱ ን ማቋረጥ ና ደጀን ማሳጣት ነው',\n", - " 'tr_956_tr10057': 'እነዚህ በ ሽሬ አውራጃ የሚገኙ ወረዳ ዎች ናቸው',\n", - " 'tr_957_tr10058': 'ኢንፎርሜሽ ንና እውነት በ ገዥው ፓርቲ በ ሞ ኖፓል ተ ይ ዟል',\n", - " 'tr_958_tr10059': 'በዚህ ታላቅ ሰልፍ ላይ አገር ወዳድ ኢትዮጵያውያ ን ሁሉ ተገኝተው አንድ ነታቸውን እንደሚያ ስ መሰክሩ ና ድምጻቸው ን በ አንድነት እንደሚ ያሰሙ ታውቋል',\n", - " 'tr_959_tr10060': 'ጊዜው ወደ ሶስት ሳምንት እየ ተጠጋ ነው',\n", - " 'tr_960_tr10061': 'መንግስት በ ኢንቨስትመንት እንቅስቃሴ ላይ የ ተከሰቱ ም የ ፖሊሲ ና የ አሰራር ግድፈቶች ን ለ ማስወገድ እርምጃ መውሰዱ ከ ግሉ ኢንቨስትመንት ፍሰት የ ሚገኘው ን ድርሻ እንደሚያ ሻሽለው ም ገለጹ',\n", - " 'tr_961_tr10062': 'እኔ ግን ነፍጠኛ ም መድፈኛ ም እንዳል ሆ ኩኝ ልንገራችሁ ብዬ እንጂ ፖለቲከኛ ሳል ሆን አሽሙረኛ ነኝ ብዬ እናንተ ን ላሳምናችሁ አል ሞክር ም',\n", - " 'tr_962_tr10063': 'ኮሎኔል በዛብህ ጴጥሮስ የ አማራጭ ሀይሎች ሊቀመንበር የ ዶክተር በየነ ጴጥሮስ ወንድም መሆናቸው ተያይዞ ተ ገልጿ ል',\n", - " 'tr_963_tr10064': 'የ መስተዳድሩ መግለጫ ከተማዋ ስር ነቀል ለውጥ እንደሚ ያስፈልጋት ገልጾ ህዝቡ በዚህ እንዲ ሳተፍ ቢ ጠይቅ ም ጊዜያዊ መስተዳድሩ የ መዋቅር ለውጡ ን ያስፈጽማል ተብሎ አይጠበቅ ም',\n", - " 'tr_964_tr10065': 'ለወደፊቱ በሚ ዘጋጀው ጉባኤ የ በ ኩሌን ሀሳብ ለ ካድሬው ይዤ አቀርባ ለሁ',\n", - " 'tr_965_tr10066': 'ኤኤፍፒ ከ ሶስት ሺ በላይ የኤርትራ ኩናማ ዎች ወደ ኢትዮጵያ ሸሽተው በ መግባት የኤርትራ ሰራዊት በ ሀይል እየ መለመላቸው ነው ሲሉ ውንጀላ ሰንዝ ረዋል',\n", - " 'tr_966_tr10067': 'ዋናው አላማችን አባላ ቶቻችን በ ስፖርቱ ተሳታፊ እንዲሆኑ ና ለ ሀገራችን ስፖርት የ በኩላቸው ን አስተዋጽኦ እንዲ ያበረክቱ እንጂ እንደ አንዳንድ ክለቦች ድርጅት ን ለ ማስተዋወቅ አይደለም',\n", - " 'tr_967_tr10068': 'በ ማጠቃለያ ውም በ እርዳታ አ ሰባሰቡ ወቅት ኢህአዲግ በ በጐ አይ ን የማ ይመለከታቸው ና በ አሸባሪነት ጠርጥሬ ያ ቸዋለሁ የሚ ላቸው ኢትዮጵያውያ ን የ ህግ ታራሚዎች ሳይ ቀሩ በ እርዳታው ተሳትፎ ማድረጋቸው ን አመልክ ቷል',\n", - " 'tr_968_tr10069': 'ምክትል ዳይሬክተሩ ትናንት አዲስ አበባ ሲ ገቡ የ ኢትዮጵያ ዜና አገልግሎት ድርጅት የስራ ሀ ላፈ ዎች ቦሌ አለም አቀፍ አውሮፕላን ጣቢያ ተገኝተው ተቀብለ ዋቸዋል',\n", - " 'tr_969_tr10070': 'የ ኦጋዴን ነጻ አውጪ ግንባር ን እንቅስቃሴ ለ ማምከን ኢህአዴግ ተደጋጋሚ ጥረቶች ን አካሂ ዷል',\n", - " 'tr_970_tr10071': 'አያ ይሄን ን ደብዳቤ በ ዋዛ እንዳ ያዩት ዋዛ አይደለም',\n", - " 'tr_971_tr10072': 'የ ኦርቶዶክስ ና የ ፕሮቴስታንት እምነቶች ልዩነት የሚያስ ገነዝብ ትምህርት ተ ጀም ሯል',\n", - " 'tr_972_tr10073': 'ቢነግሩ ት ለማ ይሰማ ጆሮ የተባለ ውን እንመልከት',\n", - " 'tr_973_tr10074': 'አብዮታችን ወዴት ና እንዴት እ የተጓዘ እንደሚ ገኝ የነ ጠረ ስእል መያዝ የ ድርጅታችን መታደስ አንደኛው ና ቁልፉ እርምጃ ነው',\n", - " 'tr_974_tr10075': 'ህግ ን የ መጣስ ተግባር ሊ ያስከትል የሚ ችለው ን ጦስ የ ኢትዮጵያ ህዝብ በ ጥሞ ና ሊያ ሰላ ስለው ይገባል ባዮች ነን',\n", - " 'tr_975_tr10076': 'ተበታት ነን ያለ ን ስለሆነ እነማን እንዳሉ ና እነማን እንዳል መጡ ለማወቅ አልተቻለ ም',\n", - " 'tr_976_tr10077': 'በ ክልሉ ፍትህ ና ርትእ እንዳይኖር ያደረጉት መስተዳ ድ ሮቹ ናቸው ሲሉ ተ ሰብሳቢዎቹ ገልጸዋል',\n", - " 'tr_977_tr10078': 'ኮሚሽነሩ ግን የ ውሀ ሽ ታ ሆኑ',\n", - " 'tr_978_tr10079': 'ስንዴ ቢ ሰፍሩ ልን ም ቢር በ ንም ኩሩ ና በራሱ የሚ ተማመን ህዝብ እንዳለ ን ሊ ያውቁ ይገባል',\n", - " 'tr_979_tr10080': 'የ ኢትዮ ኤርትራ ን ግጭት በ ተመለከተ ግብጽ ለ ሁለቱ ም ወገን በማ ያደላ መልኩ የ ገለልተኝነት ሚና እንደምት ጫወት በ ሆስኒ ሙባረክ እንደ ተነገራቸው ገልጸዋል',\n", - " 'tr_980_tr10081': 'ተግባ ሬ ግልጽ አቋሜ ም ከ ኢትዮጵያውያ ን ፍላጐት ውጪ ያልሆነ ነው',\n", - " 'tr_981_tr10082': 'ዛሬ ወንድ ና ሴቶች እኩል ናቸው ብለው የሚናገሩ በ ሂሳብ ትምህርት የ ወደቁ ወይም ያልተማሩ ቢ ሰኙ አ ያስገርም ም',\n", - " 'tr_982_tr10083': 'ብሄራዊ ቡድናችን ዝግጅቱ ን እንደማ ያቋርጥ ተ ገልጿ ል',\n", - " 'tr_983_tr10084': 'በ እለቱ ኢንተር አንድ ለ ዜሮ አሸን ፏል',\n", - " 'tr_984_tr10085': 'እና ፊዮሬንቲና ና ቦሎኛ ነገ አይ ላቀቁ ም',\n", - " 'tr_985_tr10086': 'ሌሎች ድርጅቶች ክለብ ሲያ ቋቁሙ ስራ አስኪያጅ ኮሚቴ ይኖራ ቸዋል',\n", - " 'tr_986_tr10087': 'የ ኢትዮጵያ ፉትቦል ደረጃ ን እንዴት አ ዩት',\n", - " 'tr_987_tr10088': 'ለ ልኡል አልቤር ክለብ ኤሪክ ካን ቶ ና ተሰልፎ ተጫው ቷል',\n", - " 'tr_988_tr10089': 'እንደ ምክትል ፕሬዚዳንት ዋ ና ጸሀፊው አባባል በ ኢትዮጵያ ውስጥ በ አሁኑ ወቅት አስራ አምስት ሚሊዮን ህጻናት የ ትምህርት እድል ያላገኙ ናቸው',\n", - " 'tr_989_tr10090': 'ታዛቢዎች እንደሚ ሉት በ ስኳር ና በ ዱቄት ፋብሪካ ሀላፊዎች ክስ መቅረቡ የ ሙስናው ን ዘመቻ ነጻ ና የ ተሟላ አ ያደርገው ም',\n", - " 'tr_990_tr10091': 'በ እየሩሳሌም በ ሚገኘው ና ለ ክርስቲያኖች ቅዱስ ተብሎ በሚ ጠራው ቦታ ላይ ኢትዮጵያዊያ ንና የ ግብጽ መነኩሴ ዎች በ ፈጠሩ ት ግጭት ከፍተኛ ጉዳት መድረሱ ተገለጸ',\n", - " 'tr_991_tr10092': 'በ ጂቡቲ ወህኒ ቤት ኢትዮጵያውያ ን እየ ተንገላቱ ነው',\n", - " 'tr_992_tr10093': 'ይሁን እንጂ ሀብት ና ንብረታቸው እንደማይ ነካ ባቸው ና በ ወኪሎ ቻቸው አማካይ ነት ሊጠበቅ ላቸው እንደሚ ችል ታውቋል',\n", - " 'tr_993_tr10094': 'ለ ኢትዮጵያ ና ለ ኢትዮጵያውያ ን የምናውቅ ላቸው እኛ ወይም እኔ ብቻ ነኝ የሚ ል በሽታ አሁን ም አለ ብን',\n", - " 'tr_994_tr10095': 'ጸሀፊ ዎቹ ቅዳሜ ና እሁድ ገብተው ይፈልጋሉ ተ ባለ',\n", - " 'tr_995_tr10096': 'ጠላት ና ወገን ተባባሪ ባላንጣ ሲ ሆኑ ደግሞ ስለ አንዳች አዲስ ተስፋ ማውሳት ያስቸግራ ል',\n", - " 'tr_996_tr10097': 'የ ዚያ ን ያህል ባይ ሆኑ ም ጨው ና ሌሎች ንም በ ምጽዋ ወደብ የተ ራገፉ እቃዎች ን የ ጫኑ ተሽከርካሪዎች ደግሞ ወደ ኢትዮጵያ እንዳይ ገቡ ተ ከልክለው መቆማቸው ታውቋል',\n", - " 'tr_997_tr10098': 'ባለሞያ ው ለዚህ ሶስት ምክንያቶች ን ሰጥተዋል',\n", - " 'tr_998_tr10099': 'ስምምነቱ ን የፈረሙት የ ንግድ ና ኢንዱስትሪ ሚኒስትር አቶ ግርማ ብሩ ና የ ጅቡቲ የ ገንዘብ የ ኢኮኖሚ ና ፕላን ሚኒስትር ያሲን አልሚ ቦ ህ ናቸው',\n", - " 'tr_999_tr10100': 'ሌላው ቀርቶ የ ኤቨርተን ደጋፊዎች እንኳ ን ከ ራሴ አንስቶ ራሽ ን በ ሞዴልነት እን ወስደው ነበር',\n", - " 'tr_1000_tr11001': 'ያ ኮምፒ ተር ለ ተጠቃሚው በ ትክክል የሚ ፈለገው ን ነገር እንዲ ያሟላ ማድረግ ነው',\n", - " ...}" + "10875" ] }, "metadata": {}, @@ -1123,517 +197,19 @@ } ], "source": [ - "display(translation_obj)" + "display(len(translation_obj))" ] }, { "cell_type": "code", - "execution_count": 13, + "execution_count": 17, + "id": "f1056fa7", "metadata": {}, "outputs": [ { "data": { "text/plain": [ - "{'tr_10000_tr097082': (array([-0.11535194, -0.13088593, -0.11130099, ..., -0.12260991,\n", - " -0.14306018, -0.09356608], dtype=float32),\n", - " 9.088,\n", - " 1,\n", - " 22000),\n", - " 'tr_10001_tr097083': (array([-0.11713821, -0.1325651 , -0.11193331, ..., -0.11807333,\n", - " -0.13700932, -0.08942752], dtype=float32),\n", - " 5.632,\n", - " 1,\n", - " 22000),\n", - " 'tr_10002_tr097084': (array([-0.12715799, -0.14431693, -0.12283181, ..., -0.11431045,\n", - " -0.13372336, -0.08774392], dtype=float32),\n", - " 6.144,\n", - " 1,\n", - " 22000),\n", - " 'tr_10003_tr097085': (array([-0.12300719, -0.139679 , -0.11857443, ..., -0.11635446,\n", - " -0.1341145 , -0.08703998], dtype=float32),\n", - " 5.76,\n", - " 1,\n", - " 22000),\n", - " 'tr_10004_tr097086': (array([-0.11654395, -0.13136779, -0.11089978, ..., -0.12697333,\n", - " -0.14742425, -0.0961772 ], dtype=float32),\n", - " 5.376,\n", - " 1,\n", - " 22000),\n", - " 'tr_10005_tr097087': (array([-0.12053408, -0.13501762, -0.11414921, ..., -0.11928798,\n", - " -0.13834795, -0.09034028], dtype=float32),\n", - " 6.656,\n", - " 1,\n", - " 22000),\n", - " 'tr_10006_tr097088': (array([-0.12422882, -0.14019111, -0.11809152, ..., -0.12450344,\n", - " -0.1450578 , -0.09492932], dtype=float32),\n", - " 6.528,\n", - " 1,\n", - " 22000),\n", - " 'tr_10007_tr097089': (array([-0.12306449, -0.1394157 , -0.1172735 , ..., -0.12550128,\n", - " -0.14435506, -0.09380701], dtype=float32),\n", - " 5.504,\n", - " 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dtype=float32),\n", - " 3.2,\n", - " 1,\n", - " 22000),\n", - " 'tr_10086_tr098048': (array([-0.12661912, -0.14280415, -0.12063462, ..., -0.12124718,\n", - " -0.14029978, -0.09175819], dtype=float32),\n", - " 4.096,\n", - " 1,\n", - " 22000),\n", - " 'tr_10087_tr098049': (array([-0.11118729, -0.12678559, -0.10747544, ..., -0.1269342 ,\n", - " -0.14780396, -0.09676003], dtype=float32),\n", - " 5.12,\n", - " 1,\n", - " 22000),\n", - " 'tr_10088_tr098050': (array([-0.1212725 , -0.13772127, -0.11666689, ..., -0.12715375,\n", - " -0.1461284 , -0.09472588], dtype=float32),\n", - " 5.248,\n", - " 1,\n", - " 22000),\n", - " 'tr_10089_tr098051': (array([-0.12368317, -0.14043643, -0.11887812, ..., -0.12213954,\n", - " -0.14189196, -0.09261528], dtype=float32),\n", - " 6.912,\n", - " 1,\n", - " 22000),\n", - " 'tr_1008_tr11009': (array([-0.01907633, -0.02169414, -0.01808988, ..., -0.02907302,\n", - " -0.03371771, -0.02193047], dtype=float32),\n", - " 6.016,\n", - " 1,\n", - " 22000),\n", - " 'tr_10090_tr098052': (array([-0.11293647, -0.1282733 , -0.108813 , ..., -0.12874217,\n", - " -0.14914206, -0.09698306], dtype=float32),\n", - " 5.12,\n", - " 1,\n", - " 22000)}" + "5000" ] }, "metadata": {}, @@ -1641,12 +217,52 @@ } ], "source": [ - "display(audio_obj)" + "display(len(audio_obj))" ] }, { "cell_type": "code", - "execution_count": 16, + "execution_count": 28, + "id": "d2af6021", + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "'የ ሰርጉ ወጥ ኩ ችም ተደርጐ ነው የ ተሰራው'" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "data": { + "text/html": [ + "\n", + " \n", + " " + ], + "text/plain": [ + "" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "sample_label = list(audio_obj.keys())[490]\n", + "display(translation_obj[sample_label])\n", + "display(ipd.Audio(audio_obj[sample_label][0], rate=rate))" + ] + }, + { + "cell_type": "code", + "execution_count": 18, + "id": "4e832d5d", "metadata": { "colab": { "base_uri": "https://localhost:8080/", @@ -1690,7 +306,7 @@ " የተለያዩ የ ትግራይ አውራጃ ተወላጆች ገንዘባቸው ን አዋጥ ተው የ ልማት ...\n", " tr_10000_tr097082\n", " 1\n", - " 22000\n", + " 8000\n", " 9.088\n", " \n", " \n", @@ -1698,7 +314,7 @@ " የ ጠመንጃ ተኩስ ተከፈተ ና አራት የኤርትራ ወታደሮች ተገደሉ\n", " tr_10001_tr097083\n", " 1\n", - " 22000\n", + " 8000\n", " 5.632\n", " \n", " \n", @@ -1706,7 +322,7 @@ " ላነሷቸው ጥያቄዎች የ ሰጡት ን መልስ አቅርበ ነዋል\n", " tr_10002_tr097084\n", " 1\n", - " 22000\n", + " 8000\n", " 6.144\n", " \n", " \n", @@ -1714,7 +330,7 @@ " እ ብዱ አስፋልቱ ላይ የ ኰለኰ ለ ው ድንጋይ መኪና አላ ሳልፍ አለ\n", " tr_10003_tr097085\n", " 1\n", - " 22000\n", + " 8000\n", " 5.760\n", " \n", " \n", @@ -1722,7 +338,7 @@ " ጠጁ ን ኰ መኰ መ ኰ መኰ መ ና ሚስቱ ን ሲ ያሰቃ ያት አደረ\n", " tr_10004_tr097086\n", " 1\n", - " 22000\n", + " 8000\n", " 5.376\n", " \n", " \n", @@ -1734,81 +350,81 @@ " ...\n", " \n", " \n", - " 95\n", - " በ እለቱ ጥቁር ማሊያ አድርገው የ ገቡት ዩናይት ዶች ልክ እንደ ማሊያው ...\n", - " tr_10087_tr098049\n", + " 4995\n", + " እነ አቶ ተወልደ ካድሬው የሚ ያግዛቸው መስሏቸው ተስፋ አድርገው እንደ ነ...\n", + " tr_4709_tr48010\n", " 1\n", - " 22000\n", - " 5.120\n", + " 8000\n", + " 7.936\n", " \n", " \n", - " 96\n", - " ከ የክልሉ ጥሩ ጥሩ ተጨዋቾች ናቸው ብለው ያመኑ ባቸውን አሰባ ስበዋል\n", - " tr_10088_tr098050\n", + " 4996\n", + " የ አውሮፓ ፓር ሊያ ሜንት በ ኢትዮጵያ ዲሞክራሲያዊ ሂደት ላይ ያለውን ጥ...\n", + " tr_470_tr05070\n", " 1\n", - " 22000\n", - " 5.248\n", + " 8000\n", + " 6.272\n", " \n", " \n", - " 97\n", - " አቶ ደምስ ማ ንም እንደሚ ያውቀው በ ኢትዮጵያ ፉትቦል ፌዴሬሽን ና በ ክ...\n", - " tr_10089_tr098051\n", + " 4997\n", + " አንቺ ቆንጆ የምት ያቸው እንዴት ያሉት ን ሴቶች ነው ለስላሳ ሳቅ በ አዳ...\n", + " tr_4710_tr48011\n", " 1\n", - " 22000\n", - " 6.912\n", + " 8000\n", + " 5.632\n", " \n", " \n", - " 98\n", - " የ ኮሪያ ወታደራዊ ጠበብ ት ኢትዮጵያ ን ን እየ ረዱ ነው\n", - " tr_1008_tr11009\n", + " 4998\n", + " በ አይ ኤም ኤፍ የ ዋሽንግተን ስብሰባ የ ኢትዮጵያ ልኡክ ሊ ሄድ ነው\n", + " tr_4711_tr48012\n", " 1\n", - " 22000\n", - " 6.016\n", + " 8000\n", + " 4.480\n", " \n", " \n", - " 99\n", - " የ ኢትዮጵያ ኦሎምፒክ ኮሚቴ ጽፈት ቤት ጉዳዩ ን አስመልክቶ በ የ አድራሻ...\n", - " tr_10090_tr098052\n", + " 4999\n", + " ምናልባት ከ ኢትዮጵያ ሄዶ ይሆናል\n", + " tr_4712_tr48013\n", " 1\n", - " 22000\n", - " 5.120\n", + " 8000\n", + " 3.328\n", " \n", " \n", "\n", - "

100 rows × 5 columns

\n", + "

5000 rows × 5 columns

\n", "" ], "text/plain": [ - " translation label \\\n", - "0 የተለያዩ የ ትግራይ አውራጃ ተወላጆች ገንዘባቸው ን አዋጥ ተው የ ልማት ... tr_10000_tr097082 \n", - "1 የ ጠመንጃ ተኩስ ተከፈተ ና አራት የኤርትራ ወታደሮች ተገደሉ tr_10001_tr097083 \n", - "2 ላነሷቸው ጥያቄዎች የ ሰጡት ን መልስ አቅርበ ነዋል tr_10002_tr097084 \n", - "3 እ ብዱ አስፋልቱ ላይ የ ኰለኰ ለ ው ድንጋይ መኪና አላ ሳልፍ አለ tr_10003_tr097085 \n", - "4 ጠጁ ን ኰ መኰ መ ኰ መኰ መ ና ሚስቱ ን ሲ ያሰቃ ያት አደረ tr_10004_tr097086 \n", - ".. ... ... \n", - "95 በ እለቱ ጥቁር ማሊያ አድርገው የ ገቡት ዩናይት ዶች ልክ እንደ ማሊያው ... tr_10087_tr098049 \n", - "96 ከ የክልሉ ጥሩ ጥሩ ተጨዋቾች ናቸው ብለው ያመኑ ባቸውን አሰባ ስበዋል tr_10088_tr098050 \n", - "97 አቶ ደምስ ማ ንም እንደሚ ያውቀው በ ኢትዮጵያ ፉትቦል ፌዴሬሽን ና በ ክ... tr_10089_tr098051 \n", - "98 የ ኮሪያ ወታደራዊ ጠበብ ት ኢትዮጵያ ን ን እየ ረዱ ነው tr_1008_tr11009 \n", - "99 የ ኢትዮጵያ ኦሎምፒክ ኮሚቴ ጽፈት ቤት ጉዳዩ ን አስመልክቶ በ የ አድራሻ... tr_10090_tr098052 \n", + " translation label \\\n", + "0 የተለያዩ የ ትግራይ አውራጃ ተወላጆች ገንዘባቸው ን አዋጥ ተው የ ልማት ... tr_10000_tr097082 \n", + "1 የ ጠመንጃ ተኩስ ተከፈተ ና አራት የኤርትራ ወታደሮች ተገደሉ tr_10001_tr097083 \n", + "2 ላነሷቸው ጥያቄዎች የ ሰጡት ን መልስ አቅርበ ነዋል tr_10002_tr097084 \n", + "3 እ ብዱ አስፋልቱ ላይ የ ኰለኰ ለ ው ድንጋይ መኪና አላ ሳልፍ አለ tr_10003_tr097085 \n", + "4 ጠጁ ን ኰ መኰ መ ኰ መኰ መ ና ሚስቱ ን ሲ ያሰቃ ያት አደረ tr_10004_tr097086 \n", + "... ... ... \n", + "4995 እነ አቶ ተወልደ ካድሬው የሚ ያግዛቸው መስሏቸው ተስፋ አድርገው እንደ ነ... tr_4709_tr48010 \n", + "4996 የ አውሮፓ ፓር ሊያ ሜንት በ ኢትዮጵያ ዲሞክራሲያዊ ሂደት ላይ ያለውን ጥ... tr_470_tr05070 \n", + "4997 አንቺ ቆንጆ የምት ያቸው እንዴት ያሉት ን ሴቶች ነው ለስላሳ ሳቅ በ አዳ... tr_4710_tr48011 \n", + "4998 በ አይ ኤም ኤፍ የ ዋሽንግተን ስብሰባ የ ኢትዮጵያ ልኡክ ሊ ሄድ ነው tr_4711_tr48012 \n", + "4999 ምናልባት ከ ኢትዮጵያ ሄዶ ይሆናል tr_4712_tr48013 \n", "\n", - " channel sample_rate duration \n", - "0 1 22000 9.088 \n", - "1 1 22000 5.632 \n", - "2 1 22000 6.144 \n", - "3 1 22000 5.760 \n", - "4 1 22000 5.376 \n", - ".. ... ... ... \n", - "95 1 22000 5.120 \n", - "96 1 22000 5.248 \n", - "97 1 22000 6.912 \n", - "98 1 22000 6.016 \n", - "99 1 22000 5.120 \n", + " channel sample_rate duration \n", + "0 1 8000 9.088 \n", + "1 1 8000 5.632 \n", + "2 1 8000 6.144 \n", + "3 1 8000 5.760 \n", + "4 1 8000 5.376 \n", + "... ... ... ... \n", + "4995 1 8000 7.936 \n", + "4996 1 8000 6.272 \n", + "4997 1 8000 5.632 \n", + "4998 1 8000 4.480 \n", + "4999 1 8000 3.328 \n", "\n", - "[100 rows x 5 columns]" + "[5000 rows x 5 columns]" ] }, - "execution_count": 16, + "execution_count": 18, "metadata": {}, "output_type": "execute_result" } @@ -1819,7 +435,8 @@ }, { "cell_type": "code", - "execution_count": 17, + "execution_count": 19, + "id": "3d5f8486", "metadata": { "colab": { "base_uri": "https://localhost:8080/", @@ -1870,7 +487,7 @@ " የተለያዩ የ ትግራይ አውራጃ ተወላጆች ገንዘባቸው ን አዋጥ ተው የ ልማት ...\n", " tr_10000_tr097082\n", " 1\n", - " 22000\n", + " 8000\n", " 9.088\n", " \n", " \n", @@ -1878,7 +495,7 @@ " የ ጠመንጃ ተኩስ ተከፈተ ና አራት የኤርትራ ወታደሮች ተገደሉ\n", " tr_10001_tr097083\n", " 1\n", - " 22000\n", + " 8000\n", " 5.632\n", " \n", " \n", @@ -1886,7 +503,7 @@ " ላነሷቸው ጥያቄዎች የ ሰጡት ን መልስ አቅርበ ነዋል\n", " tr_10002_tr097084\n", " 1\n", - " 22000\n", + " 8000\n", " 6.144\n", " \n", " \n", @@ -1894,7 +511,7 @@ " እ ብዱ አስፋልቱ ላይ የ ኰለኰ ለ ው ድንጋይ መኪና አላ ሳልፍ አለ\n", " tr_10003_tr097085\n", " 1\n", - " 22000\n", + " 8000\n", " 5.760\n", " \n", " \n", @@ -1902,7 +519,7 @@ " ጠጁ ን ኰ መኰ መ ኰ መኰ መ ና ሚስቱ ን ሲ ያሰቃ ያት አደረ\n", " tr_10004_tr097086\n", " 1\n", - " 22000\n", + " 8000\n", " 5.376\n", " \n", " \n", @@ -1914,81 +531,81 @@ " ...\n", " \n", " \n", - " 95\n", - " በ እለቱ ጥቁር ማሊያ አድርገው የ ገቡት ዩናይት ዶች ልክ እንደ ማሊያው ...\n", - " tr_10087_tr098049\n", + " 4995\n", + " እነ አቶ ተወልደ ካድሬው የሚ ያግዛቸው መስሏቸው ተስፋ አድርገው እንደ ነ...\n", + " tr_4709_tr48010\n", " 1\n", - " 22000\n", - " 5.120\n", + " 8000\n", + " 7.936\n", " \n", " \n", - " 96\n", - " ከ የክልሉ ጥሩ ጥሩ ተጨዋቾች ናቸው ብለው ያመኑ ባቸውን አሰባ ስበዋል\n", - " tr_10088_tr098050\n", + " 4996\n", + " የ አውሮፓ ፓር ሊያ ሜንት በ ኢትዮጵያ ዲሞክራሲያዊ ሂደት ላይ ያለውን ጥ...\n", + " tr_470_tr05070\n", " 1\n", - " 22000\n", - " 5.248\n", + " 8000\n", + " 6.272\n", " \n", " \n", - " 97\n", - " አቶ ደምስ ማ ንም እንደሚ ያውቀው በ ኢትዮጵያ ፉትቦል ፌዴሬሽን ና በ ክ...\n", - " tr_10089_tr098051\n", + " 4997\n", + " አንቺ ቆንጆ የምት ያቸው እንዴት ያሉት ን ሴቶች ነው ለስላሳ ሳቅ በ አዳ...\n", + " tr_4710_tr48011\n", " 1\n", - " 22000\n", - " 6.912\n", + " 8000\n", + " 5.632\n", " \n", " \n", - " 98\n", - " የ ኮሪያ ወታደራዊ ጠበብ ት ኢትዮጵያ ን ን እየ ረዱ ነው\n", - " tr_1008_tr11009\n", + " 4998\n", + " በ አይ ኤም ኤፍ የ ዋሽንግተን ስብሰባ የ ኢትዮጵያ ልኡክ ሊ ሄድ ነው\n", + " tr_4711_tr48012\n", " 1\n", - " 22000\n", - " 6.016\n", + " 8000\n", + " 4.480\n", " \n", " \n", - " 99\n", - " የ ኢትዮጵያ ኦሎምፒክ ኮሚቴ ጽፈት ቤት ጉዳዩ ን አስመልክቶ በ የ አድራሻ...\n", - " tr_10090_tr098052\n", + " 4999\n", + " ምናልባት ከ ኢትዮጵያ ሄዶ ይሆናል\n", + " tr_4712_tr48013\n", " 1\n", - " 22000\n", - " 5.120\n", + " 8000\n", + " 3.328\n", " \n", " \n", "\n", - "

100 rows × 5 columns

\n", + "

5000 rows × 5 columns

\n", "" ], "text/plain": [ - " translation label \\\n", - "0 የተለያዩ የ ትግራይ አውራጃ ተወላጆች ገንዘባቸው ን አዋጥ ተው የ ልማት ... tr_10000_tr097082 \n", - "1 የ ጠመንጃ ተኩስ ተከፈተ ና አራት የኤርትራ ወታደሮች ተገደሉ tr_10001_tr097083 \n", - "2 ላነሷቸው ጥያቄዎች የ ሰጡት ን መልስ አቅርበ ነዋል tr_10002_tr097084 \n", - "3 እ ብዱ አስፋልቱ ላይ የ ኰለኰ ለ ው ድንጋይ መኪና አላ ሳልፍ አለ tr_10003_tr097085 \n", - "4 ጠጁ ን ኰ መኰ መ ኰ መኰ መ ና ሚስቱ ን ሲ ያሰቃ ያት አደረ tr_10004_tr097086 \n", - ".. ... ... \n", - "95 በ እለቱ ጥቁር ማሊያ አድርገው የ ገቡት ዩናይት ዶች ልክ እንደ ማሊያው ... tr_10087_tr098049 \n", - "96 ከ የክልሉ ጥሩ ጥሩ ተጨዋቾች ናቸው ብለው ያመኑ ባቸውን አሰባ ስበዋል tr_10088_tr098050 \n", - "97 አቶ ደምስ ማ ንም እንደሚ ያውቀው በ ኢትዮጵያ ፉትቦል ፌዴሬሽን ና በ ክ... tr_10089_tr098051 \n", - "98 የ ኮሪያ ወታደራዊ ጠበብ ት ኢትዮጵያ ን ን እየ ረዱ ነው tr_1008_tr11009 \n", - "99 የ ኢትዮጵያ ኦሎምፒክ ኮሚቴ ጽፈት ቤት ጉዳዩ ን አስመልክቶ በ የ አድራሻ... tr_10090_tr098052 \n", + " translation label \\\n", + "0 የተለያዩ የ ትግራይ አውራጃ ተወላጆች ገንዘባቸው ን አዋጥ ተው የ ልማት ... tr_10000_tr097082 \n", + "1 የ ጠመንጃ ተኩስ ተከፈተ ና አራት የኤርትራ ወታደሮች ተገደሉ tr_10001_tr097083 \n", + "2 ላነሷቸው ጥያቄዎች የ ሰጡት ን መልስ አቅርበ ነዋል tr_10002_tr097084 \n", + "3 እ ብዱ አስፋልቱ ላይ የ ኰለኰ ለ ው ድንጋይ መኪና አላ ሳልፍ አለ tr_10003_tr097085 \n", + "4 ጠጁ ን ኰ መኰ መ ኰ መኰ መ ና ሚስቱ ን ሲ ያሰቃ ያት አደረ tr_10004_tr097086 \n", + "... ... ... \n", + "4995 እነ አቶ ተወልደ ካድሬው የሚ ያግዛቸው መስሏቸው ተስፋ አድርገው እንደ ነ... tr_4709_tr48010 \n", + "4996 የ አውሮፓ ፓር ሊያ ሜንት በ ኢትዮጵያ ዲሞክራሲያዊ ሂደት ላይ ያለውን ጥ... tr_470_tr05070 \n", + "4997 አንቺ ቆንጆ የምት ያቸው እንዴት ያሉት ን ሴቶች ነው ለስላሳ ሳቅ በ አዳ... tr_4710_tr48011 \n", + "4998 በ አይ ኤም ኤፍ የ ዋሽንግተን ስብሰባ የ ኢትዮጵያ ልኡክ ሊ ሄድ ነው tr_4711_tr48012 \n", + "4999 ምናልባት ከ ኢትዮጵያ ሄዶ ይሆናል tr_4712_tr48013 \n", "\n", - " channel sample_rate duration \n", - "0 1 22000 9.088 \n", - "1 1 22000 5.632 \n", - "2 1 22000 6.144 \n", - "3 1 22000 5.760 \n", - "4 1 22000 5.376 \n", - ".. ... ... ... \n", - "95 1 22000 5.120 \n", - "96 1 22000 5.248 \n", - "97 1 22000 6.912 \n", - "98 1 22000 6.016 \n", - "99 1 22000 5.120 \n", + " channel sample_rate duration \n", + "0 1 8000 9.088 \n", + "1 1 8000 5.632 \n", + "2 1 8000 6.144 \n", + "3 1 8000 5.760 \n", + "4 1 8000 5.376 \n", + "... ... ... ... \n", + "4995 1 8000 7.936 \n", + "4996 1 8000 6.272 \n", + "4997 1 8000 5.632 \n", + "4998 1 8000 4.480 \n", + "4999 1 8000 3.328 \n", "\n", - "[100 rows x 5 columns]" + "[5000 rows x 5 columns]" ] }, - "execution_count": 17, + "execution_count": 19, "metadata": {}, "output_type": "execute_result" } @@ -1999,7 +616,8 @@ }, { "cell_type": "code", - "execution_count": 18, + "execution_count": 20, + "id": "d6c2fa46", "metadata": {}, "outputs": [], "source": [ @@ -2010,7 +628,8 @@ }, { "cell_type": "code", - "execution_count": 19, + "execution_count": 21, + "id": "7dda976a", "metadata": {}, "outputs": [], "source": [ @@ -2019,6 +638,7 @@ }, { "cell_type": "markdown", + "id": "7e592b9d", "metadata": {}, "source": [ "### Data Agumentation, adding noise" @@ -2026,12 +646,13 @@ }, { "cell_type": "code", - "execution_count": 20, + "execution_count": 22, + "id": "6b243702", "metadata": {}, "outputs": [ { "data": { - "image/png": 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sRPYqx66V+WX4cWtx4AXDkF9aiw2HTkR0G/Fg99G2QaDSv1ceaPuekuBKp13wr+aJTXx9V1sKq7DlSGz2OL/0817Ng333ZAYUvkADJiOZC+tv3VqmkhCRfnAGPwqKxeZA4Yl6/GXGZtzzRdvKChR7jlQ0tHnujk83qF7P13lt69i6xXLeekVd+KXkKHhqeuoCDZj0lSqhBX+zPHJ2P++2F1VFuwlEYWGwTEF5a3E+zn5hsaoem3BuZTNnOXyRGmCn5rtJSjBGpA3tIVYGKHYUjhj5zT/xw06frzFYbutIRT0uc82MGSNfcVB2Hq3GK/M5uU28YLBMQalqcE5TalARLXeg42JMitSJ6bWFwU8VnGiK3UNMe5zYF+46hrs+U9+b3xFpGSxHqyJZrAT87cnfwM1Y/7TUHAsptsXumYzaTW2TDVtcOYLtdRKK9YOoHkTqM9xaGPwtVYOv0X8xQG3cU1oTOMd5bavyYt9vLsbcMOs6dxSPz9qh2bqiVb+XwTJRx8RgmQJ6Y9E+T2kwNbmAPG9EV6Q+f4uKW82xvA+oTcNYsLM04DLXT18Du6KnLXYvJbT3k4YXDSJKn2ws7++R4u+b4P5PsYLBMgVkszefAYoq2w4K84knjg5JTbAcyztBewQ+sfvpaM+uZRoGe5aJSEMMlimgUM87HCDVMVlUVLiI5djBISU+WnlA86oYzHP0TsM5SaKYsxylDccoflwUKxgsU0Ch9tKEEyjFcpClF5G6WAlU41bpJh3XFv7T5xv9vv7gt1vxxA87Na8r/rorWLY7JOpdU4NTbFTACZSXHgt/AxGpx2CZAlJTAUNp9NPzNW4JBWvhrmN4b2mB5ustr21S1XtWWtOkeRu0MnvbUb+v55fWRnT7byzah4W7A+c5xwt7O3cth1IDfPy0hX5fZ6zs3zkvLkZ1ozXazfDr+vdWY+Ph2JxMiSKHwTIFpsNRGGsLymNmOuVo2FEc3Ex83uw9VoPD5fVeX7PaGQ1oxdukMLHswpeXhhXwaprCEMS6Bv19roYbdGLOcmCNFnu0m+DX2gMV0W4C6RCDZQooWiPLfWm02nH99DV49Ptt0W6KbhnDKNl20SvLcNU73mdIi8dgINg/WW3ai7GDHX33ldaqHPwZOdHaS5mzTNQxdbDDNcWqHcVVmL3V/21xt0e/3w4gslPaxrpQU2fcfPUgf7TqYFjrpWbhXNCQNp6fu1vT9cXjxaRaevyEbHYHdoZxN446PgbLFFB7xKSPfr8df/qiecCVv166fcdqAOgyO0Q3wo3DfA1Umr5M+zzojuLv321XtbzygsYWQv6sHoV6rJg22/cU0qEINmZ9d+l+jberx1CQAvl+czEueX15tJtBOsZgmQJqjw4wNT2hta4KAuH2nnZk4fZa6v2cnzt1NtYfjO3cQuX+e/mb3tNeYk2o+83PO49p244o9V8yDSM2Ndn0nUdN0cdgmQJqj5zl1lvwd9J1n5AM3Ht9CvdCIhbO+Yd8DEIMhpoeQE2rNCgoL2h2Ho3tW8C5U2e3+zZDqWYRaUzDCKxYzcRW7YQdLxQIww0KqD2OI2q24V50zrYS9gj4EO7dgI5+0lfz5z31406c0HhiEoAnaKVQdrfX/UzuEondd8OhEwGXcegvftcdZX1zvRxmHp7pHCx++8d5UW4J6RWDZQqoPU7panqvlTHGnpKaCLQm9oU7+FHLk1idhhNvTF+239OLGc5fqPbPq43A5CEmo/6C5dyps8O6AP1i3WHP46d/3Ik5AWpZu4WSNtHepSN/3lEScJmOfpEZitaHIuUndLiiXld53gt2aZsORB0Hg2UKrF26ltUs2rxwKEGMze7AtxsKVb8vljw+a0dY7/cWvIR6+/TOzzaE1RalWVuaZ9PbUVyNuz8Pbd1qT9CBFi+rVT/5il57lsMp/zZXERz/e8UBfLX+iBZNUm3LEe0nlQhmHICO4j7dalLsXy/M2401BbE99oDiA4NlCiisHrwgzx5tcpZ9LJc7dTbyj9cGXtCPHcXVeOCbLerfGEcarQ7MWH+4xXPXvLMqpHUdqQg9t1ipptGK7UXNub0/7SjBnG2Be/u8UZuGHKjH0BFCXrNOY+Ww8tXzDp3AugMV2O/6jaYlmbRplBe+Pr/SmkbcFWAq81CYggiW2bMcWEWrlKZGa2yn0q3KL4t2E6gdMFgmv4orG/Can9zAQIKtyxtq4BDKqcmiw4FBerTxUMveuZoQUxG0mqjim7yWdwPCCTbV3vYPFASNf9b/NMixJNx477r3VuOOT5y5n0crG1DVEHh641C26St1K1J5w8YgRhTbGSy30Z4fyeI9pZivcWWVQH79wdp23R5FB4Nl8utgeV1Y799aWBXUcq1PfEHPmqbyQLy9qArbi4JrU7xTxgZSStQ0hhYsF1c1apKX+NSPLWvxhhMsN6iccjeuegw1+FP3H3ceNzYersRfv47MXZz27pkPZsZFre6idCQBdycNv8fbP87DHz7hID3SHoNl8ivcvMp6S3ABVttBIJEJTi57YwWe/EHbCRD05oq3VmiyHuUgweX7wrvVuPFw4EoCaoWzb76xKF/V8v6yLDrKhCJuWv/2apsC9yyHUgaupsmGvHastR1Mz/K9X21uh5bElkAXyuHGyjWNVpz1/CJMm70zYmUeiRgsk1/hB8vB9eCFnoYR/MHxg+UtZ587WqW/ep9a2HJEm55zZYpmMLfS/WnSKBVDKZx9s3XeZCD+epZtHewErXUnejADuI5Vqx8gOXvrUVzz7uo2z0fqQvuFedpOjR0vAn0b4VbuOeWJn1FU2YB1B50X5MHklhOpxWCZ/Ar3VufyfWVBVVEIdeKT/aW1gRdyeWb2rhb/nvDcopC2GS+UwWi4aQiRyCMNZ9cM9o6Hm78eq46SoeHuASwoq8PAR+ZEuTXUUQT6fWgV2h5wDSoNd/ZSIm8YLJNfWhx28oMIaNsE5UEGIE+EmVLBOs2+fbL6UEhVHryJyMCnMHZOtYMO/TVfq55MtXnUWityXdRe/c4qzW9nz9xYGNSkHnr04YoDzIMNS/tcTVa7xlTosX45xT4Gy+SXFoNoEk2Bd7No1Zx9c7G63NV4406fCDfWtYfZtewteCs4HvrgUy1Lx2l1HfDLN7XJNQ/Vp6sPRWzd93+9BVeHWHow2mZuKmz3CgsdScCeZY0P/aYgcsuJ1OJeRX6Fm08GANdPXxPEdlr+u1zD6YUdDol//bzH62s/bClu95nAIunmf2tbxmj6sgJ8te4w7psR3sAlmz28iHKGxpNbqE0ricTAoXeW7G/x72DuwERSqHnlepqBDdA+LUZnf17MCZizHMItIn9pVEzDoEiIXMV46hDa67ATqe1IKfHwzG2Ykec72NpdUo3sjKQItaB9hVu1orVXFuzVZD3h5jy/PN/7xY4exHosVVTZgGmzd4Y8wYveaP19sMJCeB78dqvf19X2x+wsrsYlry/Hwecv9b4+dasjCgp7lskvLXqWo7mdslqL30AZADKSEyKybWpmDbNnuaxWuzsNgPrg3d/Sl7y2PLzGRNn/Nhd5DZSDDRL11vOqdU+33v6+WBNo6nG1R/7qRv+VecrrLHh4pv8AnUgtBsvkl1YhbKCDV6RC8mBO+NHKl44n4cQbNQFOjq35+s6tdgdsdgc2HDqByvrwSuEpHQ5hIgo9DXbztf8HG3SGG0tqNYjUTfM0jJi/dxA9s7ce1XydCUEM4PtyXfBpW3r6LZJ+MQ2D/NIqkFy9v9zv65HqWQ6mCgNPhfoWbCy1bO9xlNU24f6vt+Dhi4fi1jNzsfHwCVjtEqlmI655dzVOy+2M9QfVnxyvenuVz9u+oQimnGKo5mw7iq2FVZh68dCglveV4hmJ38XmI5UYlZPZ4rm//VfbXkAtZlv8YHkBvlh3GNeNy1E9GJSa/emLjZqvU+sBfDuKOaMrBcZgmfzSKoY9WF6P7UVVGNE7w+vrkRqToXWvFUVBEF9hwfFa3PLhOs+/n5u7G3O3l2Cz6xbw0Ow0AAgpUI6ESOyVUko02RyYvqwAm49UYkC3VFw3Lifg+3wNsGqw2pEQxBzPatIernxrJV68ZmSLds3drm2udDixcmW9Bc/M3oVvNxQCAJ6fuxtpiTxNqvWXGZtx9Zg+QS2rtqMkmH1SjSZr+EXgHQ4JAwcWdmhMw6B24+8KPlKpEB1tdrVY9ecvN4X83kC3wWsarfjFv5a2eX6zIldyt87qafsKMBfvLg15nbO2FGPoY/M8f/dD327FZa8vx9+/2+b3fb5+emdGaNKehxQDvhosdtQ2qZsgJhC1PcvPzmmerGhbUZUnUHZr6mDTmbeH7zYV4av1h4NaVm2ai7uOsla56dPm7Aq8UACc3bHjY7BMfrVXOm+kSmMGk7Ost9JX1FKgr6dc48F/vtg0DJp8/U3vLN3v/YUgHC5vmzu9vbgai3eXosnme8ITXxeqwQax//wp9EolJ/9jXsjv9UXt9fH0ZQUAnDntf5mxpc3raiewIXVCPfzqqUrJjuLqaDeBIozBMvmlZY+vv3qa4eQst65Xq2QLYjIM/Rxyw9NRg/5APYXt9Vc3ahg0+epNUzsNt9uyvcfxr/ney/wVVzXi3i9918kO9+7xohB6w0urI1fbPNTfQXWDFWW1TRq3Jn4F28Ov9k6Ae/mIzAoaok2H9ZHeRZGjSbAshJgihNgjhMgXQkz18vr9QoidQoitQoiFQoh+WmyXIk/LnuWH/AzkCSco93cLLJ56lgMNooxVgb6d9hrNrsXAMTdfqwo1f/JYgODzYHkdKustXnP4A12ovjBvN857cTEOlHmfMdEaQo/7+GcXYvm+46rfF4xQvyXO/KatYHt+1XYQu387ejps10V5qnqKvLCPDkIII4C3AFwMYBiAG4UQw1ottgnAOCnlSADfAngx3O1S+2ivA5K7dytQDU21gmn/1sKOMRr61x9oO3uf1kIdbBnoFucD37S9dR4JUsO78eH+rn7c6px5MnfqbABAWpL/QWi7S2ow6qn5+Hxd2zxSfz3LX+cdwTtL9uNQRT2ue3e112VCraF987/XBV4oBF+sDS5XtrU/fpancUviW7A/d9U1z12La5GG0VE6SijytLiUHg8gX0pZIKW0APgKwBXKBaSUi6WU7oS6NQCCGyZLURfJY8mO4iqUu257Gl29W9N+DH+whVIw7X/yh52oatA2SKe2Qu2ZvfXDyARVaml52zecNeVOnY17vtiEM55b6Hku2Dszi3eXotHashfMX8/yi4q7Nha7A6dNW4AX5u1uceGjp9xRAPjCywVBIA6HxJqCigi0xjeLzYHb/qOPfTsS5u88FtRytY3qUo/cx5Gr31mFijrf4xUWBLF9CwdvUpC0CJZ7A1BWAC90PefL7wHM1WC71A4iUZD/H//bjtlbj+LS11d4aqy6T9iBZttT65dvrghqubFPz9d0u9SWnnIMQxFoJjI1fF04hPIJ1TbZcMenG4JadtHuUny86iAenrkVK/PLIKX0G2grZ06sa7LheE0T3lmyHx+uPIC/zNiMIxX1IaVhRFKSSf1pbcAjcyLQEv8q6ixYvCcyqSixpLQmtDzx3SU1OP3ZBT5fv/2TwHcKwp1ZVGuFJ+pRWtOcUnXzv9eios6CrYWVHTbNLlZoESx7O9J63QOFEL8BMA7AP328focQIk8IkXf8OA8ieqD5bFhS4pPVh/Dx6oMAmg9W0S5RGesl5jbGwAATb2MtNx4+gbOeX6S73klvbvtovXYr8/Hn1qjsZQOAA8e95xL7siK/DF+uO4KbPliL/cfr8PrCfUG9T/kbeWb2Lny3qQiL95Tq7reTmWKOdhOCEu1jnl6oTYVQXmiGG+xqeQGshSvfWoXx0xbiLzM2Y2dxNZbvK8P+47X47X/W48b310S7eXFNi2C5EICy8n0fAMWtFxJCTALwdwCXSym9XkpKKadLKcdJKcd169ZNg6aR3njOq67/l9Y0IXfqbK8DCQ+V1+HWD9fhjSBP5q1pWepL7656e1W0mxCQt97Uq95ehaLKhhYpBfHgUIX3ADfQQD1v1Ob5L99X5nm8aPcxlIRRmeL95QW6SmEqrWkMafrxqHAd8+K9NJ3aDhktO3DeXpKv3co04K7G8t2mIlzy+nfcGDEAACAASURBVHIAwO0f5/lNN6H2oUWwvB7AICFEfyGEGcANAGYpFxBCjAbwHpyBcuhV9ynmrch3nqjd6R0Vdc6Dg7dbwef9cwmW7j2O7zcXAXDeBvbn1fl78cdPmw8szEfTF3caxvYi54DKGkWQdzzEW7HRdpnrhKbWtkLfgxZ9Vfe46JWl+MZLmlJeGLMSPjsnvMkUjlREbtruYBUppg6PpVvV7lKagx+N76xEtal+Wt7HCKKyaLs56KPajPJi9A+f5CF36mzPWB9qP2EHy1JKG4B7APwEYBeAr6WUO4QQTwkhLnct9k8AnQB8I4TYLISY5WN1pDNap2G0HqzlXr97ViZv3D0vj32/3e+631ycj592HMOYp+djT0kNhv3jp/AaS5pyOCTKa5tw2RsrYLM7cMoTP0e7Sao1KEpEnfPCImwPcTKCZX7Kpr3nmphk37Ea/P6j9Vi8pxTvLt2Pvcdq8eC3bcsvvrLAe33lePHW4ubeweQEYxRbop14qtKgNotH0xKOOqmyX1zZgIkvLQm4nHvQZFOc342IBk0mvZdSzgEwp9Vz/1A8nqTFdqj9tdfBJMHo+7rNPZNY4QnfvVgPz2wZRFzzbmTTEu76bAPe/PUYGJl4GDS7QyK/tBYAcKJeP7fu1Rjz9HzsenoKSqsbccTP/hiOn3cew6infkal6zNaGMYU2PGgUXEBM2fb0Si2RB1/AfGHKw7g83WHseivE9uvQVESyTSMM59biFUPX6DZtiNF7ZiNeosddofk+acdsQo7+RWpg4k7r9C9epOfH33vzGQA/qspfLnuSIuBRqEMlAqGlBK5U2dj7vaSkGdb01pVjASeDglcP905SOX7TUVRbk1oGlxl18Y/G9kc60oV32m8nzBnKval7ze3GS6jW/7io1X7y1FwvC5me5hTzcH38Kuvsxz88sVV/vPxU1S0M5LUBsuTXl6KSS8vxcMzt0WoRdQag2XyK1LTvx6rdq7Xk4bhZ/as7cXVKKps8DNZtjbyS2t8vvbST3vwyvy92KKYwCSUwViRoJdbiYHsPdb8+U6b07aedmV920EsO4o7xoQxkRQLlUTay90TB0a7CUHzFyRWuvJUY3VgV3pyQsTWreXefuGwbM3WFcqFTe7U2ThYVgdbCMnTB8rq8GUINcUpNAyWya/ff9w+s1oFmlPhwxUHNJ1625tPVh/y+dqbi/Px5uJ8NCkmdHha4wlUQqWHQVbBuCnADIPXv7emTWWAcAavUfzRMp810vy1teiEs3NAOXgxlqi5gFM7s6f7YxvZO0PV+9quR2p6dzDUXa+4qgGHykOv4LLvmO9OnmCFcncyVu96hIrBMrVwqFxdzdZwuSsiBDrJqbktHapAv327Q7YYmHXCS09oNAQ78Yre7TlWg8GPzsUr85sHrDXZ7H7eER3KSQNIP576YSfeXVoQ7WYETXm8aV3msrbJhsQEA44GSCPQo8W7S1VNNKI25HKfK6xB9sb6Ctxfmb8Xz8zWrsND7YWau127j9aE1Sl14SvLwrq7tL2oCqc+9TO2FQZ/F2/FvjL0f3iO7iYkiiQGy+RxtKoB5/1zSbtu0z2qN9CPXUJG/HZzMOkMby3e73m8VcXBhYL32sJ9niDZX3pOtIyfFl81oWPFD1tjJ18ZaBlcfdcqh7/RaoeUoc9uF037/KSzeaM+ZxkwCqCuKbgL6Rumr/b6/CGN63GrPT25p53XIp1v7YHykOudr3SVc12RH/xEcIt2H3O9pyzAkh2H/s5EFDXuup/RuFp8f/kBv6/P3FiEjYcjO9vS52vV53/F262o9vLGQmc5sAQ/JQWJ3B78ZotuanUHO4mSMrhauvc4cqfOxqHyOjgcEjaHRJPNgVKdjItQQ6gcXbLvWK2q5SUkDAYRdArFeh+pXCd166Rqu4E8+O0WVcu7g2W1kwp58+v31+LUJ3/GLf/2n+rmjfuC7O3F+z1tCmTdgQoIAOsPVKjeXqxisEwe7kEG7koS0QwEhfA+j3okSdlycowGix02uwMlfm6F9n94Dsprm2C1O3DnZxsAOAdFztpSjCOxMpOYDr25OB8DH5mDNxbpa4Yt0qdvNhRGuwke/5q/Fw98EzhwUvao/rjVWfKu6EQDLHYHjK4BGoUnYu8YonYyqNnbjrZJQ6mqt2Kzj6mopXROYhXuNOtbi7S9M/i/zcWqJgtxT9Vd3aBd3vSyfep7evcfd16sSLQchP3AN1s8r7V2qLweEs6LPF/+OW831sVYMJ2Q1XeYr9cYLJOHzfXjdecRF/iYUag9SKntqOdgnai34KcdJSirbcKop37G/325CX/4xH8+2f99uQlf5x3BvO0l+DrvCN5evB9//nITznlxMR77fjs+XOG/15y8sztkTN6GJvp2Q2HA2+vKzoiczs7ymFUNVjRZHZ5ygLG4/6sdsAcAjTZ3R40Vr8zfi2fn7sKVb63ET9vb1s2W0tmZEm5annuCDy2NfWYBGix23PrhOuROne13Wfcd3GB7c4P1dd4RVet0dwbZHA5scV2g5JfW4tsNhZ4Sn2sKyj0TMlU1WD0lNH0NTKxutOKtJftxx6d5MXX3VZjMyb5e02RSEuoY3D3LVQ1WrDtQgeve857r1ZG9u3Q/Zm5szh+cu70k4HtW7S/HKtc0uw/P3IbROZme1z5d46yw8buz+2vcUieWDSPSp9NdtbgfuWQofndWf1Q1WNG1U6LndeVP1z3BTZ3FjkabHQYDADuw/sAJHCyrQ25Wans2PSyhpPEt3HUM5w/tjpGtZvW8d8ZmLM7JRHZ6EoSrt90hJQSEqmPfmoJynDGgKwDngLZAHSDhOPkf84Jazt0Dr/VsfA99uxW9M5Nx1klZQS3vLk/YaHV4Sroud/UY7y6pQaPVjhumr8GTlw/HjeP74pwXFsFocPbsN1jtqLfYkGJuGUpuOVKJtEQTrDYHthVVYWSfTLTmDqJFpMtcBan13Y3W2LMcIrtDtpj6Nlx6uPpy39Y6UtGAo1WxWbIoXMpAORR2h0TeobY5ct9vKsKBsjqvOYiBDvpztx319Pa3dttH60NrKBG1i2fn7MZ7ywow9pkFnsFUgDPo65TYMshosNjQaLXD4AogLHYHJr60BI1WOyw2h8+8bCklHA6J2z9e3yaX12JzYNne436D2A+WF4SU872npAYLdh6DwyFxtKoBVfVWFFeqz7PedLgS98/Y3OZ5gxCY8NwizFN0WtgcDtU9yzdMX4PcqbNhtTtw2Rsr2q3KyMJdx7B833HXgE2JdQcqkDt1Niw2h+dObiQGyb29JB8r9pVhZ3E1Nh0+AYvNgdyps5E7dTZW7y/3DNADgLqm5v3FXarQPdFP0YnmsnbFlQ3Ye6wG1Y02T4nPJJOzYktRZQPeXNScq3+ovB5WhwMOKbGjuNrzvMMhPTnaT/+4E798c0Wb7zFQ0GqzOwJ+9zWNVtUxVWOAixbjE088oWqF7eWZf73xxArTKBQcr8Xp/bvi9o/Xo6iyAWP6ZuL95QVIMZtgsTvw6HfbMDInE40WOzYfqUTfLinYUVyFqnoruqSaMXXmNuworsJpuV0wfWkBcrNS0WR14IlZO9A9LRF1FhveX1aAkTkZyC+txYaDJzCgWyec/9ISfLzqIM4Y2BV3frYBx6oaMTQ7Hf9ZeRAHy+qwKr8MN7y/BmW1Tdh1tAavLdiL8f27YPX+Mpyot6J3ZjI+WnkAyWYTUsxGPPDNFnRKNMFoEPj3igMY0TsdRyoakHewAn26JOP66avx49ajOHdwN0x+ZRnMJoFhPdPxw9ZiDO6ehkarA28s3IfemSn4blMhrnx7FYZmp+NoVQOO1zShV2Yy7v1qE7YVVuHUnEw8N3cXMpITkJGcgDnbjmJw9zTkl9bixXl7MLJPBmZtLsK0ObswYWAWbvvPehypqENWWiL+u7EIP+8oQW7XVJ8DI0i9eTtK8PGqg3h/+QGcOTALZ72wCCVVjSg8UY+r3lmFVLMJRZX1+M/KgzhncBZW7ivD9OUFGJKdhqvfWY13luxH11Qz/re5CKfmZMJkELj49eXY6CUwJyJ9cd95mrmxCJX1Vvz2P+vx6/H98M2GQk8Po0EA4/t3RZ/Oyfgmr/n5RJMB24uqsLO4Gnd9vhFzt5Xg5gn9POs+49mFmDZnF15buA8FZXV4a/F+/PLUXpi1uQjZGcl4ft4uPP3jLizdexzDe6Vj19Fq5GalYvX+cszcWIQEo8A9X2zCB8sL8KvRvTF3ewmGZqehpLoRMzcUYkh2Og6U1WHdgQoM6NYJS/ccR2W9Bd3TknDatAWYtaUY3dIScdMHa/Hu0v3YebS67QcQwFVjemPZ3rI2k7AkmYyw2B0Y378LRrnu2G08VIlFu0thdUjVtY0nDOyK/4bZIaLGrC3F+G5TETYdPoGthVV49PvtAIDqBise+HZrxLZ7pKIBMzcV4fO1hzFj/REcKq/DHtdAyv9uLMT/NhfjvkmD4XBIvDx/ryflMS3JhOvG5eCFebudPd4CGNYrHfO2l2BAt1SkmI1Ysa8MFlegn2Qy4pJTeuKHLcV4dcE+vLkoHzeMz8G8HSXYcKgSNodEvy6pOG9INwDAqwv24bf/WY9OiSZ8uuYwDpXXI8EgUF5nwbaiKnROMWPkkz9j0+FKXHByd4x6cj5uGJ+Deosd7y87gKQEIx6ftQP3frUZ1Q1WpCcn4Fh1E7IzkjDsH/NwuLwefbuk4MznF2HTkUpcOaoXKuutSDYbsTK/DL9+fw1G983EX2ZsxqerD+HCYT2wtbAK+4/XIT0pAa+++Q4ee+DPT3r7TIUeejS9Sew5SPa89VUAQP+sVBwoq4MAcObArli5vxwmg0CvzGQcrqhHcoIRg3p0wtbCKkwc0g1bC6tQUWfBqJxMbD5SCaNBYMKALliRX47MlAScN6gbZm0pRoLJgL5dUpBfWovMlARPLd8Eo4DN7iwkJuDMnU0wCgzpkYadR6sh0Vwj02hw3g4yGQTSkkw44VrHpSN7YvbWozAbDbh8VC98u6EQRoNAv64pKDhehx7pichMMWNPSQ36dknB4Yp6GAWQkWJGRZ0FCUaBC4b2wLwdJUgxGzG+fxcs2eO8NWI2GdpM3nBK7wxscw1YSDAKz+CBs1yfFwAM75XuucpLTjCgwdq8DrPRgPRkE+otdtRr2GNOzZISDGi0OpCcYESD1e7Zt9zc+9KUEdktelJSzUbUtfpOfjmyJ37Y2jafj4hiR6dEE2oVPXv3XjAI5w/tjpv/vdYz0Nqbb+6cgPLaJozt1wWnTVvgeV6I4CbHePLyYXh81k7PvxNNBthdVTgAICM5AZOH98DXec6Bk4N7dMLeY7XonZns6X08qXsnFFc2eM4XRoOAw6HtfKIm1+3+cwd1wye/Hw+b3YEJzy1CeV2T6lJt1NLup6eg3mLHGc8u9FyY9emcjB/uORvjn10Aq90Z10wZkY0ftx7FpJO7Y3z/Lnhx3h7PfpKWZMKbvx6DL9Yews87jnn97s85KQuf3n46ymqbcMWbK9tMtNMl1dziIikpwQApgeyMJE+v9uThPfDTjrY55gbhTGdKNBk86SyZKQmoqrdCArj+tBzMWH8EGckJGJWT2WZA4tDsNOwucQ5qHNgtFSte+gOaju7zmhcSE8Ey0DIAbC3ZbPSZEqF8n2vMhOdH5i3odEsyGXx2yxsF4G5KkskAi93hWac7IPLWZvcXC8ATMHm2p3if+wABOIN1o+Lfrdul3IZyHe73BvPtmo3Cc6VoFAJ2ne4TkSaEMy/Jx24WUWaTAVabw/N9KfeV1oI9IRKRvrU+Zt9xbn+cP6QH7vg0r0WwbDIIGA0CTTZHm3NA64BbSXl+SDAIWBUHFfdrZqOhTQUL5XPKQMTdFvf5SHkujCSjEFj0wHl46oedWJ5f5vO8TS3jGl8xTqrZiBl/nACzyYBfvb3SU7M6KcGAT39/On730XrUNNpaxCkj+2TgzIFdW0z8k2o24tmrTsE7S/Z7gk6g5TlqUPdOeP7qU3D1O81joMxGd5pR252ndQzi7kRq/VgASFD8fa07lZTxT4v3tTp/ppiNngu+ox/f5zNY1m3OcmZKy7nl3T94b3+FMlA2G4Xni1C+zygEHNIZgLiDZovN4XlsMgiYDM3v8xYoG12flvL7bbQ5WgQ13gJl98jmFtu2O5BoMrR5H9CcO2wQzi/b5nAe0Ly1S3khoFwH4Hyv8m9yfy6tP0PlDhuvgTLg/AFFI1AGnPuie9PJCQZP6Shv4vgrIupQmlods+tdA/xac9ddBtp2gHirN+w+7Cs7a5SBstlo8AQP3kq9Kc9PTbbmUnZCoEXJtvY6XhoMwB8+ycOyfccZKPthNAjYXd+nAHx+Vo02Bx75bhvKaps8+fGAc3/5eNVBz76hrKpRVW9tk9dudUhU1FlQeKJlb7HyHHWwvA53fraxxesWu/TEHSaDgCJM8cQg7qeU+cnKx1Lx9yWZDG3uvrozAtzc8Y+ybQkG4QmUDb5Puc52+n85enwFC4F+m96uVICWQaAyuHU/DqZmo5pBvsqDlPILdj+0OwLPSKd8OVDtSl+rUv5d7s+GsZa+NVh5MiCKB62PxQ0WO5qsDr8XxK2rJ3g79gc6nQVTC1m5Hff5M1oX6la7xN5jtc4KC3bt6hK3B3cPp7+7hVppHUz6W67J5kBxZWPL+MQhPTW/W6+jwWpvk1NusTmwtbDKM+OqN1a7RFW9xefrvmIvNR+VrywAdxxmd0h4a6G1dWzmJ9VCtz3LRERE8aTBakeTzQ5tM387jtogZ+3TE/c3qbcc6+LKBpRUNbToPXYH9d40WO1e8+i/21TkufPtjdEgfHZixhIGy0RERDrQaHWgyeaA5M0lr5iCph2bXWJNQUWbIN5XUN9kdfjMjW+dAqHUUeYC0G0aBhERUTyx2Bx46NutLcaaUMfWHukZ3piMApsOB1961Gp3+K3Q0tGxZ5mIiEgHCk84S2V1lN44CixaX7XDIf32CLdmMoo2OcvxhMEyERGRDhx01ZVlqEyRpnY+BZPB0KLcbbxhsExERKQTzMCg9uCedC1Y8b5fMlgmIiLSCWZgUHtRs6vF8xwMAINlIiIiIvIj3vPoGSwTERERkU8MlomIiIiIfIjzLAwGy0RERETkmxDO2fjiFSclISIiIiKfHBJx3b3MnmUiIiIiIh8YLBMRERER+cBgmYiIiIjIBwbLREREREQ+MFgmIiIiIvKBwTIRERERkQ8MlomIiIiIfGCwTERERETkgybBshBiihBijxAiXwgx1cvriUKIGa7X1wohcrXYLhERERFRJIUdLAshjADeAnAxgGEAbhRCDGu12O8BnJBSngTgFQAvhLtdIiIiIqJI06JneTyAfCllgZTSAuArAFe0WuYKAB+7Hn8L4AIhRPxOMk5EREREMUGLYLk3gCOKfxe6nvO6jJTSBqAKQFcNtk1EREREFDFaBMveeohlCMtACHGHECJPCJFXX31Cg6YREREREYVOi2C5EECO4t99ABT7WkYIYQKQAaCi9YqklNOllOOklONS0jtr0DQiIiIiotBpESyvBzBICNFfCGEGcAOAWa2WmQXgVtfjawAsklK26VkmIiIiItITU7grkFLahBD3APgJgBHAh1LKHUKIpwDkSSlnAfg3gE+FEPlw9ijfEO52iYiIiIgiLexgGQCklHMAzGn13D8UjxsBXKvFtoiIiIiI2gtn8CMiIiIi8oHBMhERERGRDwyWiYiIiIh8YLBMREREROQDg2UiIiIiIh8YLBMRERER+cBgmYiIiIjIBwbLREREREQ+MFgmIiIiIvKBwTIREZEOiGg3gMgHg4jv/ZPBMhERkQ7IaDeAyAeJ+N4/GSwTERERkU/x3KsMMFgmIiIiIj+MhvgOlxksExEREZFPJkN8h4vx/dcTERERkV8ivjuWGSwTERERxROjyuDXIeN5eB+DZSIiIl0Y0SsdAAdTUeQlm02qlrfZJTolqntPR8JgmYiISAc6p5oBACa13X4xzhjv9/ijQAggq5M56OXtDokuqcEv39EwWCYiItKBRJMBL117KhKM8XVqtsf5Lf5oaLI5cFpul6CXN5sMSE00RrBF+hZfv0giIiKdSjQZkWgyxP1gKl/ivXyZljKSEjAqJxOmID/TpASjzzQMf0F0R/nKGCwTERHpQIrZFSwza9mr5ITY69nU6zeZmmhEz8xkJJqaw0D3xYj7Yk2I5mA3OcGIzOSENuu5eUI/NFodPrfjkGixjVil27/AYmv+8M2KD9rXVVBSgsGzrNmV76W8k6W8IlU+dq/bbFS+z/s2EgLkkSUYhWebyp3DbGz7OMEgPOsLtN7W3J9BglG02JG9tVP52L2sySC8Xu0pn2LPRvSYjYYW+zwRxYdksxGJCUa/x9/WgYe3c2Iw55RgzzsGAc+50aw45wTbI6mFJJMBl43siSabvd22qQWB9p8iOpj8b7PRgFNzMtEzIwkGxfdod0jcNXEgUl2D/wScwS7g3De7dEpssZ4kkwGDu3dCepLvgX/pSSYMyU4D4L2XOcEovO6LvvYv97NGQ3O8ZTSI5gBfsaz7t5JgFF4DduUmzEYDIHx/eLo9I9c02TyPLTaH5w+1OSSEaBnMpZiNnisbi80Bi9357dodzR+W3SFhMgiYDAJ217efnGDwBOUWu/J9Einm5uDT4Nqe1fW68otVBqnO152vNbnabBDOdQPOL9/92GgUnvVZ7bLFF6l8bBCtgnujATZH8/vcqV4NVrunzVa7hMF1RejeBtC809sc0vMYcO7wgPNH7f7b2juFTC+xeSSP/63XrdyHld+5xe6Aze7wuhwRdRytb1+nmI2e47GS8vigPDYP65XuOa64DxMC3s9VrQcN+jvGK885QgjPudFil554wuaQLTqCIsnmkHjqihG449wB7bI9rUQjE9uo+J7dnYitmYwC900ajC6pZjgUwUBaogmTh2d79qVEU/P+2TnFjG6tgmWTUaBLaiJyuqT4bE+fzil448bRAJpjEJOis9Bqly3iFHeQbHO0/fQMovkzdcZxwvPYHeC7XzcanHGYextNtra93w4JpLriJovdd+84oONgWenKUb08f+jdEwc6f+QSuGhYDwBA97REXH5qLwDAfRcMwkndOwEA7jxvoOd9d503ADaHxLBe6fjrRYMBAAYhcMHQ7gCA03I7I811dXTu4CzUW+wwCKBP52Q4pPPAcuUo5zasduk5yLmvdI0GgSE90jyB+GOXnowmmwOZKWY8cslQAM4v37290TmZOHdQFgDg0lN6osnmgBDAuH6dPW3+64WD4ZDAWQO7eg4SFrujxYhU9wHwj+cOQL3F7vlbHNK5I9x+Tn8AQN8uKZ7Pq1snM7qlOXf6/lmpaLQ5YBDAyD4ZoX5FYdPL8A4vv0/N1z3ItX9K2Xwya7I50NU1Mvm+SYM8B6m0JJPXnoKHpgyJXEOJKOIGdkttk26RlGBEsrltqkGTzeEJoi12B9Y+cgHWPHwBZtxxhieQlWgZTADOO6eZKc5b5zZFQPLZ70/3BCMCzqAqwSiQ0zkZgPOc8+dfnAQAGJCVivMGdwMAXDIi23OOu/60nIABRrjcd9guG9kTXVLNeHDyUEwY0LVde7VjjfKuvK/0iHqLHTmdk9EtLbHFd9g1zYzBPTqhweqMJexS4uYz+gEAuqWZ0TnV7LnLADgvpDKSE5DbNdVne7IzktCvayoOPn8phmanQcAZC7kD5NyuzYF2r4wk2BzOzsNJJztjpbQkE/54njP+cciWnUfuHOrLRvZErauDdXROprPtDmDar0Z4Xr96TO82bZs8vIfnd3DpyJ4+/wYA0G3RvP5ZqXjosmE4NScTY/t1xqAeaThnUBZG9snE2YOycFpuF9Rb7DhncxGuOy0HAgJ/v/Rk9EhPws0T+sFsMiAtKQG5XVOQm5WKMwZ0xdmDumFcbmdICWR1SsTFI7IBAOsOVODCYT1Q3WCDhERmihmP/2876i12PHrZMLy1KB9nDcrCWQO74tpxOeicYsbB8jrc88VGPH/1SGQmJ2B3SQ3unjgQ+cdrkZlsRnZGEk7pk4mTe6YhxWxCitmEi0dkw2wyYMOhE5g4pDuqGqxosNiRnZGEgT/vQWqiCbefMwCPzNyKG8b3xei+nfHLU3shNysVDofEOYOycObALKwpKMcfP92AOX8+B0ajQEqCEZ1TzejdORk90pNw0bAemLWlGBcNy0ZSggE3ju+Lgd064USdBb8aXY4pI7Kx7kAFthVV4Tdn9MMHKwpwap9MdE4x47I3VuCk7p1w0+l98eQPO6O8F8Q+g2gbgH/429Nw52cb8Luz+iMrLRFP/bADT185AulJCaios+Dcwd1w5ajeaLTZ0T8rFUMenQcA+OL203G8tgmXjewFo0HAIASen7s7Cn8VEYXqvZvH4sctxbj7/JNw7burPc8bhKtnOcHYptf3zxcMQpeUBDzxw048NHkIeqQneV67/rQczFh/BOcOysKyfWVISzJh3SOTcKy6Ef26puDtJfvxz5/24OoxvfHQlKGw2BzI6ZKCTY9diP3Ha9G3SwrGP7sQJ3XvhP/96SwcKKvD8F7pqLPYMWlYD4zsk4kTdRbUNtmQ0yUF+4/XIis1ERkpCZix/ggA4JPfjcctH64L+TN59fpR+Hj1QWw6XNni+UST8+7vOEXVhhvG52BLYSVgc3jtffTnh3vOxi/fXBFyO0P1f784CTldUvDQt1sBAC9deyqW7CnFj1uPtsv2H7tsGJ7+seX53GQ0IM0gWpyfememIMVsQmZKAspqLeiaasY5g7Lw6ZpD6JKaiB7piUgwGmCxu9JhJJCebMLwXumYtaUYvzsrF3+7eCheW7AP7yzZDwAY6krBAIA/nDMAz87ZhTd+PRr3frUZx2uacN+kQRiSnY4uqWZkdUrEr95eiV8M7Y57LxiEF+btxl8vGgK7Q+IXQ7pjRO8MvLd0hI+cJQAAIABJREFUP15flI9Xrx+FM0/qCqMQ6NopEb0zd2FQjzT8Ymh3jHl6Pp68fDhuOr0fbjrdGezvPVaDRJMRj152Mr5YexgpZhOuG9cHZbUWdEoyoclqxwd/9f0ZCqnTki3jxo2TeXl50W5GXNlTUoPJry7Dv28dhwarHfd8sSnaTeowFj8wEdnpSTAZheqyUEcq6tGnc7LXdKp/ztuNt1wHJSLSp3d/MwZ3frYRWx6/CBmuQVJ7Smpw+ZsrWtwefubKEThvcDdMfnWZ504hABx47hJ/6ZQeMzcW4opRvduMu2m02pHkZ3DcmoJyjO6b2eK2ezDqLTYICCSbjXA4JAwGgefn7sK7SwtUref6cTlISzLhgxUHWjyfZDKg0ebAV3ecgTMGdAUALN5Tij99vhF2h/db674MyErFogcmInfqbFVtC8fyh85HosmAbmmJEELgWHUjps3ehdduGIV9pbW46JVlEdnuXRMH4vdn90eq2QSrw4FOZhMufX05SqobseSB82GxOzx3l0954ifUNDp7Za8fl4MXrhmJG6avxpqCCpzaJwOv3jAa57+0BHdPHIirxvTGpJeXeTqBUsxGzLv3XHROTUDewRM433Xn/Ov1R/D4rB0wCODpK0fgqjF92rTxvxsKsa+0FlMvHhqRz0CtuiYbuuSejKaj+7z+0GIiDYPah/sAm52RhEHd0wIs3TG9dsOosN6fmmjEVV5u9/TPSkWy2RhS/dScLik+T5QPTtHHgYaIWurqSpdbcP95mDKiJw4+f6knUAacPcnuYM+d+5tiNiIxweDJI+2dmYxdT00JKlAGgKvG9PE6QN1foAwAZwzoqjpQdrbX5EkbcQ8UC2U9V4/tg4e8HMsyU8w4+PylnkAZcOa0SqmujNyOJydj0QMTAQAbHp2Em07vq7qNwTrHlV4JOI/d3dOTPN9fj/QkvH7jaAjR3GmiXF4rk4dnI6tTIpLNRqQnJcBgEJh737nY9I+LkJGS4AmUAXjSTwWAXpnOOxbXn5bjaX9fVz7y4B5pGNitE6YMz/Z8x41WO3pkJCItKcETKANA/26pMBicucSj+3b22sarx/bRTaAMBP6NMFgmD3f+bHpSAoZkp2HPM1Oi3KL2NyQ7DYsfmIgDz12C03I748HJQ3D72f39vufmM/rhyz+cAQD46Lbx6JOZ7Hnto9tOw9d/nBDRNhOR/qz7+yQcfP5Szxia1pQBcOdUZxCdmmhCosnomaTjpO6dvOYw65na6k4AMKJ3OswmAw48dwk+uu003HvBIADA+7eMa7OsgICEVJW3nKqoD9y1UyKm/eoU1W0M1ke3jcffpgzBKFfurC/uzymUiwt/fvy/s3GqivFHnVOcF3XJZiN6uc5d7ouTU3pnwGgQ2PDoJFwxqheEEHj1hlGePOeM5ASv7R/ZJwN1TXb07pyM/lm+85n1JNDFl25zlqn9mVxXuulJzgN3e4109iUaZXdyOqd4Dqzf3HkmAOfVc+vbg26/GNodj102DAlGgddvHI3TcrvglN4ZuHpsH2R1SmxxkCZ1Lj+1Jyw2iXk7SqLdFCJVXrn+1IAnX+XLx6qbADiDj6QEg2cQnTI3OVYE2wuulOQKuIQQmDikO84Z1A2/O7t/i5745vVDdc+yN3ecOwDTl6lLFwkkf9rFMBoE7pp4Eu6aeJLfZd09y1pfDI3orW6gfp/OydhRXA0BYGQfZ4DfMyMZ064cgcmucV1dFVUwkhKMyEh2jq8Z6ONCMNFkxLu/GYvhvdJD+yOixF5TfsTXa+xZJg/3scdzWybKNcvaO1A+NSfTa3Dr7/bMh789DWaTAUIIT0WWpAQj+nVNZaAchnduGoPXbxyDCQO7Bl6Y4t7TVwyPdhM8vr1zAn41um2OZmsGxfH17okD0adzMgZ0S4XZaIBDOo/HvTNjL1hW28ly18SBLWr9As5A2FugDDiDZYeUns6dULlLjWnlxatHqmpTgqdzSpt25HZNwZ8v8B+ge+Pu+c1MSWhxF+SmM/ohq1WpOLcBWakQACa6qqR4M2VEtt+ScnpkrztR6us1Bsvk4f7xtj5wtYc/BqifeenInhjT1/9trXCd0ju2roI7sgtdZQ7Vjnan+HTzhFxkdTIHXrAdKCs3+KMMlkf37YwVf/sFuqclufJZBcxGQ0z2LNtVFg1IUpmGICDazIXgzx/O8Z5Gt6O4StV2A/mVl7Eq/rjnaEj3cVGgxoq/nY/595+H+y9UX1K0e5pzH7tz4klB99afMaArJBBXnRkMlskjq1Mi9j97STtv03mCC/Qj7WQ2hX3bLZBgpph96dpTPY/PjKMDRXuaefeZnh4ahw6D5b3PXBztJpAXf4uxwa7KG3fui0M396357unee/b07KyB6gasqb2B6a7E0CnIO3d/v3SY1+cnD89Wt+EADCr/EPdEM/391CgOVu/M5JAGjwPARcOd+955g3z3Erd2ySk9MXFwN4zxMXivI2KwTC1EOiBtK7jtKUfvRkrrGa5aMxqEZ2QwoJ98wrxHJ0W7CZq4akxvHHz+0hYH4CQdDm7iVOT6dO24HNx13sBoNyNo/u7gpScloNHmQM+MZJ/L6NUpfTKQnRH8sVHtKcedHqimbJw3V4/t45m0Qgtq/w7399+nczJ+uu/ckLe7++ngq6V406dzCg4+fyn6dg0+ZWJYr3R89LvxUU/VbE886pNfM+8+M6Lrd//WHAFu3d19/sCIT8H9lwsH+3ztvZvH4r3fjEXnlOZbZnrpyYqV2ayWP3S+39efv2pkm+fcszgRBcM981gs8PezdV+U98qMvWAZCLYLxLWsyoDLvXh+aa2q93ljDTPgVgolcLx4RDYGZ6eF1UkVqOQZaYPBMvkVqUCsdWkbf7mp5wzKQorZFDCgDpe7Cog3k4dnY9KwHhjUI81zInNPeR5t7X83IDTKg7q3izBvPbZ67Vnr01k/7Yqjzp2APlp1MNpNCJq/2/buW/S+Brnp3dGqxqCXDSUNQytztke30s47vxmLrE6JqsvtpSeZcMuEfnj9xtERahm1FlawLIToIoSYL4TY5/p/mwQWIcQoIcRqIcQOIcRWIcT14WyTOgZ3YOQ+RNjsvgPhzUecU6D6y8l656YxLQL70/sHN8gmFMseOh/v3Tw26Jy5SEvzE+TridEgPL3LuRrk6UXDeNd+tcQ1wUGkPDQl+IE6Op2Etd1crZgd7MHJ6gc4RYu/IPGWCbm4ZUK/9mtMFAUzVqT1O4J121m5Gq0pstR2eMy771w8dcUITwUmirxwe5anAlgopRwEYKHr363VA7hFSjkcwBQArwohIlvWgDSj/kCmcv2u1Vvtvm+HZbp6V8b28z2Y4OJTenoed001Y/rN41qkTGht8vDsuMrX0oJRCM/I78wY7TFzTzBjMhpw8xmRCWYmD++BuyeehO1PTsaL14zEsgfPx7d3+p7YJt53Q+Xv3NcEIHrkr2f5/KHd8dQV2uXT6pn6nOXgl338l/5LCqodlBcpaicmifRdVmor3GD5CgAfux5/DODK1gtIKfdKKfe5HhcDKAUQ/LBLiiqtjyXuHrnWQbjdTxqGuxf6gYv89xq9+5uxeOmakVjzyAXISEnAqqkXhNdY0pQwOG8rb39yMgwGgYPPXxrtJoXl6StH4M+umcbU+tVo32Wmnr7SGSR1SjThunE56Ns1BeNyu+CP5w7AvPvOabP8S9ec2ua5eHL/Rc1jDcId9BUN/joB4oH6NAztTko6iZXRLS24SlT/uvZUdO1kjtn0nFgWbrDcQ0p5FABc//c7GkcIMR6AGcD+MLdLMapvqyLlPTOSkZ2e5PVKec8zU/Dg5CF4cLJzIF2g+s+ThvXANeNyPOkaiaxaoCtG15lJmb7iLr83ZYS2ZZzay/1+BoX6M8DPFLDuuqetPXzJyRia3bYWeO8w8qe9TSesxhWjeiE1yhVLUhSTS1w0rAcGxUjvsvuY99+7IjuIWu/UBr9axrehlluLBF+pGFeOak61uHpsH2x49MKYSb3rSALuKUKIBUKI7V7+u0LNhoQQPQF8CuA2KaXXy38hxB1CiDwhRN7x48fVrJ4iROsr79bry0hOwJpHLoC3juVEkxF/Ov+kkAOpaEyuEi1rH9F/L7q3k8ELV4/ELRP64d3fjI1Ci6Knh4/SWv1UlG9yS1M5A9hNp/f1PD6ldwau8tPL7Yt71rFxuV2QoKOL0qQEI07UW6PdjODwTnpItOxZfuJy/cz8CAAjeqejT2Yy3rhxNHY+NRkAcOP4vhjQLTbHeHQkAY+yUkqfRVyFEMeEED2llEddwbDXqQKFEOkAZgN4VEq5xs+2pgOYDgDjxo3joaQDEkLg7ZvGoH9WKi5+bTl6uoIGdy/L0Ow07C6p0XB7wQ2AirU57FvTS81nf7yd5HK6pMRMbqa3FIhQ+Trdq50qGAAG90jDhAFdsbqgPKjlR/bJwKRhp+HUPpnokmrGuNwumLmpKOD70pNNqG6wAQCeu2okTEaBcwZl4dX5e1W3OZKaQigfp+bz04oO59uJCtU9y4rFB/fohL3HQi8h170d6ver8e2dZ0KI5hzmf14zEqP7dsZXd5zhdxA8RV64XQKzANzqenwrgP+1XkAIYQbwHYBPpJTfhLk9ameRGOB3ySk9cXLPdGx87EI8eYXzyt4d0F6gcV3dWX86O6jlZv9Zu0CIvIv1jv4ePtIjQhHO4NAzBrSs9JJgNOC3AUb9u90yoR+uHZuD84d0R5dU5+yZ/gYLKScDMgiBy0/thVevH4VLR/bE5OHZSDGbdHUrGwhtivQv7zgjAi3xr0d6It6+aUy7b1dvQk0juun0vvj5L+f5fD2YijV623eTEowtBvtdOy4HZpMB3dOSYrbmdkcR7p7yPIALhRD7AFzo+jeEEOOEEB+4lrkOwLkAfiuE2Oz6b1SY26V2EskBEF1SzZ4Dg/uE/ZdJoeWA+hJM+/9z22mabpO8C7Ue9IL7fZ8Q25OmA4vCeO9Xd0zA/L+ciz3PTME5g5xTC/sbIKt01klZbdKTpJ9g+cNbm38bfTKT8fqNo3Flq7SNBJO+roIeviS0yYJ+f3Z/jVvinxAClyiq+HQ0F7WawtsXtWNL3L/DRy452e9yuX7GBbiprW9M8SusYFlKWS6lvEBKOcj1/wrX83lSyttdjz+TUiZIKUcp/vv/9u49uqrqzgP495ebmwchDxKSAHkQIBDeIRACAREICFhEfOCDikhboVpBnKIWq/VRrTJVa2s7ndaqo3ZatVM71nZpqzKtte1q66ut7z5crNaOU21rq46MKNnzR+4Nl+Se9z53n3Pv97MWizxuztnZ9+Sc39nnt/fvlzoaT+HTGSwPLUSSKX2tL9Z8p++m/XbFSOLkRxfYV8gzze9oqtMSgPecbb2smk6i8dC06gq3XTS5sRKlxQl89UMLAABv7LfP0506phL79qzF6hnD8//twuxZzdW4cWMXzl42CV/bmn30NVnkvWPmtNTgV5et8vxzbiycWOfr587t87eyCWXn9ubSbwU/HcWYuPwnuRWNqgoUWTqXczxtgfW6tP0BEvjsZpMXu7iQ58v5stXH5LA4cLqg1VbkJu9Q58iy1bbKfZaunWVzIwoAS6dYr9bpNCp9bOc42+IHfoKWf9syP7Tlr/zGUO/1x2/ZuShze1x4fb/SfztRWSMZAKaPjfecF3IWrYQdihydi58rmzGsIPuxW6e02MVjtuiccikbp/cnV++fziXSrK7zmcugeTFjXDV2WSxjN6m+AhfZPLIOOtFs65ETPf/MqFS+dDj8HRG1FSWOFd/IPbexrN8JfjpGlnWpDfV4pihgsEy2dI4s240QhlWQKOHiRMxHcdHm9PaMrSnLSe5hLo6Tq0+Y5ftnu9uGl3g/o3c8zljUZvtzVjnLbkvG+1l6Li2MwjReY6ibU2tNiwhWTB2eZ8v12v1xW5XO659V+nCNUKyc17nnNIBnAcqZXptcwrDKd0Zp9KGQfe5U/3N6nVZkKS1O4MlPHDXs6yfObR78ePUMd5ONcsUq8J7gYlKSld5Jddi3Zy06W2oAAN/dcQSuWD8Tm3vbbH/O6k8vnQ+t2wM7D195RncREa8jlSszJqItmFiLz55y+LE6wnDRlTj6zEmdOGupuycOXldcSqfL6Lp5vWSt/URBN96fsXY55SfmLJMtXTHshNEVaKm1zqkNa81RN4VJGE6HL9CFzcWPVpYl8eOPLcfbBw7i6M89iju3LkTPhFp8bE0HSosT+Mf+d/H9Z/+MLYvacNtP93luQrvmgC7MY+7aDbPxp9f3Y2aTfR5zmtWNqtu3zMt7+4uLVwyrUHhSdzOuvv8F19twEiSXNZkownFdTRhbXYbnX3kDPRPqsPOup+JT6CQiTpjX7PyiFLv0vGx0rzdc6nOeABUWBstkS9eI7+Ze68l9gP3yVUG4ScOg8AV5F9ymWDSPGrgZ+/3V7xv8WkOqWEv1iOTgI/8dfe3Y/vWnPBWhuHbDbNevdWNaiBOCpjRWYkpjpevXW92ohjGBKlsp721HTtIaLOto9oKJdViQehIWpYlkcbN311KsuP4R+xd5PPW/e1DvRMwj2kdr3R7lJ6ZhkC1dIewHFtuvYRpWGkZZ0vkQ91PEgLwJEm/4nfRmpW5kKXysdmZp+/J2zz+je6Q6CKuHL27fsqiFkrpjW8bK/k2qdz7OvZ59D7gIlq/xkPsfJPWJCgeDZbIV1ojvsP2EtN2aESW47qRO29f8Y/+BkPZOaW6W8LOTLr6hi87RwrOWTdK2LRM297bhptPnDVvKzU0KExC9YFL3SDAnAAdz1lK9fx/NNfZLZNZVlGBjD3OISS8Gy2RLx6Dr3NYax9eEGZNvmNeMOy0KKgBA78T8eQx30dH+qpdZuW/7YtyvoRR40ImWpy+0T+PxSmcA5HdLzT7L/OpWXpLAqhljDpsQGWe6Y1vOEQ7mhLn2q6V4Pfe31o2wXUUlrKeUVNgYLJOD4CeeC1Y7B3BD91Kned3K3knZV+I4YW4TyvNotvuHNY/iTG6oxPRxVcNWCPCqOGDEsSpL5bkgvDYnjFVVjpl9eKGP983S+zt6NbLMX7pLvo+8Mmc5GKfe8zrBz4nb0u9EXjBYJls6zjtucsxyle4x1GXHzDCy3zgoTyYGc76DxgthBJsTA+Qaeg2A7F6vK5b64mnz9GzIp7M132hl+unuPvzsohWhbT9MF6zu0LK8WKHK9b0G56BQGBgsky0dMaybNIxhXJ5gb93S7X3bKSNLi1E9IpySu/ng5O7mwVHDoKOHYQTLQQ5NNxM/M9n9+l7XiY2q9BOWH56/LFChkWzG1ZRjTPXwlTDCoPv9OHJKPc5c4r1KIaXZvx+6xknGpFa+4cgyhYHBMtkKOuK7dEo9KsucA1K/u0km3B/Cd287PG/5qUuHF7KgQzKvOUFj3TAeZQfJTSxPeks5sAv28+0pfXV5Ep8JmHbjlc4+1P1Yn4Jxem915Rinb8YYLFMYGCyTraCnHbfVr4aeMN2ODnkZRVowpIKgl0A7TnYdNUXLdjLfk5ZR9jPQndSEMIIf5Bo7qcFbCofdet0leXYc6b6xcbOSydgq76POG+Y14+cfz11qx4VrOnK2r3wS9r3kvj1rcXxXE06d3wKAaRgUjvw6y5N2QW/63U6eG7of12u8ejwT//ryVbj9gz3efihmdqyYrGU7mdeczpYajCz1NwEsmZBQinAEGUH8oMO630PZpaG4XWJt+DZ9/Vj4NLer1aZyZ5qfPkyIoDFLkB1WWky/iyDs61vDKREeZ04pXDpC2xtOmYNTe1oxsrTYdREjIi8YLJOt6eOCBTlHzxzr6nW5enRaVZZERR6tfhGmoSk4flMxslVt8+OfTzy80ECQGzmvgarT7z7Gx8hoPutpqwUArJreiCuOzY9JtG5GLMtYOnmYXIauD+xcgoc/ujSHe6RCwWCZbFWXJ7EzwEjlUdMbXb1uWOBjcYad01Lj5mW2KnyOkBaadZ2HL2022UMJ5UylxXpOMxvmtRz2eZBgWedqGMDAetT5IuiI90929+Ermwcm3iYTRSh2kabiZ59WN9i6jreh3OTC2qXrFCrHLtE4TtJSOwLj63Jbke+nu/tyuj8yg8EyOcrFsm4uY2Xce85iTKqvcH6hjaljKvG984IX2oiyoBXvypJFWNx++Da++iF/6SsLJtYGaktaokjQmXGztLl3PK53qM5oxeth47SaR2mx9xHFqBZPCBLuHTdnHJpqygdXmXn97fCqY1p136iKklD+vt2MLHNNZmdjh6yKUl9ZaqgleoyriUZxIQoXg2VylJNLus+d1PooXiIimDpGfw5tlLgd0beS7aI/osTfiPzVx89yfpFL5/a1D94s1Y0sxYnz/FWd87oUntPL/SxB6CYHNtdmNVWjPEAqwZqMtKubN3fjsnXuUjD85Bnb9V6VixV4vHIzssxY2VnmTc7nN3ZhZlO1ucYQucRgmSLBS85y+pVlySJ0+EwNyHdBAzGd13ydFd5WTGvE3l3LAm/Ha/51zQi9FSUBwEWtnpz7zo4jXKVNWFk6pX7w45XTG9ExJry/z6EpWWHbsqjN8TUcWXbWUHVoJDlq/fWlTXNNN4EiisEyOcrF0+KhsZ3dOTTdnuUdDXlfatevgwHfs3zvVy+/3xXHzvC9EoidqKZh+HFyt78R/jQ/h9umheO1bs+Jm8ftRbyiOvpsjtfwduOaEwaefq1xOSGdCg//tMlRLlaq8JIXnV4aKI9iDe0CjyxHPFZuqxuBOS3xfnyb+Vg/aLBp2qc3+MsdT9N9uJmqqhi1kdIoypxgHZXuyqcbVwoHg2VylIvUSi/5sOmTLU9w1oL2TUSuYZZ+eMFytDfEOwXnYMZ7FDTYjAq/wc85y9v1NsSQEKq6x14cTtO6lrek/MVgmRzl4mR348Yu7N3lbn3MIycP5EVGcH5UZBwM+KZZFYlgTp81rxMZozjBz5STulucX+SB26D9zq0LNe+X0XIcrZzWgKcvX2W6GRRhDJbJUS7SMGorSjCpfqSr1/5TqpxzGCWU80WQWLmiJIHmUdnzM2c353ZSVT5zs7oC+eM2ZO2dVKd1v0zDiCcRQWUIK6hQ/mB1BnJm4JrulHP4k919GMVg2VKQQOzHH+tDsUXJWAYD+gQd/Y+aS9ZOC1QQRCS3j+zbG9zdnHvBNAxn7CKKI44skyO/16/F7f5HbZxisqaact/r/haCvqkNvn92VEWJ5ShLOUuFW/J6H7Fwot5RTdPOXDIxUBqC1iDKxcb8lEVuqbVfEYM3k86iPoK7dckE002gCGKwTI78VvD7wkbmt5oys6kaH146Uft2q8uTmFjvvpzsBxa3aW+DLpesnWb7/R19A5POSkIqn3xydwuOHVJSvJBpDTRDGqH+gcMa34yV7T164fLI33BfvHY65rYy3YwOx2CZHPl9NMoLh1lhLZ9VU+5+ZOj9Pa2htEGHM5fY30z0TW3AfdsXY4PPKoFW7vjgobLh+ZWIEYzVpFI/wupXp4ItHFkejsc45QM+xyZHfk92ptY6pXAlPVR4i3PsUCQSyoTGxe2jtW8zHyQ0Hiym0sEZLBPlJ44sk6P6ykPlSZtcVLFKEx5dRoV13faWlhDf4MFr4OM22Itvj4RL5+S4XKzgkw0n+Nkb+ifC7qK4YDhDjs48YgLWpXIrvRS74InQrLD6v6RARpa9tn19l3P+8ROXrNSabpBPzls5xXQTAuM6y0T5icEyOSpOFKGuogRAPKoxUbiO6Rzr+rWFtJZwabHzxKW6kaWHfX5uXzs+dfzMsJoUK6f26CtMYi4Nw8x+iShcDJbJlUmpNUlzVWKa15zgwhrkOr7L/YS3/3v3YDiNyIFcDBJObqzEaQvGh7+jGNCZ72vqFo05y8ONiPjqF0HcuqXbdBMoRxgskyubFrTid586GqXJ3BwyfJyZH955r990E3xj4JNbcenvT66fYfm9smT+BoZ+NVaV4ZkrVptuhnbTxlahb2qj6WZQjgSKfESkVkQeEpHfpv4fZfPaKhH5k4h8Icg+yQwRQXGiCHdv68XeXd4X86fcc1qN5MS5w0eIv3feElfbTqflAMD5q6xzTUeNKLH8XtSNq3Y/mZWC8xIrP/mJo2y/73dteDfsNh3WmtxxN7J0YOGtfBoEyZ/fhNwI+pe9G8BepdRkAHtTn1u5EsAjAfdHho2rKcekev1lYjOd3N2M9y+I7vq8cbG0ox5zWqyXPpvVVDXsa+UuR8b+46zewY8zV0vJtGp6YyglhXPh/FVTUK25nPqjFy7Xur1CVlthfxNmKmc5waRlW2HexBCFKWiwvB7A7amPbwdwXLYXicg8AI0AHgy4P4oRv6MIn97QiXOWt2tuTeGZ31aLe89Z7Oln3D4Kz3xvrebwxWUQaeHE2mFfC2MErKV2hPZtUnalHOGlANyE9HE5v5EeQc8ojUqpVwAg9X/D0BeISBGA6wFcEHBfFCFVZc71bNyOUpIZ2QJCt5NxMn+yXyl0ZSkPG5eiNNnauW62/zLUPO798VLsxklDVRnu3LpQ2/YyWY2OTmmM51MU8ofBcmFxPDuJyMMi8kyWf+td7uMjAO5XSv3Rxb62icjjIvL4a6+95nLzZIJTzuDa2WP5SDLCXrhyTdavD13azEp6BLqkuAjTxx6eztHTNnykNspqhqRbPPzRpWit8z8KfNe2cIK0fKf7fNFY5e5Y1mW0y7+dQjb0Bp0BJ8WFY7CslFqplJqZ5d+3AfxZRMYCQOr/V7NsohfAdhHZB+A6AJtFZI/Fvm5SSnUrpbrr6+t9/1IUvmKHUSCeA6OtLJkIdKFqqS3HlzbNw2+uOhpdraNw46ldg987YvJAOec4XAjnjR+FU+a3YMGEQwF+0Dzr4oRg1fRDs+TXdY7Ds3m4GkDUMTuW/Mp26nrp6vflvB0UHUGfe90H4IzUx2cA+PbQFyilTlNKtSql2gCcD+AOpZToy5kEAAANKElEQVTdREDKA/k06zkffO3MBVq3JyJYM3PM4OcttSNw9fGzhrxG6y5Dcc/Zi7CsowH/ummetm0mE0W4afPA+qvLOupxw8mdqCh1TlsiKjRRne+XrVlDK2/GJc2M9Ah6Bt8D4Bsi8iEAfwBwEgCISDeAs5RSZwbcPhEFtG/PWrz+vwdC389J3c0oLynCn17fDyBeF5PaihKMHlmCv7wVrJ/+8yOLMDk1Mn3bB+ajZ0Kt41MYCkdYR19E4zsiClGgs7hS6q9KqRVKqcmp//+W+vrj2QJlpdRtSqntQfZJ8RCfMKkwFCeGvyO636NkogjHdzXH9qnCpoXjsbEn2JKFXa2jBn//ZR0NGFHCEWVT0kFttiIi38xY+pDMicup4qrjhpekj0vbSQ+eyYkKQNaVBkI62x+0Wksu4s5baV1cheJrxrjh64l3B5iEysIj/mzsaUV9TCdBblp4qCT91DGVeOF/3jTYGjKBf/UUCt51R0vmurPPfTLcyWb9qUREHgNkkmT5SIfSYi4N6Mc1J8zKixuNS4+ZDoBPTwsNR5YpFDyRRIuIYN+etdh/4CDKLdZSrnOoiuZWf386WOZRQOakn2/oPgyzFTwpTyYws6la747ImFlN1XjqD3833QyKEAbLFIrGqjLTTaAsMgPlzBiirqIETzisne3WwfTIspatUSEpSRThwMF+082w1TGmctjXnrliNbisfP64fN0MlJck8OVHXjrs618+fR56JsRrHXnSI/7PRCiSdq3qMN0E8kBXoAwcKn/NgWXy6p6zF2nfpu7DcEpjJfbtWQsA6GisxOOXrESiSPgkxZdo9llRkaA4y93P6hljUJwowoVrOnDeUZzjUEg4skyhyIfctHwX1rW9nyPL5FPbaP+VE62EFcSumNqABRNrWbkvkHhOBv7IsnbTTaAcY7BMRFr1x3Q1DMovZcmBlKOwbtpu2TI/pC1TFKTXiZ/FXHQC0zCISLPBIIWPpcmgpppy/PzjK0w3g2Iqffr6zo4jzDaEIoHBMvn2wpVrTDeBAgirwt45y9tT2yfyZugNVmlxEUZYrN7iRmNVGXPnIy26b86CCXVoqik33QyKCAbL5Ft6BJHiKUgQYmfwuIjudZBioKu1Bi9edTTO52ThvNWeKg0fRUdMHo2f7O4z3QyKCAbLFNh1J3WabgL5sK5zHGo1ra2cTVgj11QYulpGadkOj8NounFjV6SDZaJMDJYpsNnNnAARR4kiQUfj8DVjdeHjb/JKqUOTQy9dN1ApbUJ9RaBt8jgkoqAYLFNgiosfxFZRiGcAxiikw/KOhkA/31DFpd2IKBgGy0QFLMxH1BzRI6/CWEGlobIM569iAQki8o/BMgXGoCi+wnzvmCtKXiUT2Y+ZS9ZOC7TdzKW/n7lidaBtEVHhYbBMgQ29vH3xtLlG2kHeFYUYLfMmirwqLU7gV5eu0r7ditJD9bdGlrIWVxTw9EBxwmCZArlz68JhM5r7mcQcG6GOLPNqSH44HDebFrZ63uTm3vHYsqjNX3uIqODxFpsC6Z1UN+xrrHYcH6XFYd4vM1om76rLk7hr20LL71913CzP20wmilhgImJ4maA4YbBM2imOLMfGNSfMxo6+/aFsmyPL5NfCicNvwoM6cLBf+zaJqDAwDYO0OLevffBjxsrxUVtRgplN4ayTzViZouRdBsuRwvMDxQmDZdLioxklaZmzTERRs2JqI1ZOC7ZmM+nTWFVmuglErjENg7RjrEwA0zBIHx3nlFnN1bj5jPnBN0SBvXDlGpQlE6abQeQaR5ZJu+62UaabQBHAdZaJKBsGyhQ3DJZJqxtO6cT4ugrTzaAI4MgyERHlA6ZhkFb9nENDALYumYD1c5pMN4PyxIxxVaabQEQFjCPLpBUn9xEAXLx2emirbFDhWdQ+Ghes7nB+IRFRCBgsk1aMlYmIiCifMFgmrTiyTERERPmEwTJpc+LcZiyZUm+6GURERETacIIfaXP9yZ2mm0BERESkFUeWiYgo8oqLuBYhEZnBkWUiIoq8zb1t6GplwSMiyj2OLBMRUeSVlyTQM6HWdDOIqAAxWCYiIiIissBgmYiIiIjIQqBgWURqReQhEflt6v+sCWUi0ioiD4rI8yLynIi0BdkvEREREVEuBB1Z3g1gr1JqMoC9qc+zuQPAtUqpaQB6ALwacL9ERERERKELGiyvB3B76uPbARw39AUiMh1AsVLqIQBQSr2llHo74H6JiIiIiEIXNFhuVEq9AgCp/xuyvGYKgL+LyLdE5CkRuVZEEgH3S0REREQUOsd1lkXkYQBjsnzrYg/7WAKgC8AfANwNYAuAW7LsaxuAbQDQ2trqcvNEREREROFwDJaVUiutvicifxaRsUqpV0RkLLLnIr8M4Cml1Eupn7kXwEJkCZaVUjcBuAkAuru7lbtfgYiIiIgoHEHTMO4DcEbq4zMAfDvLax4DMEpE6lOf9wF4LuB+iYiIiIhCFzRY3gPgKBH5LYCjUp9DRLpF5GYAUEodBHA+gL0i8jQAAfCVgPslIiIiIgqdKBXNbAcReRPAi6bbEVGjAfzFdCMiin1jjX2THfvFGvvGGvsmO/aLNfaNtSj0zXilVH22bzjmLBv0olKq23QjokhEHmffZMe+sca+yY79Yo19Y419kx37xRr7xlrU+4blromIiIiILDBYJiIiIiKyEOVg+SbTDYgw9o019o019k127Bdr7Btr7Jvs2C/W2DfWIt03kZ3gR0RERERkWpRHlomIiIiIjIpksCwia0TkRRH5nYjsNt0eU5z6QUS2iMhrIvLL1L8zTbQzCkTkVhF5VUSeMd0Wk5z6QUSWicg/Mo6ZS3PdxqgQkRYR+YGIPC8iz4rITtNtMsFNP/C4GSAiZSLyCxH5VaqvrjDdJhPc9AOvT4cTkYSIPCUi3zXdFpPs+iHKx0zklo4TkQSAf8FAkZOXATwmIvcppQqq6p+HfrhbKbU95w2MntsAfAHAHYbbYdptcO6HR5VSx+SmOZH2HoBdSqknRaQSwBMi8lChnWvgvh943ADvAOhTSr0lIkkAPxaRB5RSPzPdsBxz2w+8Ph2yE8DzAKpMN8Qwp36I5DETxZHlHgC/U0q9pJQ6AOAuAOsNt8kE9oMHSqkfAfib6XaYxn5wTyn1ilLqydTHb2LgBN5ktlW5x35wTw14K/VpMvWv4Cb+sB+8EZFmAGsB3Gy6LSbFuR+iGCw3AfhjxucvozBP3G774UQR+bWIfFNEWnLTNIq53tTj0wdEZIbpxkSBiLQB6ALwc7MtMcuhH3jcYPAx8i8BvArgIaVUQR4zLvuB16cBnwVwIYB+0w0xzE0/RPKYiWKwLFm+Voh3rG764TsA2pRSswE8DOD20FtFcfckBkp6dgL4PIB7DbfHOBEZCeAeAOcppd4w3R5THPqBx02KUuqgUmoOgGYAPSIy03SbTHDRD7w+ARCRYwC8qpR6wnRbTHLZD5E9ZqIYLL8MIPNuohnAfxtqi0mO/aCU+qtS6p3Up18BMC9HbaOYUkq9kX58qpS6H0BSREYbbpYxqXzLewB8TSn1LdPtMcWpH3jcDKeU+juAHwJYY7gpRln1A69PgxYDOFZE9mEgnbJPRP7dbJOMcOyHKB8zUQyWHwMwWUQmiEgJgFMB3Ge4TSY49oOIjM349FgM5BoSWRKRMSIiqY97MHAO+KvZVpmR6odbADyvlPqM6faY4qYfeNwMEJF6EalJfVwOYCWAF8y2Kvfc9AOvTwOUUhcppZqVUm0YuI7/l1Jqk+Fm5ZybfojyMRO51TCUUu+JyHYA3weQAHCrUupZw83KOat+EJFPAnhcKXUfgHNF5FgMzGb/G4AtxhpsmIjcCWAZgNEi8jKAy5RSt5htVe5l6wcMTL6BUupLADYAOFtE3gOwH8CpqnArEy0GcDqAp1O5lwDw8dTIaSHJ2g8AWgEeN0OMBXB7arWiIgDfUEoV4lJgWfuB1yfyKi7HDCv4ERERERFZiGIaBhERERFRJDBYJiIiIiKywGCZiIiIiMgCg2UiIiIiIgsMlomIiIiILERu6TgiIjpEROoA7E19OgbAQQCvpT5/Wym1yEjDiIgKBJeOIyKKCRG5HMBbSqnrTLeFiKhQMA2DiCimROSt1P/LROQREfmGiPxGRPaIyGki8gsReVpEJqVeVy8i94jIY6l/i83+BkRE0cdgmYgoP3QC2AlgFgYq8k1RSvUAuBnAjtRrPgfgBqXUfAAnpr5HREQ2mLNMRJQfHlNKvQIAIvJ7AA+mvv40gOWpj1cCmC4i6Z+pEpFKpdSbOW0pEVGMMFgmIsoP72R83J/xeT8OneuLAPQqpfbnsmFERHHGNAwiosLxIIDt6U9EZI7BthARxQKDZSKiwnEugG4R+bWIPAfgLNMNIiKKOi4dR0RERERkgSPLREREREQWGCwTEREREVlgsExEREREZIHBMhERERGRBQbLREREREQWGCwTEREREVlgsExEREREZIHBMhERERGRhf8HKpBElf2yIYUAAAAASUVORK5CYII=\n", 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\n", 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\n", + "image/png": 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\n", 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" ] @@ -2075,7 +696,7 @@ "text/html": [ "\n", " \n", " " @@ -2084,7 +705,7 @@ "" ] }, - "execution_count": 20, + "execution_count": 22, "metadata": {}, "output_type": "execute_result" } @@ -2108,6 +729,7 @@ }, { "cell_type": "markdown", + "id": "f7e6bd25", "metadata": {}, "source": [ "### Shiffiting to left and right" @@ -2116,11 +738,12 @@ { "cell_type": "code", "execution_count": 21, + "id": "01e32d0b", "metadata": {}, "outputs": [ { "data": { - "image/png": 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sRPYqx66V+WX4cWtx4AXDkF9aiw2HTkR0G/Fg99G2QaDSv1ceaPuekuBKp13wr+aJTXx9V1sKq7DlSGz2OL/0817Ng333ZAYUvkADJiOZC+tv3VqmkhCRfnAGPwqKxeZA4Yl6/GXGZtzzRdvKChR7jlQ0tHnujk83qF7P13lt69i6xXLeekVd+KXkKHhqeuoCDZj0lSqhBX+zPHJ2P++2F1VFuwlEYWGwTEF5a3E+zn5hsaoem3BuZTNnOXyRGmCn5rtJSjBGpA3tIVYGKHYUjhj5zT/xw06frzFYbutIRT0uc82MGSNfcVB2Hq3GK/M5uU28YLBMQalqcE5TalARLXeg42JMitSJ6bWFwU8VnGiK3UNMe5zYF+46hrs+U9+b3xFpGSxHqyJZrAT87cnfwM1Y/7TUHAsptsXumYzaTW2TDVtcOYLtdRKK9YOoHkTqM9xaGPwtVYOv0X8xQG3cU1oTOMd5bavyYt9vLsbcMOs6dxSPz9qh2bqiVb+XwTJRx8RgmQJ6Y9E+T2kwNbmAPG9EV6Q+f4uKW82xvA+oTcNYsLM04DLXT18Du6KnLXYvJbT3k4YXDSJKn2ws7++R4u+b4P5PsYLBMgVkszefAYoq2w4K84knjg5JTbAcyztBewQ+sfvpaM+uZRoGe5aJSEMMlimgUM87HCDVMVlUVLiI5djBISU+WnlA86oYzHP0TsM5SaKYsxylDccoflwUKxgsU0Ch9tKEEyjFcpClF5G6WAlU41bpJh3XFv7T5xv9vv7gt1vxxA87Na8r/rorWLY7JOpdU4NTbFTACZSXHgt/AxGpx2CZAlJTAUNp9NPzNW4JBWvhrmN4b2mB5ustr21S1XtWWtOkeRu0MnvbUb+v55fWRnT7byzah4W7A+c5xwt7O3cth1IDfPy0hX5fZ6zs3zkvLkZ1ozXazfDr+vdWY+Ph2JxMiSKHwTIFpsNRGGsLymNmOuVo2FEc3Ex83uw9VoPD5fVeX7PaGQ1oxdukMLHswpeXhhXwaprCEMS6Bv19roYbdGLOcmCNFnu0m+DX2gMV0W4C6RCDZQooWiPLfWm02nH99DV49Ptt0W6KbhnDKNl20SvLcNU73mdIi8dgINg/WW3ai7GDHX33ldaqHPwZOdHaS5mzTNQxdbDDNcWqHcVVmL3V/21xt0e/3w4gslPaxrpQU2fcfPUgf7TqYFjrpWbhXNCQNp6fu1vT9cXjxaRaevyEbHYHdoZxN446PgbLFFB7xKSPfr8df/qiecCVv166fcdqAOgyO0Q3wo3DfA1Umr5M+zzojuLv321XtbzygsYWQv6sHoV6rJg22/cU0qEINmZ9d+l+jberx1CQAvl+czEueX15tJtBOsZgmQJqjw4wNT2hta4KAuH2nnZk4fZa6v2cnzt1NtYfjO3cQuX+e/mb3tNeYk2o+83PO49p244o9V8yDSM2Ndn0nUdN0cdgmQJqj5zl1lvwd9J1n5AM3Ht9CvdCIhbO+Yd8DEIMhpoeQE2rNCgoL2h2Ho3tW8C5U2e3+zZDqWYRaUzDCKxYzcRW7YQdLxQIww0KqD2OI2q24V50zrYS9gj4EO7dgI5+0lfz5z31406c0HhiEoAnaKVQdrfX/UzuEondd8OhEwGXcegvftcdZX1zvRxmHp7pHCx++8d5UW4J6RWDZQqoPU7panqvlTHGnpKaCLQm9oU7+FHLk1idhhNvTF+239OLGc5fqPbPq43A5CEmo/6C5dyps8O6AP1i3WHP46d/3Ik5AWpZu4WSNtHepSN/3lEScJmOfpEZitaHIuUndLiiXld53gt2aZsORB0Hg2UKrF26ltUs2rxwKEGMze7AtxsKVb8vljw+a0dY7/cWvIR6+/TOzzaE1RalWVuaZ9PbUVyNuz8Pbd1qT9CBFi+rVT/5il57lsMp/zZXERz/e8UBfLX+iBZNUm3LEe0nlQhmHICO4j7dalLsXy/M2401BbE99oDiA4NlCiisHrwgzx5tcpZ9LJc7dTbyj9cGXtCPHcXVeOCbLerfGEcarQ7MWH+4xXPXvLMqpHUdqQg9t1ipptGK7UXNub0/7SjBnG2Be/u8UZuGHKjH0BFCXrNOY+Ww8tXzDp3AugMV2O/6jaYlmbRplBe+Pr/SmkbcFWAq81CYggiW2bMcWEWrlKZGa2yn0q3KL4t2E6gdMFgmv4orG/Can9zAQIKtyxtq4BDKqcmiw4FBerTxUMveuZoQUxG0mqjim7yWdwPCCTbV3vYPFASNf9b/NMixJNx477r3VuOOT5y5n0crG1DVEHh641C26St1K1J5w8YgRhTbGSy30Z4fyeI9pZivcWWVQH79wdp23R5FB4Nl8utgeV1Y799aWBXUcq1PfEHPmqbyQLy9qArbi4JrU7xTxgZSStQ0hhYsF1c1apKX+NSPLWvxhhMsN6iccjeuegw1+FP3H3ceNzYersRfv47MXZz27pkPZsZFre6idCQBdycNv8fbP87DHz7hID3SHoNl8ivcvMp6S3ABVttBIJEJTi57YwWe/EHbCRD05oq3VmiyHuUgweX7wrvVuPFw4EoCaoWzb76xKF/V8v6yLDrKhCJuWv/2apsC9yyHUgaupsmGvHastR1Mz/K9X21uh5bElkAXyuHGyjWNVpz1/CJMm70zYmUeiRgsk1/hB8vB9eCFnoYR/MHxg+UtZ587WqW/ep9a2HJEm55zZYpmMLfS/WnSKBVDKZx9s3XeZCD+epZtHewErXUnejADuI5Vqx8gOXvrUVzz7uo2z0fqQvuFedpOjR0vAn0b4VbuOeWJn1FU2YB1B50X5MHklhOpxWCZ/Ar3VufyfWVBVVEIdeKT/aW1gRdyeWb2rhb/nvDcopC2GS+UwWi4aQiRyCMNZ9cM9o6Hm78eq46SoeHuASwoq8PAR+ZEuTXUUQT6fWgV2h5wDSoNd/ZSIm8YLJNfWhx28oMIaNsE5UEGIE+EmVLBOs2+fbL6UEhVHryJyMCnMHZOtYMO/TVfq55MtXnUWityXdRe/c4qzW9nz9xYGNSkHnr04YoDzIMNS/tcTVa7xlTosX45xT4Gy+SXFoNoEk2Bd7No1Zx9c7G63NV4406fCDfWtYfZtewteCs4HvrgUy1Lx2l1HfDLN7XJNQ/Vp6sPRWzd93+9BVeHWHow2mZuKmz3CgsdScCeZY0P/aYgcsuJ1OJeRX6Fm08GANdPXxPEdlr+u1zD6YUdDol//bzH62s/bClu95nAIunmf2tbxmj6sgJ8te4w7psR3sAlmz28iHKGxpNbqE0ricTAoXeW7G/x72DuwERSqHnlepqBDdA+LUZnf17MCZizHMItIn9pVEzDoEiIXMV46hDa67ATqe1IKfHwzG2Ykec72NpdUo3sjKQItaB9hVu1orVXFuzVZD3h5jy/PN/7xY4exHosVVTZgGmzd4Y8wYveaP19sMJCeB78dqvf19X2x+wsrsYlry/Hwecv9b4+dasjCgp7lskvLXqWo7mdslqL30AZADKSEyKybWpmDbNnuaxWuzsNgPrg3d/Sl7y2PLzGRNn/Nhd5DZSDDRL11vOqdU+33v6+WBNo6nG1R/7qRv+VecrrLHh4pv8AnUgtBsvkl1YhbKCDV6RC8mBO+NHKl44n4cQbNQFOjq35+s6tdgdsdgc2HDqByvrwSuEpHQ5hIgo9DXbztf8HG3SGG0tqNYjUTfM0jJi/dxA9s7ce1XydCUEM4PtyXfBpW3r6LZJ+MQ2D/NIqkFy9v9zv65HqWQ6mCgNPhfoWbCy1bO9xlNU24f6vt+Dhi4fi1jNzsfHwCVjtEqlmI655dzVOy+2M9QfVnxyvenuVz9u+oQimnGKo5mw7iq2FVZh68dCglveV4hmJ38XmI5UYlZPZ4rm//VfbXkAtZlv8YHkBvlh3GNeNy1E9GJSa/emLjZqvU+sBfDuKOaMrBcZgmfzSKoY9WF6P7UVVGNE7w+vrkRqToXWvFUVBEF9hwfFa3PLhOs+/n5u7G3O3l2Cz6xbw0Ow0AAgpUI6ESOyVUko02RyYvqwAm49UYkC3VFw3Lifg+3wNsGqw2pEQxBzPatIernxrJV68ZmSLds3drm2udDixcmW9Bc/M3oVvNxQCAJ6fuxtpiTxNqvWXGZtx9Zg+QS2rtqMkmH1SjSZr+EXgHQ4JAwcWdmhMw6B24+8KPlKpEB1tdrVY9ecvN4X83kC3wWsarfjFv5a2eX6zIldyt87qafsKMBfvLg15nbO2FGPoY/M8f/dD327FZa8vx9+/2+b3fb5+emdGaNKehxQDvhosdtQ2qZsgJhC1PcvPzmmerGhbUZUnUHZr6mDTmbeH7zYV4av1h4NaVm2ai7uOsla56dPm7Aq8UACc3bHjY7BMfrVXOm+kSmMGk7Ost9JX1FKgr6dc48F/vtg0DJp8/U3vLN3v/YUgHC5vmzu9vbgai3eXosnme8ITXxeqwQax//wp9EolJ/9jXsjv9UXt9fH0ZQUAnDntf5mxpc3raiewIXVCPfzqqUrJjuLqaDeBIozBMvmlZY+vv3qa4eQst65Xq2QLYjIM/Rxyw9NRg/5APYXt9Vc3ahg0+epNUzsNt9uyvcfxr/ney/wVVzXi3i9918kO9+7xohB6w0urI1fbPNTfQXWDFWW1TRq3Jn4F28Ov9k6Ae/mIzAoaok2H9ZHeRZGjSbAshJgihNgjhMgXQkz18vr9QoidQoitQoiFQoh+WmyXIk/LnuWH/AzkCSco93cLLJ56lgMNooxVgb6d9hrNrsXAMTdfqwo1f/JYgODzYHkdKustXnP4A12ovjBvN857cTEOlHmfMdEaQo/7+GcXYvm+46rfF4xQvyXO/KatYHt+1XYQu387ejps10V5qnqKvLCPDkIII4C3AFwMYBiAG4UQw1ottgnAOCnlSADfAngx3O1S+2ivA5K7dytQDU21gmn/1sKOMRr61x9oO3uf1kIdbBnoFucD37S9dR4JUsO78eH+rn7c6px5MnfqbABAWpL/QWi7S2ow6qn5+Hxd2zxSfz3LX+cdwTtL9uNQRT2ue3e112VCraF987/XBV4oBF+sDS5XtrU/fpancUviW7A/d9U1z12La5GG0VE6SijytLiUHg8gX0pZIKW0APgKwBXKBaSUi6WU7oS6NQCCGyZLURfJY8mO4iqUu257Gl29W9N+DH+whVIw7X/yh52oatA2SKe2Qu2ZvfXDyARVaml52zecNeVOnY17vtiEM55b6Hku2Dszi3eXotHashfMX8/yi4q7Nha7A6dNW4AX5u1uceGjp9xRAPjCywVBIA6HxJqCigi0xjeLzYHb/qOPfTsS5u88FtRytY3qUo/cx5Gr31mFijrf4xUWBLF9CwdvUpC0CJZ7A1BWAC90PefL7wHM1WC71A4iUZD/H//bjtlbj+LS11d4aqy6T9iBZttT65dvrghqubFPz9d0u9SWnnIMQxFoJjI1fF04hPIJ1TbZcMenG4JadtHuUny86iAenrkVK/PLIKX0G2grZ06sa7LheE0T3lmyHx+uPIC/zNiMIxX1IaVhRFKSSf1pbcAjcyLQEv8q6ixYvCcyqSixpLQmtDzx3SU1OP3ZBT5fv/2TwHcKwp1ZVGuFJ+pRWtOcUnXzv9eios6CrYWVHTbNLlZoESx7O9J63QOFEL8BMA7AP328focQIk8IkXf8OA8ieqD5bFhS4pPVh/Dx6oMAmg9W0S5RGesl5jbGwAATb2MtNx4+gbOeX6S73klvbvtovXYr8/Hn1qjsZQOAA8e95xL7siK/DF+uO4KbPliL/cfr8PrCfUG9T/kbeWb2Lny3qQiL95Tq7reTmWKOdhOCEu1jnl6oTYVQXmiGG+xqeQGshSvfWoXx0xbiLzM2Y2dxNZbvK8P+47X47X/W48b310S7eXFNi2C5EICy8n0fAMWtFxJCTALwdwCXSym9XkpKKadLKcdJKcd169ZNg6aR3njOq67/l9Y0IXfqbK8DCQ+V1+HWD9fhjSBP5q1pWepL7656e1W0mxCQt97Uq95ehaLKhhYpBfHgUIX3ADfQQD1v1Ob5L99X5nm8aPcxlIRRmeL95QW6SmEqrWkMafrxqHAd8+K9NJ3aDhktO3DeXpKv3co04K7G8t2mIlzy+nfcGDEAACAASURBVHIAwO0f5/lNN6H2oUWwvB7AICFEfyGEGcANAGYpFxBCjAbwHpyBcuhV9ynmrch3nqjd6R0Vdc6Dg7dbwef9cwmW7j2O7zcXAXDeBvbn1fl78cdPmw8szEfTF3caxvYi54DKGkWQdzzEW7HRdpnrhKbWtkLfgxZ9Vfe46JWl+MZLmlJeGLMSPjsnvMkUjlREbtruYBUppg6PpVvV7lKagx+N76xEtal+Wt7HCKKyaLs56KPajPJi9A+f5CF36mzPWB9qP2EHy1JKG4B7APwEYBeAr6WUO4QQTwkhLnct9k8AnQB8I4TYLISY5WN1pDNap2G0HqzlXr97ViZv3D0vj32/3e+631ycj592HMOYp+djT0kNhv3jp/AaS5pyOCTKa5tw2RsrYLM7cMoTP0e7Sao1KEpEnfPCImwPcTKCZX7Kpr3nmphk37Ea/P6j9Vi8pxTvLt2Pvcdq8eC3bcsvvrLAe33lePHW4ubeweQEYxRbop14qtKgNotH0xKOOqmyX1zZgIkvLQm4nHvQZFOc342IBk0mvZdSzgEwp9Vz/1A8nqTFdqj9tdfBJMHo+7rNPZNY4QnfvVgPz2wZRFzzbmTTEu76bAPe/PUYGJl4GDS7QyK/tBYAcKJeP7fu1Rjz9HzsenoKSqsbccTP/hiOn3cew6infkal6zNaGMYU2PGgUXEBM2fb0Si2RB1/AfGHKw7g83WHseivE9uvQVESyTSMM59biFUPX6DZtiNF7ZiNeosddofk+acdsQo7+RWpg4k7r9C9epOfH33vzGQA/qspfLnuSIuBRqEMlAqGlBK5U2dj7vaSkGdb01pVjASeDglcP905SOX7TUVRbk1oGlxl18Y/G9kc60oV32m8nzBnKval7ze3GS6jW/7io1X7y1FwvC5me5hTzcH38Kuvsxz88sVV/vPxU1S0M5LUBsuTXl6KSS8vxcMzt0WoRdQag2XyK1LTvx6rdq7Xk4bhZ/as7cXVKKps8DNZtjbyS2t8vvbST3vwyvy92KKYwCSUwViRoJdbiYHsPdb8+U6b07aedmV920EsO4o7xoQxkRQLlUTay90TB0a7CUHzFyRWuvJUY3VgV3pyQsTWreXefuGwbM3WFcqFTe7U2ThYVgdbCMnTB8rq8GUINcUpNAyWya/ff9w+s1oFmlPhwxUHNJ1625tPVh/y+dqbi/Px5uJ8NCkmdHha4wlUQqWHQVbBuCnADIPXv7emTWWAcAavUfzRMp810vy1teiEs3NAOXgxlqi5gFM7s6f7YxvZO0PV+9quR2p6dzDUXa+4qgGHykOv4LLvmO9OnmCFcncyVu96hIrBMrVwqFxdzdZwuSsiBDrJqbktHapAv327Q7YYmHXCS09oNAQ78Yre7TlWg8GPzsUr85sHrDXZ7H7eER3KSQNIP576YSfeXVoQ7WYETXm8aV3msrbJhsQEA44GSCPQo8W7S1VNNKI25HKfK6xB9sb6Ctxfmb8Xz8zWrsND7YWau127j9aE1Sl14SvLwrq7tL2oCqc+9TO2FQZ/F2/FvjL0f3iO7iYkiiQGy+RxtKoB5/1zSbtu0z2qN9CPXUJG/HZzMOkMby3e73m8VcXBhYL32sJ9niDZX3pOtIyfFl81oWPFD1tjJ18ZaBlcfdcqh7/RaoeUoc9uF037/KSzeaM+ZxkwCqCuKbgL6Rumr/b6/CGN63GrPT25p53XIp1v7YHykOudr3SVc12RH/xEcIt2H3O9pyzAkh2H/s5EFDXuup/RuFp8f/kBv6/P3FiEjYcjO9vS52vV53/F262o9vLGQmc5sAQ/JQWJ3B78ZotuanUHO4mSMrhauvc4cqfOxqHyOjgcEjaHRJPNgVKdjItQQ6gcXbLvWK2q5SUkDAYRdArFeh+pXCd166Rqu4E8+O0WVcu7g2W1kwp58+v31+LUJ3/GLf/2n+rmjfuC7O3F+z1tCmTdgQoIAOsPVKjeXqxisEwe7kEG7koS0QwEhfA+j3okSdlycowGix02uwMlfm6F9n94Dsprm2C1O3DnZxsAOAdFztpSjCOxMpOYDr25OB8DH5mDNxbpa4Yt0qdvNhRGuwke/5q/Fw98EzhwUvao/rjVWfKu6EQDLHYHjK4BGoUnYu8YonYyqNnbjrZJQ6mqt2Kzj6mopXROYhXuNOtbi7S9M/i/zcWqJgtxT9Vd3aBd3vSyfep7evcfd16sSLQchP3AN1s8r7V2qLweEs6LPF/+OW831sVYMJ2Q1XeYr9cYLJOHzfXjdecRF/iYUag9SKntqOdgnai34KcdJSirbcKop37G/325CX/4xH8+2f99uQlf5x3BvO0l+DrvCN5evB9//nITznlxMR77fjs+XOG/15y8sztkTN6GJvp2Q2HA2+vKzoiczs7ymFUNVjRZHZ5ygLG4/6sdsAcAjTZ3R40Vr8zfi2fn7sKVb63ET9vb1s2W0tmZEm5annuCDy2NfWYBGix23PrhOuROne13Wfcd3GB7c4P1dd4RVet0dwbZHA5scV2g5JfW4tsNhZ4Sn2sKyj0TMlU1WD0lNH0NTKxutOKtJftxx6d5MXX3VZjMyb5e02RSEuoY3D3LVQ1WrDtQgeve857r1ZG9u3Q/Zm5szh+cu70k4HtW7S/HKtc0uw/P3IbROZme1z5d46yw8buz+2vcUieWDSPSp9NdtbgfuWQofndWf1Q1WNG1U6LndeVP1z3BTZ3FjkabHQYDADuw/sAJHCyrQ25Wans2PSyhpPEt3HUM5w/tjpGtZvW8d8ZmLM7JRHZ6EoSrt90hJQSEqmPfmoJynDGgKwDngLZAHSDhOPkf84Jazt0Dr/VsfA99uxW9M5Nx1klZQS3vLk/YaHV4Sroud/UY7y6pQaPVjhumr8GTlw/HjeP74pwXFsFocPbsN1jtqLfYkGJuGUpuOVKJtEQTrDYHthVVYWSfTLTmDqJFpMtcBan13Y3W2LMcIrtDtpj6Nlx6uPpy39Y6UtGAo1WxWbIoXMpAORR2h0TeobY5ct9vKsKBsjqvOYiBDvpztx319Pa3dttH60NrKBG1i2fn7MZ7ywow9pkFnsFUgDPo65TYMshosNjQaLXD4AogLHYHJr60BI1WOyw2h8+8bCklHA6J2z9e3yaX12JzYNne436D2A+WF4SU872npAYLdh6DwyFxtKoBVfVWFFeqz7PedLgS98/Y3OZ5gxCY8NwizFN0WtgcDtU9yzdMX4PcqbNhtTtw2Rsr2q3KyMJdx7B833HXgE2JdQcqkDt1Niw2h+dObiQGyb29JB8r9pVhZ3E1Nh0+AYvNgdyps5E7dTZW7y/3DNADgLqm5v3FXarQPdFP0YnmsnbFlQ3Ye6wG1Y02T4nPJJOzYktRZQPeXNScq3+ovB5WhwMOKbGjuNrzvMMhPTnaT/+4E798c0Wb7zFQ0GqzOwJ+9zWNVtUxVWOAixbjE088oWqF7eWZf73xxArTKBQcr8Xp/bvi9o/Xo6iyAWP6ZuL95QVIMZtgsTvw6HfbMDInE40WOzYfqUTfLinYUVyFqnoruqSaMXXmNuworsJpuV0wfWkBcrNS0WR14IlZO9A9LRF1FhveX1aAkTkZyC+txYaDJzCgWyec/9ISfLzqIM4Y2BV3frYBx6oaMTQ7Hf9ZeRAHy+qwKr8MN7y/BmW1Tdh1tAavLdiL8f27YPX+Mpyot6J3ZjI+WnkAyWYTUsxGPPDNFnRKNMFoEPj3igMY0TsdRyoakHewAn26JOP66avx49ajOHdwN0x+ZRnMJoFhPdPxw9ZiDO6ehkarA28s3IfemSn4blMhrnx7FYZmp+NoVQOO1zShV2Yy7v1qE7YVVuHUnEw8N3cXMpITkJGcgDnbjmJw9zTkl9bixXl7MLJPBmZtLsK0ObswYWAWbvvPehypqENWWiL+u7EIP+8oQW7XVJ8DI0i9eTtK8PGqg3h/+QGcOTALZ72wCCVVjSg8UY+r3lmFVLMJRZX1+M/KgzhncBZW7ivD9OUFGJKdhqvfWY13luxH11Qz/re5CKfmZMJkELj49eXY6CUwJyJ9cd95mrmxCJX1Vvz2P+vx6/H98M2GQk8Po0EA4/t3RZ/Oyfgmr/n5RJMB24uqsLO4Gnd9vhFzt5Xg5gn9POs+49mFmDZnF15buA8FZXV4a/F+/PLUXpi1uQjZGcl4ft4uPP3jLizdexzDe6Vj19Fq5GalYvX+cszcWIQEo8A9X2zCB8sL8KvRvTF3ewmGZqehpLoRMzcUYkh2Og6U1WHdgQoM6NYJS/ccR2W9Bd3TknDatAWYtaUY3dIScdMHa/Hu0v3YebS67QcQwFVjemPZ3rI2k7AkmYyw2B0Y378LRrnu2G08VIlFu0thdUjVtY0nDOyK/4bZIaLGrC3F+G5TETYdPoGthVV49PvtAIDqBise+HZrxLZ7pKIBMzcV4fO1hzFj/REcKq/DHtdAyv9uLMT/NhfjvkmD4XBIvDx/ryflMS3JhOvG5eCFebudPd4CGNYrHfO2l2BAt1SkmI1Ysa8MFlegn2Qy4pJTeuKHLcV4dcE+vLkoHzeMz8G8HSXYcKgSNodEvy6pOG9INwDAqwv24bf/WY9OiSZ8uuYwDpXXI8EgUF5nwbaiKnROMWPkkz9j0+FKXHByd4x6cj5uGJ+Deosd7y87gKQEIx6ftQP3frUZ1Q1WpCcn4Fh1E7IzkjDsH/NwuLwefbuk4MznF2HTkUpcOaoXKuutSDYbsTK/DL9+fw1G983EX2ZsxqerD+HCYT2wtbAK+4/XIT0pAa+++Q4ee+DPT3r7TIUeejS9Sew5SPa89VUAQP+sVBwoq4MAcObArli5vxwmg0CvzGQcrqhHcoIRg3p0wtbCKkwc0g1bC6tQUWfBqJxMbD5SCaNBYMKALliRX47MlAScN6gbZm0pRoLJgL5dUpBfWovMlARPLd8Eo4DN7iwkJuDMnU0wCgzpkYadR6sh0Vwj02hw3g4yGQTSkkw44VrHpSN7YvbWozAbDbh8VC98u6EQRoNAv64pKDhehx7pichMMWNPSQ36dknB4Yp6GAWQkWJGRZ0FCUaBC4b2wLwdJUgxGzG+fxcs2eO8NWI2GdpM3nBK7wxscw1YSDAKz+CBs1yfFwAM75XuucpLTjCgwdq8DrPRgPRkE+otdtRr2GNOzZISDGi0OpCcYESD1e7Zt9zc+9KUEdktelJSzUbUtfpOfjmyJ37Y2jafj4hiR6dEE2oVPXv3XjAI5w/tjpv/vdYz0Nqbb+6cgPLaJozt1wWnTVvgeV6I4CbHePLyYXh81k7PvxNNBthdVTgAICM5AZOH98DXec6Bk4N7dMLeY7XonZns6X08qXsnFFc2eM4XRoOAw6HtfKIm1+3+cwd1wye/Hw+b3YEJzy1CeV2T6lJt1NLup6eg3mLHGc8u9FyY9emcjB/uORvjn10Aq90Z10wZkY0ftx7FpJO7Y3z/Lnhx3h7PfpKWZMKbvx6DL9Yews87jnn97s85KQuf3n46ymqbcMWbK9tMtNMl1dziIikpwQApgeyMJE+v9uThPfDTjrY55gbhTGdKNBk86SyZKQmoqrdCArj+tBzMWH8EGckJGJWT2WZA4tDsNOwucQ5qHNgtFSte+gOaju7zmhcSE8Ey0DIAbC3ZbPSZEqF8n2vMhOdH5i3odEsyGXx2yxsF4G5KkskAi93hWac7IPLWZvcXC8ATMHm2p3if+wABOIN1o+Lfrdul3IZyHe73BvPtmo3Cc6VoFAJ2ne4TkSaEMy/Jx24WUWaTAVabw/N9KfeV1oI9IRKRvrU+Zt9xbn+cP6QH7vg0r0WwbDIIGA0CTTZHm3NA64BbSXl+SDAIWBUHFfdrZqOhTQUL5XPKQMTdFvf5SHkujCSjEFj0wHl46oedWJ5f5vO8TS3jGl8xTqrZiBl/nACzyYBfvb3SU7M6KcGAT39/On730XrUNNpaxCkj+2TgzIFdW0z8k2o24tmrTsE7S/Z7gk6g5TlqUPdOeP7qU3D1O81joMxGd5pR252ndQzi7kRq/VgASFD8fa07lZTxT4v3tTp/ppiNngu+ox/f5zNY1m3OcmZKy7nl3T94b3+FMlA2G4Xni1C+zygEHNIZgLiDZovN4XlsMgiYDM3v8xYoG12flvL7bbQ5WgQ13gJl98jmFtu2O5BoMrR5H9CcO2wQzi/b5nAe0Ly1S3khoFwH4Hyv8m9yfy6tP0PlDhuvgTLg/AFFI1AGnPuie9PJCQZP6Shv4vgrIupQmlods+tdA/xac9ddBtp2gHirN+w+7Cs7a5SBstlo8AQP3kq9Kc9PTbbmUnZCoEXJtvY6XhoMwB8+ycOyfccZKPthNAjYXd+nAHx+Vo02Bx75bhvKaps8+fGAc3/5eNVBz76hrKpRVW9tk9dudUhU1FlQeKJlb7HyHHWwvA53fraxxesWu/TEHSaDgCJM8cQg7qeU+cnKx1Lx9yWZDG3uvrozAtzc8Y+ybQkG4QmUDb5Puc52+n85enwFC4F+m96uVICWQaAyuHU/DqZmo5pBvsqDlPILdj+0OwLPSKd8OVDtSl+rUv5d7s+GsZa+NVh5MiCKB62PxQ0WO5qsDr8XxK2rJ3g79gc6nQVTC1m5Hff5M1oX6la7xN5jtc4KC3bt6hK3B3cPp7+7hVppHUz6W67J5kBxZWPL+MQhPTW/W6+jwWpvk1NusTmwtbDKM+OqN1a7RFW9xefrvmIvNR+VrywAdxxmd0h4a6G1dWzmJ9VCtz3LRERE8aTBakeTzQ5tM387jtogZ+3TE/c3qbcc6+LKBpRUNbToPXYH9d40WO1e8+i/21TkufPtjdEgfHZixhIGy0RERDrQaHWgyeaA5M0lr5iCph2bXWJNQUWbIN5XUN9kdfjMjW+dAqHUUeYC0G0aBhERUTyx2Bx46NutLcaaUMfWHukZ3piMApsOB1961Gp3+K3Q0tGxZ5mIiEgHCk84S2V1lN44CixaX7XDIf32CLdmMoo2OcvxhMEyERGRDhx01ZVlqEyRpnY+BZPB0KLcbbxhsExERKQTzMCg9uCedC1Y8b5fMlgmIiLSCWZgUHtRs6vF8xwMAINlIiIiIvIj3vPoGSwTERERkU8MlomIiIiIfIjzLAwGy0RERETkmxDO2fjiFSclISIiIiKfHBJx3b3MnmUiIiIiIh8YLBMRERER+cBgmYiIiIjIBwbLREREREQ+MFgmIiIiIvKBwTIRERERkQ8MlomIiIiIfGCwTERERETkgybBshBiihBijxAiXwgx1cvriUKIGa7X1wohcrXYLhERERFRJIUdLAshjADeAnAxgGEAbhRCDGu12O8BnJBSngTgFQAvhLtdIiIiIqJI06JneTyAfCllgZTSAuArAFe0WuYKAB+7Hn8L4AIhRPxOMk5EREREMUGLYLk3gCOKfxe6nvO6jJTSBqAKQFcNtk1EREREFDFaBMveeohlCMtACHGHECJPCJFXX31Cg6YREREREYVOi2C5EECO4t99ABT7WkYIYQKQAaCi9YqklNOllOOklONS0jtr0DQiIiIiotBpESyvBzBICNFfCGEGcAOAWa2WmQXgVtfjawAsklK26VkmIiIiItITU7grkFLahBD3APgJgBHAh1LKHUKIpwDkSSlnAfg3gE+FEPlw9ijfEO52iYiIiIgiLexgGQCklHMAzGn13D8UjxsBXKvFtoiIiIiI2gtn8CMiIiIi8oHBMhERERGRDwyWiYiIiIh8YLBMREREROQDg2UiIiIiIh8YLBMRERER+cBgmYiIiIjIBwbLREREREQ+MFgmIiIiIvKBwTIREZEOiGg3gMgHg4jv/ZPBMhERkQ7IaDeAyAeJ+N4/GSwTERERkU/x3KsMMFgmIiIiIj+MhvgOlxksExEREZFPJkN8h4vx/dcTERERkV8ivjuWGSwTERERxROjyuDXIeN5eB+DZSIiIl0Y0SsdAAdTUeQlm02qlrfZJTolqntPR8JgmYiISAc6p5oBACa13X4xzhjv9/ijQAggq5M56OXtDokuqcEv39EwWCYiItKBRJMBL117KhKM8XVqtsf5Lf5oaLI5cFpul6CXN5sMSE00RrBF+hZfv0giIiKdSjQZkWgyxP1gKl/ivXyZljKSEjAqJxOmID/TpASjzzQMf0F0R/nKGCwTERHpQIrZFSwza9mr5ITY69nU6zeZmmhEz8xkJJqaw0D3xYj7Yk2I5mA3OcGIzOSENuu5eUI/NFodPrfjkGixjVil27/AYmv+8M2KD9rXVVBSgsGzrNmV76W8k6W8IlU+dq/bbFS+z/s2EgLkkSUYhWebyp3DbGz7OMEgPOsLtN7W3J9BglG02JG9tVP52L2sySC8Xu0pn2LPRvSYjYYW+zwRxYdksxGJCUa/x9/WgYe3c2Iw55RgzzsGAc+50aw45wTbI6mFJJMBl43siSabvd22qQWB9p8iOpj8b7PRgFNzMtEzIwkGxfdod0jcNXEgUl2D/wScwS7g3De7dEpssZ4kkwGDu3dCepLvgX/pSSYMyU4D4L2XOcEovO6LvvYv97NGQ3O8ZTSI5gBfsaz7t5JgFF4DduUmzEYDIHx/eLo9I9c02TyPLTaH5w+1OSSEaBnMpZiNnisbi80Bi9357dodzR+W3SFhMgiYDAJ217efnGDwBOUWu/J9Einm5uDT4Nqe1fW68otVBqnO152vNbnabBDOdQPOL9/92GgUnvVZ7bLFF6l8bBCtgnujATZH8/vcqV4NVrunzVa7hMF1RejeBtC809sc0vMYcO7wgPNH7f7b2juFTC+xeSSP/63XrdyHld+5xe6Aze7wuhwRdRytb1+nmI2e47GS8vigPDYP65XuOa64DxMC3s9VrQcN+jvGK885QgjPudFil554wuaQLTqCIsnmkHjqihG449wB7bI9rUQjE9uo+J7dnYitmYwC900ajC6pZjgUwUBaogmTh2d79qVEU/P+2TnFjG6tgmWTUaBLaiJyuqT4bE+fzil448bRAJpjEJOis9Bqly3iFHeQbHO0/fQMovkzdcZxwvPYHeC7XzcanHGYextNtra93w4JpLriJovdd+84oONgWenKUb08f+jdEwc6f+QSuGhYDwBA97REXH5qLwDAfRcMwkndOwEA7jxvoOd9d503ADaHxLBe6fjrRYMBAAYhcMHQ7gCA03I7I811dXTu4CzUW+wwCKBP52Q4pPPAcuUo5zasduk5yLmvdI0GgSE90jyB+GOXnowmmwOZKWY8cslQAM4v37290TmZOHdQFgDg0lN6osnmgBDAuH6dPW3+64WD4ZDAWQO7eg4SFrujxYhU9wHwj+cOQL3F7vlbHNK5I9x+Tn8AQN8uKZ7Pq1snM7qlOXf6/lmpaLQ5YBDAyD4ZoX5FYdPL8A4vv0/N1z3ItX9K2Xwya7I50NU1Mvm+SYM8B6m0JJPXnoKHpgyJXEOJKOIGdkttk26RlGBEsrltqkGTzeEJoi12B9Y+cgHWPHwBZtxxhieQlWgZTADOO6eZKc5b5zZFQPLZ70/3BCMCzqAqwSiQ0zkZgPOc8+dfnAQAGJCVivMGdwMAXDIi23OOu/60nIABRrjcd9guG9kTXVLNeHDyUEwY0LVde7VjjfKuvK/0iHqLHTmdk9EtLbHFd9g1zYzBPTqhweqMJexS4uYz+gEAuqWZ0TnV7LnLADgvpDKSE5DbNdVne7IzktCvayoOPn8phmanQcAZC7kD5NyuzYF2r4wk2BzOzsNJJztjpbQkE/54njP+cciWnUfuHOrLRvZErauDdXROprPtDmDar0Z4Xr96TO82bZs8vIfnd3DpyJ4+/wYA0G3RvP5ZqXjosmE4NScTY/t1xqAeaThnUBZG9snE2YOycFpuF9Rb7DhncxGuOy0HAgJ/v/Rk9EhPws0T+sFsMiAtKQG5XVOQm5WKMwZ0xdmDumFcbmdICWR1SsTFI7IBAOsOVODCYT1Q3WCDhERmihmP/2876i12PHrZMLy1KB9nDcrCWQO74tpxOeicYsbB8jrc88VGPH/1SGQmJ2B3SQ3unjgQ+cdrkZlsRnZGEk7pk4mTe6YhxWxCitmEi0dkw2wyYMOhE5g4pDuqGqxosNiRnZGEgT/vQWqiCbefMwCPzNyKG8b3xei+nfHLU3shNysVDofEOYOycObALKwpKMcfP92AOX8+B0ajQEqCEZ1TzejdORk90pNw0bAemLWlGBcNy0ZSggE3ju+Lgd064USdBb8aXY4pI7Kx7kAFthVV4Tdn9MMHKwpwap9MdE4x47I3VuCk7p1w0+l98eQPO6O8F8Q+g2gbgH/429Nw52cb8Luz+iMrLRFP/bADT185AulJCaios+Dcwd1w5ajeaLTZ0T8rFUMenQcA+OL203G8tgmXjewFo0HAIASen7s7Cn8VEYXqvZvH4sctxbj7/JNw7burPc8bhKtnOcHYptf3zxcMQpeUBDzxw048NHkIeqQneV67/rQczFh/BOcOysKyfWVISzJh3SOTcKy6Ef26puDtJfvxz5/24OoxvfHQlKGw2BzI6ZKCTY9diP3Ha9G3SwrGP7sQJ3XvhP/96SwcKKvD8F7pqLPYMWlYD4zsk4kTdRbUNtmQ0yUF+4/XIis1ERkpCZix/ggA4JPfjcctH64L+TN59fpR+Hj1QWw6XNni+UST8+7vOEXVhhvG52BLYSVgc3jtffTnh3vOxi/fXBFyO0P1f784CTldUvDQt1sBAC9deyqW7CnFj1uPtsv2H7tsGJ7+seX53GQ0IM0gWpyfememIMVsQmZKAspqLeiaasY5g7Lw6ZpD6JKaiB7piUgwGmCxu9JhJJCebMLwXumYtaUYvzsrF3+7eCheW7AP7yzZDwAY6krBAIA/nDMAz87ZhTd+PRr3frUZx2uacN+kQRiSnY4uqWZkdUrEr95eiV8M7Y57LxiEF+btxl8vGgK7Q+IXQ7pjRO8MvLd0hI+cJQAAIABJREFUP15flI9Xrx+FM0/qCqMQ6NopEb0zd2FQjzT8Ymh3jHl6Pp68fDhuOr0fbjrdGezvPVaDRJMRj152Mr5YexgpZhOuG9cHZbUWdEoyoclqxwd/9f0ZCqnTki3jxo2TeXl50W5GXNlTUoPJry7Dv28dhwarHfd8sSnaTeowFj8wEdnpSTAZheqyUEcq6tGnc7LXdKp/ztuNt1wHJSLSp3d/MwZ3frYRWx6/CBmuQVJ7Smpw+ZsrWtwefubKEThvcDdMfnWZ504hABx47hJ/6ZQeMzcW4opRvduMu2m02pHkZ3DcmoJyjO6b2eK2ezDqLTYICCSbjXA4JAwGgefn7sK7SwtUref6cTlISzLhgxUHWjyfZDKg0ebAV3ecgTMGdAUALN5Tij99vhF2h/db674MyErFogcmInfqbFVtC8fyh85HosmAbmmJEELgWHUjps3ehdduGIV9pbW46JVlEdnuXRMH4vdn90eq2QSrw4FOZhMufX05SqobseSB82GxOzx3l0954ifUNDp7Za8fl4MXrhmJG6avxpqCCpzaJwOv3jAa57+0BHdPHIirxvTGpJeXeTqBUsxGzLv3XHROTUDewRM433Xn/Ov1R/D4rB0wCODpK0fgqjF92rTxvxsKsa+0FlMvHhqRz0CtuiYbuuSejKaj+7z+0GIiDYPah/sAm52RhEHd0wIs3TG9dsOosN6fmmjEVV5u9/TPSkWy2RhS/dScLik+T5QPTtHHgYaIWurqSpdbcP95mDKiJw4+f6knUAacPcnuYM+d+5tiNiIxweDJI+2dmYxdT00JKlAGgKvG9PE6QN1foAwAZwzoqjpQdrbX5EkbcQ8UC2U9V4/tg4e8HMsyU8w4+PylnkAZcOa0SqmujNyOJydj0QMTAQAbHp2Em07vq7qNwTrHlV4JOI/d3dOTPN9fj/QkvH7jaAjR3GmiXF4rk4dnI6tTIpLNRqQnJcBgEJh737nY9I+LkJGS4AmUAXjSTwWAXpnOOxbXn5bjaX9fVz7y4B5pGNitE6YMz/Z8x41WO3pkJCItKcETKANA/26pMBicucSj+3b22sarx/bRTaAMBP6NMFgmD3f+bHpSAoZkp2HPM1Oi3KL2NyQ7DYsfmIgDz12C03I748HJQ3D72f39vufmM/rhyz+cAQD46Lbx6JOZ7Hnto9tOw9d/nBDRNhOR/qz7+yQcfP5Szxia1pQBcOdUZxCdmmhCosnomaTjpO6dvOYw65na6k4AMKJ3OswmAw48dwk+uu003HvBIADA+7eMa7OsgICEVJW3nKqoD9y1UyKm/eoU1W0M1ke3jcffpgzBKFfurC/uzymUiwt/fvy/s3GqivFHnVOcF3XJZiN6uc5d7ouTU3pnwGgQ2PDoJFwxqheEEHj1hlGePOeM5ASv7R/ZJwN1TXb07pyM/lm+85n1JNDFl25zlqn9mVxXuulJzgN3e4109iUaZXdyOqd4Dqzf3HkmAOfVc+vbg26/GNodj102DAlGgddvHI3TcrvglN4ZuHpsH2R1SmxxkCZ1Lj+1Jyw2iXk7SqLdFCJVXrn+1IAnX+XLx6qbADiDj6QEg2cQnTI3OVYE2wuulOQKuIQQmDikO84Z1A2/O7t/i5745vVDdc+yN3ecOwDTl6lLFwkkf9rFMBoE7pp4Eu6aeJLfZd09y1pfDI3orW6gfp/OydhRXA0BYGQfZ4DfMyMZ064cgcmucV1dFVUwkhKMyEh2jq8Z6ONCMNFkxLu/GYvhvdJD+yOixF5TfsTXa+xZJg/3scdzWybKNcvaO1A+NSfTa3Dr7/bMh789DWaTAUIIT0WWpAQj+nVNZaAchnduGoPXbxyDCQO7Bl6Y4t7TVwyPdhM8vr1zAn41um2OZmsGxfH17okD0adzMgZ0S4XZaIBDOo/HvTNjL1hW28ly18SBLWr9As5A2FugDDiDZYeUns6dULlLjWnlxatHqmpTgqdzSpt25HZNwZ8v8B+ge+Pu+c1MSWhxF+SmM/ohq1WpOLcBWakQACa6qqR4M2VEtt+ScnpkrztR6us1Bsvk4f7xtj5wtYc/BqifeenInhjT1/9trXCd0ju2roI7sgtdZQ7Vjnan+HTzhFxkdTIHXrAdKCs3+KMMlkf37YwVf/sFuqclufJZBcxGQ0z2LNtVFg1IUpmGICDazIXgzx/O8Z5Gt6O4StV2A/mVl7Eq/rjnaEj3cVGgxoq/nY/595+H+y9UX1K0e5pzH7tz4klB99afMaArJBBXnRkMlskjq1Mi9j97STtv03mCC/Qj7WQ2hX3bLZBgpph96dpTPY/PjKMDRXuaefeZnh4ahw6D5b3PXBztJpAXf4uxwa7KG3fui0M396357unee/b07KyB6gasqb2B6a7E0CnIO3d/v3SY1+cnD89Wt+EADCr/EPdEM/391CgOVu/M5JAGjwPARcOd+955g3z3Erd2ySk9MXFwN4zxMXivI2KwTC1EOiBtK7jtKUfvRkrrGa5aMxqEZ2QwoJ98wrxHJ0W7CZq4akxvHHz+0hYH4CQdDm7iVOT6dO24HNx13sBoNyNo/u7gpScloNHmQM+MZJ/L6NUpfTKQnRH8sVHtKcedHqimbJw3V4/t45m0Qgtq/w7399+nczJ+uu/ckLe7++ngq6V406dzCg4+fyn6dg0+ZWJYr3R89LvxUU/VbE886pNfM+8+M6Lrd//WHAFu3d19/sCIT8H9lwsH+3ztvZvH4r3fjEXnlOZbZnrpyYqV2ayWP3S+39efv2pkm+fcszgRBcM981gs8PezdV+U98qMvWAZCLYLxLWsyoDLvXh+aa2q93ljDTPgVgolcLx4RDYGZ6eF1UkVqOQZaYPBMvkVqUCsdWkbf7mp5wzKQorZFDCgDpe7Cog3k4dnY9KwHhjUI81zInNPeR5t7X83IDTKg7q3izBvPbZ67Vnr01k/7Yqjzp2APlp1MNpNCJq/2/buW/S+Brnp3dGqxqCXDSUNQytztke30s47vxmLrE6JqsvtpSeZcMuEfnj9xtERahm1FlawLIToIoSYL4TY5/p/mwQWIcQoIcRqIcQOIcRWIcT14WyTOgZ3YOQ+RNjsvgPhzUecU6D6y8l656YxLQL70/sHN8gmFMseOh/v3Tw26Jy5SEvzE+TridEgPL3LuRrk6UXDeNd+tcQ1wUGkPDQl+IE6Op2Etd1crZgd7MHJ6gc4RYu/IPGWCbm4ZUK/9mtMFAUzVqT1O4J121m5Gq0pstR2eMy771w8dcUITwUmirxwe5anAlgopRwEYKHr363VA7hFSjkcwBQArwohIlvWgDSj/kCmcv2u1Vvtvm+HZbp6V8b28z2Y4OJTenoed001Y/rN41qkTGht8vDsuMrX0oJRCM/I78wY7TFzTzBjMhpw8xmRCWYmD++BuyeehO1PTsaL14zEsgfPx7d3+p7YJt53Q+Xv3NcEIHrkr2f5/KHd8dQV2uXT6pn6nOXgl338l/5LCqodlBcpaicmifRdVmor3GD5CgAfux5/DODK1gtIKfdKKfe5HhcDKAUQ/LBLiiqtjyXuHrnWQbjdTxqGuxf6gYv89xq9+5uxeOmakVjzyAXISEnAqqkXhNdY0pQwOG8rb39yMgwGgYPPXxrtJoXl6StH4M+umcbU+tVo32Wmnr7SGSR1SjThunE56Ns1BeNyu+CP5w7AvPvOabP8S9ec2ua5eHL/Rc1jDcId9BUN/joB4oH6NAztTko6iZXRLS24SlT/uvZUdO1kjtn0nFgWbrDcQ0p5FABc//c7GkcIMR6AGcD+MLdLMapvqyLlPTOSkZ2e5PVKec8zU/Dg5CF4cLJzIF2g+s+ThvXANeNyPOkaiaxaoCtG15lJmb7iLr83ZYS2ZZzay/1+BoX6M8DPFLDuuqetPXzJyRia3bYWeO8w8qe9TSesxhWjeiE1yhVLUhSTS1w0rAcGxUjvsvuY99+7IjuIWu/UBr9axrehlluLBF+pGFeOak61uHpsH2x49MKYSb3rSALuKUKIBUKI7V7+u0LNhoQQPQF8CuA2KaXXy38hxB1CiDwhRN7x48fVrJ4iROsr79bry0hOwJpHLoC3juVEkxF/Ov+kkAOpaEyuEi1rH9F/L7q3k8ELV4/ELRP64d3fjI1Ci6Knh4/SWv1UlG9yS1M5A9hNp/f1PD6ldwau8tPL7Yt71rFxuV2QoKOL0qQEI07UW6PdjODwTnpItOxZfuJy/cz8CAAjeqejT2Yy3rhxNHY+NRkAcOP4vhjQLTbHeHQkAY+yUkqfRVyFEMeEED2llEddwbDXqQKFEOkAZgN4VEq5xs+2pgOYDgDjxo3joaQDEkLg7ZvGoH9WKi5+bTl6uoIGdy/L0Ow07C6p0XB7wQ2AirU57FvTS81nf7yd5HK6pMRMbqa3FIhQ+Trdq50qGAAG90jDhAFdsbqgPKjlR/bJwKRhp+HUPpnokmrGuNwumLmpKOD70pNNqG6wAQCeu2okTEaBcwZl4dX5e1W3OZKaQigfp+bz04oO59uJCtU9y4rFB/fohL3HQi8h170d6ver8e2dZ0KI5hzmf14zEqP7dsZXd5zhdxA8RV64XQKzANzqenwrgP+1XkAIYQbwHYBPpJTfhLk9ameRGOB3ySk9cXLPdGx87EI8eYXzyt4d0F6gcV3dWX86O6jlZv9Zu0CIvIv1jv4ePtIjQhHO4NAzBrSs9JJgNOC3AUb9u90yoR+uHZuD84d0R5dU5+yZ/gYLKScDMgiBy0/thVevH4VLR/bE5OHZSDGbdHUrGwhtivQv7zgjAi3xr0d6It6+aUy7b1dvQk0juun0vvj5L+f5fD2YijV623eTEowtBvtdOy4HZpMB3dOSYrbmdkcR7p7yPIALhRD7AFzo+jeEEOOEEB+4lrkOwLkAfiuE2Oz6b1SY26V2EskBEF1SzZ4Dg/uE/ZdJoeWA+hJM+/9z22mabpO8C7Ue9IL7fZ8Q25OmA4vCeO9Xd0zA/L+ciz3PTME5g5xTC/sbIKt01klZbdKTpJ9g+cNbm38bfTKT8fqNo3Flq7SNBJO+roIeviS0yYJ+f3Z/jVvinxAClyiq+HQ0F7WawtsXtWNL3L/DRy452e9yuX7GBbiprW9M8SusYFlKWS6lvEBKOcj1/wrX83lSyttdjz+TUiZIKUcp/vv/9u49uqrqzgP495ebmwchDxKSAHkQIBDeIRACAREICFhEfOCDikhboVpBnKIWq/VRrTJVa2s7ndaqo3ZatVM71nZpqzKtte1q66ut7z5crNaOU21rq46MKNnzR+4Nl+Se9z53n3Pv97MWizxuztnZ9+Sc39nnt/fvlzoaT+HTGSwPLUSSKX2tL9Z8p++m/XbFSOLkRxfYV8gzze9oqtMSgPecbb2smk6i8dC06gq3XTS5sRKlxQl89UMLAABv7LfP0506phL79qzF6hnD8//twuxZzdW4cWMXzl42CV/bmn30NVnkvWPmtNTgV5et8vxzbiycWOfr587t87eyCWXn9ubSbwU/HcWYuPwnuRWNqgoUWTqXczxtgfW6tP0BEvjsZpMXu7iQ58v5stXH5LA4cLqg1VbkJu9Q58iy1bbKfZaunWVzIwoAS6dYr9bpNCp9bOc42+IHfoKWf9syP7Tlr/zGUO/1x2/ZuShze1x4fb/SfztRWSMZAKaPjfecF3IWrYQdihydi58rmzGsIPuxW6e02MVjtuiccikbp/cnV++fziXSrK7zmcugeTFjXDV2WSxjN6m+AhfZPLIOOtFs65ETPf/MqFS+dDj8HRG1FSWOFd/IPbexrN8JfjpGlnWpDfV4pihgsEy2dI4s240QhlWQKOHiRMxHcdHm9PaMrSnLSe5hLo6Tq0+Y5ftnu9uGl3g/o3c8zljUZvtzVjnLbkvG+1l6Li2MwjReY6ibU2tNiwhWTB2eZ8v12v1xW5XO659V+nCNUKyc17nnNIBnAcqZXptcwrDKd0Zp9KGQfe5U/3N6nVZkKS1O4MlPHDXs6yfObR78ePUMd5ONcsUq8J7gYlKSld5Jddi3Zy06W2oAAN/dcQSuWD8Tm3vbbH/O6k8vnQ+t2wM7D195RncREa8jlSszJqItmFiLz55y+LE6wnDRlTj6zEmdOGupuycOXldcSqfL6Lp5vWSt/URBN96fsXY55SfmLJMtXTHshNEVaKm1zqkNa81RN4VJGE6HL9CFzcWPVpYl8eOPLcfbBw7i6M89iju3LkTPhFp8bE0HSosT+Mf+d/H9Z/+MLYvacNtP93luQrvmgC7MY+7aDbPxp9f3Y2aTfR5zmtWNqtu3zMt7+4uLVwyrUHhSdzOuvv8F19twEiSXNZkownFdTRhbXYbnX3kDPRPqsPOup+JT6CQiTpjX7PyiFLv0vGx0rzdc6nOeABUWBstkS9eI7+Ze68l9gP3yVUG4ScOg8AV5F9ymWDSPGrgZ+/3V7xv8WkOqWEv1iOTgI/8dfe3Y/vWnPBWhuHbDbNevdWNaiBOCpjRWYkpjpevXW92ohjGBKlsp721HTtIaLOto9oKJdViQehIWpYlkcbN311KsuP4R+xd5PPW/e1DvRMwj2kdr3R7lJ6ZhkC1dIewHFtuvYRpWGkZZ0vkQ91PEgLwJEm/4nfRmpW5kKXysdmZp+/J2zz+je6Q6CKuHL27fsqiFkrpjW8bK/k2qdz7OvZ59D7gIlq/xkPsfJPWJCgeDZbIV1ojvsP2EtN2aESW47qRO29f8Y/+BkPZOaW6W8LOTLr6hi87RwrOWTdK2LRM297bhptPnDVvKzU0KExC9YFL3SDAnAAdz1lK9fx/NNfZLZNZVlGBjD3OISS8Gy2RLx6Dr3NYax9eEGZNvmNeMOy0KKgBA78T8eQx30dH+qpdZuW/7YtyvoRR40ImWpy+0T+PxSmcA5HdLzT7L/OpWXpLAqhljDpsQGWe6Y1vOEQ7mhLn2q6V4Pfe31o2wXUUlrKeUVNgYLJOD4CeeC1Y7B3BD91Kned3K3knZV+I4YW4TyvNotvuHNY/iTG6oxPRxVcNWCPCqOGDEsSpL5bkgvDYnjFVVjpl9eKGP983S+zt6NbLMX7pLvo+8Mmc5GKfe8zrBz4nb0u9EXjBYJls6zjtucsxyle4x1GXHzDCy3zgoTyYGc76DxgthBJsTA+Qaeg2A7F6vK5b64mnz9GzIp7M132hl+unuPvzsohWhbT9MF6zu0LK8WKHK9b0G56BQGBgsky0dMaybNIxhXJ5gb93S7X3bKSNLi1E9IpySu/ng5O7mwVHDoKOHYQTLQQ5NNxM/M9n9+l7XiY2q9BOWH56/LFChkWzG1ZRjTPXwlTDCoPv9OHJKPc5c4r1KIaXZvx+6xknGpFa+4cgyhYHBMtkKOuK7dEo9KsucA1K/u0km3B/Cd287PG/5qUuHF7KgQzKvOUFj3TAeZQfJTSxPeks5sAv28+0pfXV5Ep8JmHbjlc4+1P1Yn4Jxem915Rinb8YYLFMYGCyTraCnHbfVr4aeMN2ODnkZRVowpIKgl0A7TnYdNUXLdjLfk5ZR9jPQndSEMIIf5Bo7qcFbCofdet0leXYc6b6xcbOSydgq76POG+Y14+cfz11qx4VrOnK2r3wS9r3kvj1rcXxXE06d3wKAaRgUjvw6y5N2QW/63U6eG7of12u8ejwT//ryVbj9gz3efihmdqyYrGU7mdeczpYajCz1NwEsmZBQinAEGUH8oMO630PZpaG4XWJt+DZ9/Vj4NLer1aZyZ5qfPkyIoDFLkB1WWky/iyDs61vDKREeZ04pXDpC2xtOmYNTe1oxsrTYdREjIi8YLJOt6eOCBTlHzxzr6nW5enRaVZZERR6tfhGmoSk4flMxslVt8+OfTzy80ECQGzmvgarT7z7Gx8hoPutpqwUArJreiCuOzY9JtG5GLMtYOnmYXIauD+xcgoc/ujSHe6RCwWCZbFWXJ7EzwEjlUdMbXb1uWOBjcYad01Lj5mW2KnyOkBaadZ2HL2022UMJ5UylxXpOMxvmtRz2eZBgWedqGMDAetT5IuiI90929+Ermwcm3iYTRSh2kabiZ59WN9i6jreh3OTC2qXrFCrHLtE4TtJSOwLj63Jbke+nu/tyuj8yg8EyOcrFsm4uY2Xce85iTKqvcH6hjaljKvG984IX2oiyoBXvypJFWNx++Da++iF/6SsLJtYGaktaokjQmXGztLl3PK53qM5oxeth47SaR2mx9xHFqBZPCBLuHTdnHJpqygdXmXn97fCqY1p136iKklD+vt2MLHNNZmdjh6yKUl9ZaqgleoyriUZxIQoXg2VylJNLus+d1PooXiIimDpGfw5tlLgd0beS7aI/osTfiPzVx89yfpFL5/a1D94s1Y0sxYnz/FWd87oUntPL/SxB6CYHNtdmNVWjPEAqwZqMtKubN3fjsnXuUjD85Bnb9V6VixV4vHIzssxY2VnmTc7nN3ZhZlO1ucYQucRgmSLBS85y+pVlySJ0+EwNyHdBAzGd13ydFd5WTGvE3l3LAm/Ha/51zQi9FSUBwEWtnpz7zo4jXKVNWFk6pX7w45XTG9ExJry/z6EpWWHbsqjN8TUcWXbWUHVoJDlq/fWlTXNNN4EiisEyOcrF0+KhsZ3dOTTdnuUdDXlfatevgwHfs3zvVy+/3xXHzvC9EoidqKZh+HFyt78R/jQ/h9umheO1bs+Jm8ftRbyiOvpsjtfwduOaEwaefq1xOSGdCg//tMlRLlaq8JIXnV4aKI9iDe0CjyxHPFZuqxuBOS3xfnyb+Vg/aLBp2qc3+MsdT9N9uJmqqhi1kdIoypxgHZXuyqcbVwoHg2VylIvUSi/5sOmTLU9w1oL2TUSuYZZ+eMFytDfEOwXnYMZ7FDTYjAq/wc85y9v1NsSQEKq6x14cTtO6lrek/MVgmRzl4mR348Yu7N3lbn3MIycP5EVGcH5UZBwM+KZZFYlgTp81rxMZozjBz5STulucX+SB26D9zq0LNe+X0XIcrZzWgKcvX2W6GRRhDJbJUS7SMGorSjCpfqSr1/5TqpxzGCWU80WQWLmiJIHmUdnzM2c353ZSVT5zs7oC+eM2ZO2dVKd1v0zDiCcRQWUIK6hQ/mB1BnJm4JrulHP4k919GMVg2VKQQOzHH+tDsUXJWAYD+gQd/Y+aS9ZOC1QQRCS3j+zbG9zdnHvBNAxn7CKKI44skyO/16/F7f5HbZxisqaact/r/haCvqkNvn92VEWJ5ShLOUuFW/J6H7Fwot5RTdPOXDIxUBqC1iDKxcb8lEVuqbVfEYM3k86iPoK7dckE002gCGKwTI78VvD7wkbmt5oys6kaH146Uft2q8uTmFjvvpzsBxa3aW+DLpesnWb7/R19A5POSkIqn3xydwuOHVJSvJBpDTRDGqH+gcMa34yV7T164fLI33BfvHY65rYy3YwOx2CZHPl9NMoLh1lhLZ9VU+5+ZOj9Pa2htEGHM5fY30z0TW3AfdsXY4PPKoFW7vjgobLh+ZWIEYzVpFI/wupXp4ItHFkejsc45QM+xyZHfk92ptY6pXAlPVR4i3PsUCQSyoTGxe2jtW8zHyQ0Hiym0sEZLBPlJ44sk6P6ykPlSZtcVLFKEx5dRoV13faWlhDf4MFr4OM22Itvj4RL5+S4XKzgkw0n+Nkb+ifC7qK4YDhDjs48YgLWpXIrvRS74InQrLD6v6RARpa9tn19l3P+8ROXrNSabpBPzls5xXQTAuM6y0T5icEyOSpOFKGuogRAPKoxUbiO6Rzr+rWFtJZwabHzxKW6kaWHfX5uXzs+dfzMsJoUK6f26CtMYi4Nw8x+iShcDJbJlUmpNUlzVWKa15zgwhrkOr7L/YS3/3v3YDiNyIFcDBJObqzEaQvGh7+jGNCZ72vqFo05y8ONiPjqF0HcuqXbdBMoRxgskyubFrTid586GqXJ3BwyfJyZH955r990E3xj4JNbcenvT66fYfm9smT+BoZ+NVaV4ZkrVptuhnbTxlahb2qj6WZQjgSKfESkVkQeEpHfpv4fZfPaKhH5k4h8Icg+yQwRQXGiCHdv68XeXd4X86fcc1qN5MS5w0eIv3feElfbTqflAMD5q6xzTUeNKLH8XtSNq3Y/mZWC8xIrP/mJo2y/73dteDfsNh3WmtxxN7J0YOGtfBoEyZ/fhNwI+pe9G8BepdRkAHtTn1u5EsAjAfdHho2rKcekev1lYjOd3N2M9y+I7vq8cbG0ox5zWqyXPpvVVDXsa+UuR8b+46zewY8zV0vJtGp6YyglhXPh/FVTUK25nPqjFy7Xur1CVlthfxNmKmc5waRlW2HexBCFKWiwvB7A7amPbwdwXLYXicg8AI0AHgy4P4oRv6MIn97QiXOWt2tuTeGZ31aLe89Z7Oln3D4Kz3xvrebwxWUQaeHE2mFfC2MErKV2hPZtUnalHOGlANyE9HE5v5EeQc8ojUqpVwAg9X/D0BeISBGA6wFcEHBfFCFVZc71bNyOUpIZ2QJCt5NxMn+yXyl0ZSkPG5eiNNnauW62/zLUPO798VLsxklDVRnu3LpQ2/YyWY2OTmmM51MU8ofBcmFxPDuJyMMi8kyWf+td7uMjAO5XSv3Rxb62icjjIvL4a6+95nLzZIJTzuDa2WP5SDLCXrhyTdavD13azEp6BLqkuAjTxx6eztHTNnykNspqhqRbPPzRpWit8z8KfNe2cIK0fKf7fNFY5e5Y1mW0y7+dQjb0Bp0BJ8WFY7CslFqplJqZ5d+3AfxZRMYCQOr/V7NsohfAdhHZB+A6AJtFZI/Fvm5SSnUrpbrr6+t9/1IUvmKHUSCeA6OtLJkIdKFqqS3HlzbNw2+uOhpdraNw46ldg987YvJAOec4XAjnjR+FU+a3YMGEQwF+0Dzr4oRg1fRDs+TXdY7Ds3m4GkDUMTuW/Mp26nrp6vflvB0UHUGfe90H4IzUx2cA+PbQFyilTlNKtSql2gCcD+AOpZToy5kEAAANKElEQVTdREDKA/k06zkffO3MBVq3JyJYM3PM4OcttSNw9fGzhrxG6y5Dcc/Zi7CsowH/ummetm0mE0W4afPA+qvLOupxw8mdqCh1TlsiKjRRne+XrVlDK2/GJc2M9Ah6Bt8D4Bsi8iEAfwBwEgCISDeAs5RSZwbcPhEFtG/PWrz+vwdC389J3c0oLynCn17fDyBeF5PaihKMHlmCv7wVrJ/+8yOLMDk1Mn3bB+ajZ0Kt41MYCkdYR19E4zsiClGgs7hS6q9KqRVKqcmp//+W+vrj2QJlpdRtSqntQfZJ8RCfMKkwFCeGvyO636NkogjHdzXH9qnCpoXjsbEn2JKFXa2jBn//ZR0NGFHCEWVT0kFttiIi38xY+pDMicup4qrjhpekj0vbSQ+eyYkKQNaVBkI62x+0Wksu4s5baV1cheJrxrjh64l3B5iEysIj/mzsaUV9TCdBblp4qCT91DGVeOF/3jTYGjKBf/UUCt51R0vmurPPfTLcyWb9qUREHgNkkmT5SIfSYi4N6Mc1J8zKixuNS4+ZDoBPTwsNR5YpFDyRRIuIYN+etdh/4CDKLdZSrnOoiuZWf386WOZRQOakn2/oPgyzFTwpTyYws6la747ImFlN1XjqD3833QyKEAbLFIrGqjLTTaAsMgPlzBiirqIETzisne3WwfTIspatUSEpSRThwMF+082w1TGmctjXnrliNbisfP64fN0MlJck8OVHXjrs618+fR56JsRrHXnSI/7PRCiSdq3qMN0E8kBXoAwcKn/NgWXy6p6zF2nfpu7DcEpjJfbtWQsA6GisxOOXrESiSPgkxZdo9llRkaA4y93P6hljUJwowoVrOnDeUZzjUEg4skyhyIfctHwX1rW9nyPL5FPbaP+VE62EFcSumNqABRNrWbkvkHhOBv7IsnbTTaAcY7BMRFr1x3Q1DMovZcmBlKOwbtpu2TI/pC1TFKTXiZ/FXHQC0zCISLPBIIWPpcmgpppy/PzjK0w3g2Iqffr6zo4jzDaEIoHBMvn2wpVrTDeBAgirwt45y9tT2yfyZugNVmlxEUZYrN7iRmNVGXPnIy26b86CCXVoqik33QyKCAbL5Ft6BJHiKUgQYmfwuIjudZBioKu1Bi9edTTO52ThvNWeKg0fRUdMHo2f7O4z3QyKCAbLFNh1J3WabgL5sK5zHGo1ra2cTVgj11QYulpGadkOj8NounFjV6SDZaJMDJYpsNnNnAARR4kiQUfj8DVjdeHjb/JKqUOTQy9dN1ApbUJ9RaBt8jgkoqAYLFNgiosfxFZRiGcAxiikw/KOhkA/31DFpd2IKBgGy0QFLMxH1BzRI6/CWEGlobIM569iAQki8o/BMgXGoCi+wnzvmCtKXiUT2Y+ZS9ZOC7TdzKW/n7lidaBtEVHhYbBMgQ29vH3xtLlG2kHeFYUYLfMmirwqLU7gV5eu0r7ditJD9bdGlrIWVxTw9EBxwmCZArlz68JhM5r7mcQcG6GOLPNqSH44HDebFrZ63uTm3vHYsqjNX3uIqODxFpsC6Z1UN+xrrHYcH6XFYd4vM1om76rLk7hr20LL71913CzP20wmilhgImJ4maA4YbBM2imOLMfGNSfMxo6+/aFsmyPL5NfCicNvwoM6cLBf+zaJqDAwDYO0OLevffBjxsrxUVtRgplN4ayTzViZouRdBsuRwvMDxQmDZdLioxklaZmzTERRs2JqI1ZOC7ZmM+nTWFVmuglErjENg7RjrEwA0zBIHx3nlFnN1bj5jPnBN0SBvXDlGpQlE6abQeQaR5ZJu+62UaabQBHAdZaJKBsGyhQ3DJZJqxtO6cT4ugrTzaAI4MgyERHlA6ZhkFb9nENDALYumYD1c5pMN4PyxIxxVaabQEQFjCPLpBUn9xEAXLx2emirbFDhWdQ+Ghes7nB+IRFRCBgsk1aMlYmIiCifMFgmrTiyTERERPmEwTJpc+LcZiyZUm+6GURERETacIIfaXP9yZ2mm0BERESkFUeWiYgo8oqLuBYhEZnBkWUiIoq8zb1t6GplwSMiyj2OLBMRUeSVlyTQM6HWdDOIqAAxWCYiIiIissBgmYiIiIjIQqBgWURqReQhEflt6v+sCWUi0ioiD4rI8yLynIi0BdkvEREREVEuBB1Z3g1gr1JqMoC9qc+zuQPAtUqpaQB6ALwacL9ERERERKELGiyvB3B76uPbARw39AUiMh1AsVLqIQBQSr2llHo74H6JiIiIiEIXNFhuVEq9AgCp/xuyvGYKgL+LyLdE5CkRuVZEEgH3S0REREQUOsd1lkXkYQBjsnzrYg/7WAKgC8AfANwNYAuAW7LsaxuAbQDQ2trqcvNEREREROFwDJaVUiutvicifxaRsUqpV0RkLLLnIr8M4Cml1Eupn7kXwEJkCZaVUjcBuAkAuru7lbtfgYiIiIgoHEHTMO4DcEbq4zMAfDvLax4DMEpE6lOf9wF4LuB+iYiIiIhCFzRY3gPgKBH5LYCjUp9DRLpF5GYAUEodBHA+gL0i8jQAAfCVgPslIiIiIgqdKBXNbAcReRPAi6bbEVGjAfzFdCMiin1jjX2THfvFGvvGGvsmO/aLNfaNtSj0zXilVH22bzjmLBv0olKq23QjokhEHmffZMe+sca+yY79Yo19Y419kx37xRr7xlrU+4blromIiIiILDBYJiIiIiKyEOVg+SbTDYgw9o019o019k127Bdr7Btr7Jvs2C/W2DfWIt03kZ3gR0RERERkWpRHlomIiIiIjIpksCwia0TkRRH5nYjsNt0eU5z6QUS2iMhrIvLL1L8zTbQzCkTkVhF5VUSeMd0Wk5z6QUSWicg/Mo6ZS3PdxqgQkRYR+YGIPC8iz4rITtNtMsFNP/C4GSAiZSLyCxH5VaqvrjDdJhPc9AOvT4cTkYSIPCUi3zXdFpPs+iHKx0zklo4TkQSAf8FAkZOXATwmIvcppQqq6p+HfrhbKbU95w2MntsAfAHAHYbbYdptcO6HR5VSx+SmOZH2HoBdSqknRaQSwBMi8lChnWvgvh943ADvAOhTSr0lIkkAPxaRB5RSPzPdsBxz2w+8Ph2yE8DzAKpMN8Qwp36I5DETxZHlHgC/U0q9pJQ6AOAuAOsNt8kE9oMHSqkfAfib6XaYxn5wTyn1ilLqydTHb2LgBN5ktlW5x35wTw14K/VpMvWv4Cb+sB+8EZFmAGsB3Gy6LSbFuR+iGCw3AfhjxucvozBP3G774UQR+bWIfFNEWnLTNIq53tTj0wdEZIbpxkSBiLQB6ALwc7MtMcuhH3jcYPAx8i8BvArgIaVUQR4zLvuB16cBnwVwIYB+0w0xzE0/RPKYiWKwLFm+Voh3rG764TsA2pRSswE8DOD20FtFcfckBkp6dgL4PIB7DbfHOBEZCeAeAOcppd4w3R5THPqBx02KUuqgUmoOgGYAPSIy03SbTHDRD7w+ARCRYwC8qpR6wnRbTHLZD5E9ZqIYLL8MIPNuohnAfxtqi0mO/aCU+qtS6p3Up18BMC9HbaOYUkq9kX58qpS6H0BSREYbbpYxqXzLewB8TSn1LdPtMcWpH3jcDKeU+juAHwJYY7gpRln1A69PgxYDOFZE9mEgnbJPRP7dbJOMcOyHKB8zUQyWHwMwWUQmiEgJgFMB3Ge4TSY49oOIjM349FgM5BoSWRKRMSIiqY97MHAO+KvZVpmR6odbADyvlPqM6faY4qYfeNwMEJF6EalJfVwOYCWAF8y2Kvfc9AOvTwOUUhcppZqVUm0YuI7/l1Jqk+Fm5ZybfojyMRO51TCUUu+JyHYA3weQAHCrUupZw83KOat+EJFPAnhcKXUfgHNF5FgMzGb/G4AtxhpsmIjcCWAZgNEi8jKAy5RSt5htVe5l6wcMTL6BUupLADYAOFtE3gOwH8CpqnArEy0GcDqAp1O5lwDw8dTIaSHJ2g8AWgEeN0OMBXB7arWiIgDfUEoV4lJgWfuB1yfyKi7HDCv4ERERERFZiGIaBhERERFRJDBYJiIiIiKywGCZiIiIiMgCg2UiIiIiIgsMlomIiIiILERu6TgiIjpEROoA7E19OgbAQQCvpT5/Wym1yEjDiIgKBJeOIyKKCRG5HMBbSqnrTLeFiKhQMA2DiCimROSt1P/LROQREfmGiPxGRPaIyGki8gsReVpEJqVeVy8i94jIY6l/i83+BkRE0cdgmYgoP3QC2AlgFgYq8k1RSvUAuBnAjtRrPgfgBqXUfAAnpr5HREQ2mLNMRJQfHlNKvQIAIvJ7AA+mvv40gOWpj1cCmC4i6Z+pEpFKpdSbOW0pEVGMMFgmIsoP72R83J/xeT8OneuLAPQqpfbnsmFERHHGNAwiosLxIIDt6U9EZI7BthARxQKDZSKiwnEugG4R+bWIPAfgLNMNIiKKOi4dR0RERERkgSPLREREREQWGCwTEREREVlgsExEREREZIHBMhERERGRBQbLREREREQWGCwTEREREVlgsExEREREZIHBMhERERGRhf8HKpBElf2yIYUAAAAASUVORK5CYII=\n", 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", 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\n", 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", 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\n", + "image/png": 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", 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" ] @@ -2234,6 +857,7 @@ }, { "cell_type": "markdown", + "id": "48300879", "metadata": {}, "source": [ "### pitch" @@ -2242,11 +866,12 @@ { "cell_type": "code", "execution_count": 22, + "id": "5ac69211", "metadata": {}, "outputs": [ { "data": { - "image/png": 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\n", 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", 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" ] @@ -2286,6 +911,7 @@ }, { "cell_type": "markdown", + "id": "b69bd78f", "metadata": {}, "source": [ "### Speed" @@ -2294,11 +920,12 @@ { "cell_type": "code", "execution_count": 23, + "id": "fed7bb58", "metadata": {}, "outputs": [ { "data": { - "image/png": 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\n", + "image/png": 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", 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" ] @@ -2338,6 +965,7 @@ }, { "cell_type": "markdown", + "id": "a1c58fe6", "metadata": {}, "source": [ "### MFCC" @@ -2346,6 +974,7 @@ { "cell_type": "code", "execution_count": 24, + "id": "cbdc41f2", "metadata": {}, "outputs": [], "source": [ @@ -2374,6 +1003,7 @@ { "cell_type": "code", "execution_count": 28, + "id": "b0da4dd4", "metadata": {}, "outputs": [], "source": [ @@ -2387,6 +1017,7 @@ }, { "cell_type": "markdown", + "id": "58ffcc76", "metadata": {}, "source": [ "### Plot MFCC" @@ -2395,6 +1026,7 @@ { "cell_type": "code", "execution_count": 30, + "id": "4e23c300", "metadata": {}, "outputs": [ { @@ -2416,7 +1048,7 @@ }, { "data": { - "image/png": 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\n", 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sSRWxdCnRL6XRZbsRVRI3m/SvHCrtntoi+8JCIlJybJERnRNCqMc5Rah0Gh9URebMI6P6Vy/L7zm2SOepRrxY80zbNcwjUmKYx2+FEEI8Pp63X+kz5meoxkte39wuje/SSKl0DzPOJgQzGqmKIpIonylCzIpo0rZoTNVgv9fVmOamphirEEKJuWnM0/x+VZE7Glem8yzHHWk8UB6DEEpU13W5v/bXNA/lXoO8n1VMkxXlI6Zn3Nnvau65HPE03teOCsrvVzWeOufztr6f2of529SKx9I5Y3yfzais1nPldmtk1taIcQt2BJEVtaX90m02s1Ms/MUHAHCFwgcAcIXCBwBwhcIHAHCFwgcAcIXCBwBwhcIHAHCFwgcAcIXCBwBwhcIHAHCFwgcAcIXCBwBwhcIHAHDlziXEp5XBe2NF+hCaq/Gb8greupq/ldSgq2+3kh7yPlmVO0ZdqT5dQ0+J5lrf83Nax+qK7kfrst9ahV1XJs9JCW/SV0Yf1Cvcj6uYR1l53VxRvbEyetXWnPRwIquZy3NH4xpDteK78Vy6cruMV16BX89vXXfatzNWmpc0gLgu7R4kESEe6ufcn5qyoOOpyQCZJpJoW/N5VopCCPbYdPNkAV39vr+6CpZpzq1LMkB/eVEOSM8dl5qIIts5SELbZCQjNGk6SR5nSUep0k/ydXXfsrFq/pQcYL/reTRjI1lgSlzQpi4aqRGpPVUihCZj9Lt0TUk+0P7K80/vr+Nt9acmRej7cz0mOfSaemGkaVR9KM9VpRCkOVW1Vb8bOeFC3yl911Mf1u0r81Dn5JDTaBZ24si0T5MkDiS4mCk+IdjJNq175MtrQsYd+IsPAOAKhQ8A4AqFDwDgCoUPAOAKhQ8A4AqFDwDgCoUPAOAKhQ8A4AqFDwDgCoUPAOAKhQ8A4AqFDwDgCoUPAOAKhQ8A4MqdsURW7ENoRUjkWJRW7FDeL7EUVZxF3pZojyiRHlXkx2DHVJSfjXgflX+vojXsrrDidzS+I+bYkEYU0GC0VWNRqqgQK4pE4nemvRqFonEu63X1r9GYsp2fXcdAI3NOFrNzosZE5efV59P4EO2Pk9PxHI1C6Y04l5XEyejcyX3UuH605oPOl43EGaW2tGKqppgZK1oqhBB0nnTGNax5qv3aG9FMm+NyydN7Zb8VzSS6/Cyq6lfjXdT3S3/X83ojOuZU7tXN50bFmlutCKS8X/o4LkvUUG7hoDFX8k6EfKzeS+K34tVlu32325XH61C0VCNeq3rv8jzRubMtkTldega9evWtyPE/GlW0kutbUVhGRFMIIcQU1VNdyxoPifTRkY0SB9blcbD6pbqpxikZ74zGJh2ILTLj62S/1pFW9Nnskm90FAAAXxEUPgCAKxQ+AIArFD4AgCsUPgCAKxQ+AIArFD4AgCsUPgCAKxQ+AIArFD4AgCsUPgCAKxQ+AIArFD4AgCt3pjNYhm1ZMT7KqtlTIoKu7K4pA4v5iu5vupL2eIFyrXye3t9sa393ikNstcVYIbyX5w7hSpo1tqE7KSvs62rmMcxXMR+2shK9rpi+zCvVl7YMF+dy3jZd316lfdrSlc8bSRbTeFyW1es1KSL3na6sXq2Cno4ddEV3TW+QY7vcH5q+ICvwT2OrCQGykv30uyQm9K9elN91f+qjTlaqj8cyNnll/2ikP4wPMXuulmglA0h/T/O0lcaRryPpDK0V9vOc0HaZKRzar3qv3EcyN4POI2uF/JvrskvGI+Z0Bk1J0LHN43h5Uc6XlAT9hkz30vtX/Tn+3l+U8zuZZ91ZTrOQc/SduS7PMLX/7Kz8j6X1CWyMfRqD/tXL2b7b15rapekqxydyi3SP6/ItqRgpBs20jnyszI1exy7v1++CXivNT/0WxSq5Zj4eFSvpRL9hB76t1XfaSAZpyelBVbpDI3XlNv7iAwC4QuEDALhC4QMAuELhAwC4QuEDALhC4QMAuELhAwC4QuEDALhC4QMAuELhAwC4QuEDALhC4QMAuELhAwC48tbpDN1GVmSXVeejtZq4JgfEeY01kwNaq3NbKQSiWkHcovfPK/DrquGNdmfLk9M7fw+d3L+fp07ovWK1Qv7R7NiqX6WPYlplXVdWj7pCft7WlAS9bm88byNZYBovedZqvPKK7pp80Bi7kjBRVs2PmiKQ29BaWT0lC/S62r/0Zyer3uee0zSNuJO+T32o969SJ3IKgo7X0k56CDlVQdIhNNEg90c1z7S/82r/LyVpQlkr5Mu+/dOn5dg0TtoXw17aldug7TuQbqL3Gq5KikBOV+h0Pl2VsSn3b6SvaB9o3+V2GQkVy6rfJeUg30MTGXTs9F6pjzTxJPSvjXZLeorVRzJPq3dZ+yunLjTSF/L7ZaUkVO3Wb40mf+i7uB1m16rSUR48nJ+/Nfq98Q2t7pX7Vr+n1vdQx1BTIVLfar++WZ5CPti4byt14g78xQcAcIXCBwBwhcIHAHCFwgcAcIXCBwBwhcIHAHCFwgcAcIXCBwBwhcIHAHCFwgcAcIXCBwBwhcIHAHCFwgcAcIXCBwBw5e5YomX6WWI+9i9f2scasUOVFCFhxROF0IgoUgdigw7FHunv036NTbEiQUIIcTluD63InBSv0WlsynIeq6Jn9xKLEiW2JMff9BIdEwZ57mhEz8j525/+dPz3dYmI6RpRI916jFNZPXpQLi8RK0OONropfWTFOFX7ZFw6jSVJ8yguGtNtGicZQ+3D1Mca0dTpeEs0U44N0n4dUhTR+MN8HKu4oxzXIs+yf1Wia4YnT0obNusQQgiL+/fL5c2II4mA2cl45j5uzS2Jl5rOkmfZvZpH6mgPVxFiqQ8HvWY1nvL+pTnXX5d79dqH6ViND8p9EULpgyoeSI/ViK98SRmD/bNnpSlpni3unZWDzyVWKF9fn1Xmye7pc2ljOqYVYZaea2/0awghxPTOdPKe7F/LsRoFlOehxO9UfZ/imIad/f70V+M3YJB4rSDXWpyWb4AVJ6Tfq+H1q/mzrOaxYDpeGu/TSyRVMKKmeo04ynOjFXGUzq/jouRd1nloREJFK0ZN+13nwR34iw8A4AqFDwDgCoUPAOAKhQ8A4AqFDwDgCoUPAOAKhQ8A4AqFDwDgCoUPAOAKhQ8A4AqFDwDgCoUPAOAKhQ8A4Mqd6Qz95WUIoV4Re/HgYTlAVkEfplW5l+bvU/qBkaww3myY72sd+6bnH0p8aNBV1K1EgWoF/nQPXcE8dmUl+8FYzVxTELTduiL6pFoxfdzeX5X0hrgq7Vu++071bwh1kkM1XmlF9UGSIAZjhX5d9V5HI68a30n/aAqBrkof76X0gpU8t6Yr9OkZNSXhqmzn1Iq4kWfRuaHJAWlsoiY26IruRqpEtbJ/SOMo7V9945t2u1N/Di9KmkAvq/XncW6t0B+P1qmtJdkg6HyrUh12s3avv/c4zOh8W2s6Q+oXPdZY/V7v211dln363Dm1pXV+SsbQ5BBtl6aTlJ2SvKFJJ3nfffnuWCv/67sj291pSYLI8yBu5PpGf+s5VtKKymMYQj3/u7N7s/OjlcJxLskfOifz3GkkmkTto/U8kWB4WVIpevleTPvkncnJNVESNjQxRNMoys4y9l1vfGd/1cQF4/2qGO9ylezRSNaYNe+NjgIA4CuCwgcAcIXCBwBwhcIHAHCFwgcAcIXCBwBwhcIHAHCFwgcAcIXCBwBwhcIHAHCFwgcAcIXCBwBwhcIHAHCFwgcAcOXOWKIux7VIXMb2yZNpO8fkjP/DiJAwIiZ6OadbSrxPjovReJJlI67irnu27m9pnD9IVNDufIxmuXlVoi92lyXmY3sxbvd7IxYphLC/GaNKVsclnmRxZHd73h+t2JVQYktiIw5mf7Od/X50r0T5RInyydvL0xJvstAIotT3N09fTPuunr1647bc++j9abv/2WfVOSGUKJQQQthdjvE1/VZjjUpbF+sxFmVxvDF/1/HIx+rv/U25bm/EROUxDiGE7fnYlvXDs2nfxV/+7bR9/apE7SxWYx+t75c+Xp2WNua+zW0KoR7b3Eadb9pH+2uJW0o6iaE6elzip4YUM7N7LXFO0gf5Xa76RfrbfJdljFZyr/58jBXaX0hskbDmrz7L5eclxim/V/pOnH34Xml32r/75OfmtbrVqjpO992Wvy17mS99NSfHvjl6eF+upbFb+3Qd+12P+r368ul4fenjflviknJ/69w9enhv2t6+nMfraL9uvlbGI6bnreaOjM321TwGKs/zEMqc2LzzYNqn/RmlP3N/VPNF25j6oDWnzXOsuKYQwpCi0fRe0Yiq0/Yt7p3NfrfwFx8AwBUKHwDAFQofAMAVCh8AwBUKHwDAFQofAMAVCh8AwBUKHwDAFQofAMAVCh8AwBUKHwDAFQofAMAVCh8AwJU70xm2X4xJDLoq+OL09M2vbqykfZCu6i3pCbqav3VdawXwVsqBda/qvM162t4cp5X37z8s99qUPog3aZVzudf+uKwQHtMK49NxIVSpEMO6rOy/X40r6Hf7soq7njesxlX+h4Wslr4rK9X3y/H3m+PS1r4rQ7zclhXbj16NY9tdvCzt0lXSl+M9jnalLWdbSQtIK90P98q9ohwbXpVUh3A69kcv/bY/LivRL9N9u2151n5ZxmBYpNSKfVnpfvn66bS9vikr3IcujYOMx6DPlftD51b1XGkenZckirNHj+fnhxDi9ZgskMdldq2Xz8d/j8qzVH2c9g/rkpChYxt7WZX+IrXnRUk2GD74drlWep7luYynvhP5vpsy34ajkiSh4tW4mv/wxS/LvpMydt37H4730pOkD3J/x0tJBTgvaQPH/1GanVIl+suL2b7xIuN7v/7N/2q21SR9sPvss2l7+W5KNHhQkg203VN/abuX8pTX4zzbf/nFtKuXFITlO49Ks98Z50x/Vt6P/E6FUOZO1Lmb50sIYf3BR2P7T8v5i+vSrsXnPyvn6TXyY63L2G5Ox3etX0m6ya6cEy/S2Ojc1LnT6zzq5vfU33PKzt5O7pn2W3Pz1nmHUx3GtuzPS79c/uTTaftkdkbBX3wAAFcofAAAVyh8AABXKHwAAFcofAAAVyh8AABXKHwAAFcofAAAVyh8AABXKHwAAFcofAAAVyh8AABXKHwAAFfuTGdY3r8fQqhXv37940+m7SgpCTkJYRjsxANTX1btDl032zc00hOs+/c7Pa9Pv9t1Pb5FasTyeF23L4Swvy6rx9+8GPvmy4//edq3vSwpBd1ynhCxOi6rtF+/upr9vr+x+yC3e3tRrr86Kdf62q9/LYQQwv1vf13OL9c6f1VWwP/lZ+Mq/69+UVayvznfynnjfTcPS7LA2XslUeHhd94bf38sq8+LFz8qq8f/+C/+KYQQwsVPyrMujjvZXsz29bv52K/ulb5cbsr20Wnpg/22D7ctVvN5cPm8rC5/8m5Ztf7xr43PtX5Q0ghOP3yvXP+ynPfsh+NK8F9+/GR2/da9rLbsrsoq9Iuj8vtyU17PfN7RWUkT0Ll1cz7Oyde/LO/qzdOSZnGoP1VcjfPs3jfK+vaPPiqJBs8/HVMEnv2wzJ3rfy7vxPGH45xZnul4lWe5935JLzk6HZ9nuS6/H52V8cjv3/7vfzzte/VZSaj44h/Gvr/4pMytk2+X87/1W9+atreXYxs//8Hn076bF6WP1o/GeXT/w/vlueT9vPjyKrW5zLev/+f3y7XOyzj//P/9Ytz3tLxT66+Xsbv/zbEPvvFfPpr26bu+fvSPIYQQulXpl+c/LWkZP/rzH03blz8f75v7PYQQTh6XPnjwzQfjvnel3+9JKszN2MarZyVBQ61OynXznNN2Kevbe+h7a30jW6xrLY4lieLD92e/m/d84zsCAPAVQOEDALhC4QMAuELhAwC4QuEDALhC4QMAuELhAwC4QuEDALhC4QMAuELhAwC4QuEDALhC4QMAuELhAwC4QuEDALgS74oR+v0/+rshhBC21yVa4+L5y+bxIRyOAlqsSqTHYEQQtSIsWtfNOuO8/kCsUb8rcTB63yOJuTh9MEZ5fPN7Jernu98t8Tz3z8bz3r1XrvXwuES07Iex3S+vynOvFuW53zkusSdDGK/VxfL7zb7Ef8Q4Ps8wlG26OU8AAAJOSURBVLbu+tIvR4tdOr88o15r25f4j6fnY9TIz59IPJCcuEy31fSRS0lQ+tE/jRFHpxLRci6xRs+elHic3/vf74YQQvjOwxfTvs2iRLh0YWzj612JAlL5uV9cH0/7fvG8RKW8LLcKi/Q4i8V8nz7P5kjmnkyTT8Y0mfD//7bETP3mfytRJ7/xrRJj8+j4cmz3TWnLT74o258/GefE2alEWklq0lHquvcelQYcLcv2dl/G4/Nn4zU+/VkZhA/eL/d6dH88NsrY535TJ+uyb7Msc7bryv6Lm7GT/uYH5Vk/++nzafu//84Y0/TR4zKGOqefXYzxO798KvPtebnXxUW57jZFcD39sgzip/9YIq2uz8c+/t0/+K1p33/6bnmeB5vxXbvalYn68Wdl+8//7w+n7Q++O7b7f/z2g2nfu6flXX1+OQ7IDz4ubX33HX3/xs795NPLad/3/+rjafvxh4+n7f/5vz4IIYTw4aPSR8uu9NHzy7GP/vr7pS8+/sEvpu3/8BvjnNMxvndaBlfnUR7zq+syhjflVZy+B5dXMkZPy3O/fDHOqY1EnG2vS7tePCtxZjdX43k3l/KN25f+6tO2xsT1Q9ne3+xm52gd6GV/+X0wj81xRkcb+V4/LN/m//Onv97MQ+IvPgCAKxQ+AIArFD4AgCsUPgCAKxQ+AIArFD4AgCsUPgCAKxQ+AIArFD4AgCsUPgCAKxQ+AIArFD4AgCsUPgCAK3emMwAA8FXDX3wAAFcofAAAVyh8AABXKHwAAFcofAAAVyh8AABX/gV89t24cbFEtQAAAABJRU5ErkJggg==", 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" ] @@ -2438,9 +1070,802 @@ "librosa.display.specshow(mfccs, sr=44100, x_axis='time')" ] }, + { + "cell_type": "markdown", + "id": "f4984639", + "metadata": {}, + "source": [ + "### Tokenizer" + ] + }, + { + "cell_type": "code", + "execution_count": 5, + "id": "05d75818", + "metadata": {}, + "outputs": [], + "source": [ + "class Tokenizer:\n", + " \n", + " def __init__(self, translations):\n", + " self.translations = translations\n", + " self.unk = -1\n", + " \n", + " def build_dict(self):\n", + " text = ''\n", + " for t in self.translations:\n", + " text += t\n", + " \n", + " char_counts = Counter(text)\n", + " sorted_vocab = sorted(char_counts, key=char_counts.get, reverse=True)\n", + " int_to_char = {ii: word for ii, word in enumerate(sorted_vocab, 1)}\n", + "\n", + " char_to_int = {word: ii for ii, word in int_to_char.items()}\n", + " \n", + " return int_to_char, char_to_int\n", + " \n", + " def encode(self, sent, char_to_int):\n", + " \n", + " encoded = []\n", + " char_list = list(sent)\n", + " for c in char_list:\n", + " try:\n", + " encoded.append(char_to_int[c])\n", + " \n", + " except KeyError:\n", + " encoded.append(self.unk)\n", + " return encoded\n", + " \n", + " def decode_text(self, encoded_chars, int_to_char):\n", + " \n", + " decoded = ''\n", + " for e in encoded_chars:\n", + " try:\n", + " decoded += e\n", + " \n", + " except KeyError:\n", + " decoded += ''\n", + " \n", + " return decoded\n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + "\n", + " " + ] + }, + { + "cell_type": "markdown", + "id": "18f482fc", + "metadata": {}, + "source": [ + "### Data Generator" + ] + }, + { + "cell_type": "code", + "execution_count": 6, + "id": "6c40adbf", + "metadata": {}, + "outputs": [], + "source": [ + "class DataGenerator(tf.keras.utils.Sequence):\n", + " def __init__(self, translations, audios, batch_size=32, shuffle=True):\n", + " self.audios = audios\n", + " self.labels = translations\n", + " self.batch_size = batch_size\n", + " self.len = int(np.floor(len(self.labels) / self.batch_size))\n", + " self.shuffle = shuffle\n", + " self.on_epoch_end()\n", + " \n", + " self.tokenizer = Tokenizer(translations)\n", + " self.int_to_char, self.char_to_int = tokenizer.build_dict()\n", + " \n", + " self.cur_index = 0\n", + "\n", + " def __len__(self):\n", + " return self.len\n", + " \n", + " def encode_text(self, translations):\n", + " encoded_trans = []\n", + " \n", + " for t in translations:\n", + " encoded = self.tokenizer.encode(t, self.char_to_int)\n", + " encoded_trans.append(encoded)\n", + " \n", + " return encoded_trans\n", + " \n", + " def get_max_len(self, items):\n", + " maximum = 0\n", + " for i in items:\n", + " if len(i) > maximum:\n", + " maximum = len(i)\n", + " \n", + " return maximum\n", + "\n", + " \n", + " def __data_generation(self, batch_translations, batch_audios):\n", + " \n", + " self.cur_index = 0\n", + " encoded_trans = self.encode_text(batch_translations)\n", + " \n", + " maximum_trans_len = self.get_max_len(encoded_trans)\n", + " maximum_audio_len = self.get_max_len(batch_audios)\n", + " \n", + " \n", + " encoded_trans_np = np.zeros((len(encoded_trans), maximum_trans_len), dtype=\"int64\")\n", + " padded_audios_np = np.zeros((len(batch_audios), maximum_audio_len), dtype=\"float32\")\n", + " \n", + " label_length = np.zeros(padded_audios_np.shape[0], dtype=\"int64\")\n", + " input_length = np.zeros(encoded_trans_np.shape[0], dtype=\"int64\")\n", + " \n", + " \n", + " ind = 0\n", + " for trans, audio in zip(encoded_trans, batch_audios):\n", + " encoded_trans_np[ind,0:len(trans)] = trans\n", + " label_length[ind] = len(trans)\n", + " \n", + " padded_audio = np.pad(audio, (0, maximum_audio_len - len(audio)), mode = 'constant', constant_values=0)\n", + " \n", + " padded_audios_np[ind, ] = padded_audio\n", + " input_length[ind] = len(audio)\n", + " \n", + " ind += 1\n", + " \n", + " outputs = {'ctc': np.zeros([self.batch_size])}\n", + " inputs = {'the_input': tf.convert_to_tensor(padded_audios_np), \n", + " 'the_labels': tf.convert_to_tensor(encoded_trans_np), \n", + " 'input_length': tf.convert_to_tensor(input_length), \n", + " 'label_length': tf.convert_to_tensor(label_length) \n", + " }\n", + " \n", + " return (inputs, outputs)\n", + " \n", + " def on_epoch_end(self):\n", + " \n", + " self.indexes = np.arange(self.len*self.batch_size)\n", + "\n", + " if self.shuffle == True:\n", + "\n", + " self.indexes = self.indexes.reshape(int(self.len), int(self.batch_size))\n", + " np.random.shuffle(self.indexes)\n", + "\n", + " for i in range(self.len):\n", + " np.random.shuffle(self.indexes[i])\n", + "\n", + " self.indexes = self.indexes.reshape(int(self.len*self.batch_size))\n", + "\n", + "\n", + " def __getitem__(self, index):\n", + " indexes = self.indexes[int(index*self.batch_size):int((index+1)*self.batch_size)]\n", + " \n", + " self.cur_index += self.batch_size\n", + " \n", + " if self.cur_index >= len(self.labels):\n", + " self.cur_index = 0\n", + "\n", + " batch_labels = [self.labels[int(k)] for k in indexes]\n", + " batch_audios = [self.audios[int(k)] for k in indexes]\n", + " \n", + " batch_labels = self.labels[self.cur_index: self.cur_index + self.batch_size]\n", + " batch_audios = self.audios[ self.cur_index: self.cur_index + self.batch_size]\n", + " \n", + " \n", + " return self.__data_generation(batch_labels, batch_audios)" + ] + }, + { + "cell_type": "markdown", + "id": "5bc28e25", + "metadata": {}, + "source": [ + "### Custome LogMelSpectrogram Layer" + ] + }, + { + "cell_type": "code", + "execution_count": 7, + "id": "da5b50ac", + "metadata": {}, + "outputs": [], + "source": [ + "class LogMelSpectrogram(tf.keras.layers.Layer):\n", + " \"\"\"Compute log-magnitude mel-scaled spectrograms.\"\"\"\n", + "\n", + " def __init__(self, sample_rate, fft_size, hop_size, n_mels,\n", + " f_min=0.0, f_max=None, **kwargs):\n", + " super(LogMelSpectrogram, self).__init__(**kwargs)\n", + " self.sample_rate = sample_rate\n", + " self.fft_size = fft_size\n", + " self.hop_size = hop_size\n", + " self.n_mels = n_mels\n", + " self.f_min = f_min\n", + " self.f_max = f_max if f_max else sample_rate / 2\n", + " self.mel_filterbank = tf.signal.linear_to_mel_weight_matrix(\n", + " num_mel_bins=self.n_mels,\n", + " num_spectrogram_bins=fft_size // 2 + 1,\n", + " sample_rate=self.sample_rate,\n", + " lower_edge_hertz=self.f_min,\n", + " upper_edge_hertz=self.f_max)\n", + "\n", + " def build(self, input_shape):\n", + " self.non_trainable_weights.append(self.mel_filterbank)\n", + " super(LogMelSpectrogram, self).build(input_shape)\n", + "\n", + " def call(self, waveforms):\n", + " \"\"\"Forward pass.\n", + " Parameters\n", + " ----------\n", + " waveforms : tf.Tensor, shape = (None, n_samples)\n", + " A Batch of mono waveforms.\n", + " Returns\n", + " -------\n", + " log_mel_spectrograms : (tf.Tensor), shape = (None, time, freq, ch)\n", + " The corresponding batch of log-mel-spectrograms\n", + " \"\"\"\n", + " def _tf_log10(x):\n", + " numerator = tf.math.log(x)\n", + " denominator = tf.math.log(tf.constant(10, dtype=numerator.dtype))\n", + " return numerator / denominator\n", + "\n", + " def power_to_db(magnitude, amin=1e-16, top_db=80.0):\n", + " \"\"\"\n", + " https://librosa.github.io/librosa/generated/librosa.core.power_to_db.html\n", + " \"\"\"\n", + " ref_value = tf.reduce_max(magnitude)\n", + " log_spec = 10.0 * _tf_log10(tf.maximum(amin, magnitude))\n", + " log_spec -= 10.0 * _tf_log10(tf.maximum(amin, ref_value))\n", + " log_spec = tf.maximum(log_spec, tf.reduce_max(log_spec) - top_db)\n", + "\n", + " return log_spec\n", + "\n", + " spectrograms = tf.signal.stft(waveforms,\n", + " frame_length=self.fft_size,\n", + " frame_step=self.hop_size,\n", + " pad_end=False)\n", + "\n", + " magnitude_spectrograms = tf.abs(spectrograms)\n", + "\n", + " mel_spectrograms = tf.matmul(tf.square(magnitude_spectrograms),\n", + " self.mel_filterbank)\n", + "\n", + " log_mel_spectrograms = power_to_db(mel_spectrograms)\n", + "\n", + " # add channel dimension\n", + " log_mel_spectrograms = tf.expand_dims(log_mel_spectrograms, 3)\n", + "\n", + " return log_mel_spectrograms\n", + "\n", + " def get_config(self):\n", + " config = {\n", + " 'fft_size': self.fft_size,\n", + " 'hop_size': self.hop_size,\n", + " 'n_mels': self.n_mels,\n", + " 'sample_rate': self.sample_rate,\n", + " 'f_min': self.f_min,\n", + " 'f_max': self.f_max,\n", + " }\n", + " config.update(super(LogMelSpectrogram, self).get_config())\n", + "\n", + " return config" + ] + }, + { + "cell_type": "markdown", + "id": "cd87e420", + "metadata": {}, + "source": [ + "### Model for logspectorgram generation" + ] + }, + { + "cell_type": "code", + "execution_count": 8, + "id": "7880e388", + "metadata": {}, + "outputs": [], + "source": [ + "def preprocessin_model(sample_rate, fft_size, frame_step, n_mels, mfcc=False):\n", + "\n", + " input_data = Input(name='input', shape=(None,), dtype=\"float32\")\n", + " featLayer = LogMelSpectrogram(\n", + " fft_size=fft_size,\n", + " hop_size=frame_step,\n", + " n_mels=n_mels,\n", + " \n", + " sample_rate=sample_rate,\n", + " f_min=0.0,\n", + " \n", + " f_max=int(sample_rate / 2)\n", + " )(input_data)\n", + " \n", + " x = BatchNormalization()(featLayer)\n", + " model = Model(inputs=input_data, outputs=x, name=\"preprocessin_model\")\n", + "\n", + " return model" + ] + }, + { + "cell_type": "code", + "execution_count": 9, + "id": "a13c9798", + "metadata": {}, + "outputs": [], + "source": [ + "def BidirectionalRNN(input_dim, batch_size, sample_rate=22000,\n", + " rnn_layers=2, units=400, drop_out=0.5, act='tanh', output_dim=224):\n", + "\n", + " input_data = Input(name='the_input', shape=(\n", + " None, input_dim), batch_size=batch_size)\n", + " \n", + "\n", + "\n", + " \n", + " x = Bidirectional(LSTM(units, activation=act,\n", + " return_sequences=True, implementation=2))(input_data)\n", + " \n", + " x = BatchNormalization()(x)\n", + " x = Dropout(drop_out)(x)\n", + "\n", + " for i in range(rnn_layers - 2):\n", + " x = Bidirectional(\n", + " LSTM(units, activation=act, return_sequences=True))(x)\n", + " x = BatchNormalization()(x)\n", + " x = Dropout(drop_out)(x)\n", + "\n", + " x = Bidirectional(LSTM(units, activation=act,\n", + " return_sequences=True, implementation=2))(x)\n", + " x = BatchNormalization()(x)\n", + " x = Dropout(drop_out)(x)\n", + "\n", + " time_dense = TimeDistributed(Dense(output_dim))(x)\n", + "\n", + " y_pred = Activation('softmax', name='softmax')(time_dense)\n", + "\n", + " model = Model(inputs=input_data, outputs=y_pred, name=\"BidirectionalRNN\")\n", + "\n", + " return model" + ] + }, + { + "cell_type": "code", + "execution_count": 24, + "id": "5bc2f669", + "metadata": {}, + "outputs": [], + "source": [ + "def simple_rnn_model(input_dim, output_dim=224):\n", + "\n", + " input_data = Input(name='the_input', shape=(None, input_dim))\n", + " simp_rnn = GRU(output_dim, return_sequences=True,\n", + " implementation=2, name='rnn')(input_data)\n", + " y_pred = Activation('softmax', name='softmax')(simp_rnn)\n", + " model = Model(inputs=input_data, outputs=y_pred, name=\"simple_rnn_model\")\n", + " model.output_length = lambda x: x\n", + " return model\n" + ] + }, + { + "cell_type": "code", + "execution_count": 25, + "id": "0d55f68c", + "metadata": {}, + "outputs": [], + "source": [ + "def ctc_lambda_func(args):\n", + " y_pred, labels, input_length, label_length = args\n", + " return K.ctc_batch_cost(labels, y_pred, input_length, label_length)" + ] + }, + { + "cell_type": "code", + "execution_count": 26, + "id": "a7810465", + "metadata": {}, + "outputs": [], + "source": [ + "def input_lengths_lambda_func(args):\n", + " hop_size = frame_step\n", + " input_length = args\n", + " return tf.cast(tf.math.ceil(input_length/hop_size)-1, dtype=\"float32\")" + ] + }, + { + "cell_type": "code", + "execution_count": 27, + "id": "0cd84d9b", + "metadata": {}, + "outputs": [], + "source": [ + "def add_ctc_loss(model_builder):\n", + " the_labels = Input(name='the_labels', shape=(None,), dtype='float32')\n", + " input_lengths = Input(name='input_length', shape=(1,), dtype='float32')\n", + " label_lengths = Input(name='label_length', shape=(1,), dtype='float32')\n", + "\n", + " input_lengths2 = Lambda(input_lengths_lambda_func)(input_lengths)\n", + " if model_builder.output_length:\n", + " output_lengths = Lambda(model_builder.output_length)(input_lengths2) - 1\n", + " else:\n", + " output_lengths = input_lengths2\n", + " \n", + " # CTC loss is implemented in a lambda layer\n", + " loss_out = Lambda(ctc_lambda_func, output_shape=(1,), name='ctc')([model_builder.output, the_labels, output_lengths, label_lengths])\n", + " model = Model( inputs=[model_builder.input, the_labels, input_lengths, label_lengths], outputs=loss_out)\n", + " return model\n" + ] + }, + { + "cell_type": "code", + "execution_count": 29, + "id": "c8dfb93e", + "metadata": {}, + "outputs": [], + "source": [ + "from tensorflow.keras.models import Model, Sequential\n", + "from tensorflow.keras.layers import * \n", + "from tensorflow.keras.preprocessing.sequence import pad_sequences\n", + "from tensorflow.keras.optimizers import SGD, Adam, RMSprop\n", + "from tensorflow.keras import backend as K" + ] + }, + { + "cell_type": "code", + "execution_count": 30, + "id": "83d4fb3d", + "metadata": {}, + "outputs": [], + "source": [ + "def train(model_builder, \n", + " data_len,\n", + " data_gen,\n", + " batch_size = 25,\n", + " epochs=20, \n", + " verbose=1,\n", + " optimizer=SGD(learning_rate=0.002, decay=1e-6, momentum=0.9, nesterov=True, clipnorm=5),\n", + " ): \n", + " \n", + " model = add_ctc_loss(model_builder)\n", + "\n", + " model.compile(loss={'ctc': lambda y_true, y_pred: y_pred}, optimizer=optimizer)\n", + " print(model.summary())\n", + "\n", + "\n", + " hist = model.fit_generator(generator=data_gen,\n", + " epochs=epochs,\n", + " verbose=verbose, \n", + " use_multiprocessing=False)" + ] + }, + { + "cell_type": "markdown", + "id": "760baa7d", + "metadata": {}, + "source": [ + "### Training" + ] + }, + { + "cell_type": "code", + "execution_count": 53, + "id": "a155eb50", + "metadata": {}, + "outputs": [], + "source": [ + "audios = []\n", + "for label in audio_obj:\n", + " audios.append(audio_obj[label][0])\n", + " \n", + "translations = []\n", + "for label in audio_obj:\n", + " translations.append(translation_obj[label])" + ] + }, + { + "cell_type": "code", + "execution_count": 68, + "id": "8f6fcf08", + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "sample snt: የተለያዩ የ ትግራይ አውራጃ ተወላጆች ገንዘባቸው ን አዋጥ ተው የ ልማት ተቋማትን እንዲ መሰርቱ ትልማ አይ ፈቅድ ም\n", + "encoded snt: [8, 10, 13, 7, 111, 1, 8, 1, 3, 40, 23, 21, 1, 6, 4, 23, 98, 1, 10, 32, 28, 124, 16, 1, 17, 2, 75, 27, 31, 4, 1, 2, 1, 6, 41, 42, 1, 10, 4, 1, 8, 1, 11, 29, 3, 1, 10, 87, 29, 3, 2, 1, 19, 2, 50, 1, 12, 25, 14, 51, 1, 3, 11, 29, 1, 6, 21, 1, 76, 57, 30, 1, 18]\n", + "decoed snt: የተለያዩ የ ትግራይ አውራጃ ተወላጆች ገንዘባቸው ን አዋጥ ተው የ ልማት ተቋማትን እንዲ መሰርቱ ትልማ አይ ፈቅድ ም\n" + ] + } + ], + "source": [ + "tokenizer = Tokenizer(translations)\n", + "int_to_char, char_to_int = tokenizer.build_dict()\n", + "sample = translations[0]\n", + "encoded = tokenizer.encode(sample, char_to_int)\n", + "decoded = tokenizer.decode_text(sample, encoded)\n", + "\n", + "print(f\"sample snt: {sample}\")\n", + "print(f\"encoded snt: {encoded}\")\n", + "print(f\"decoed snt: {decoded}\")" + ] + }, + { + "cell_type": "code", + "execution_count": 69, + "id": "a2b66a26", + "metadata": {}, + "outputs": [], + "source": [ + "\n", + "sample_rate = 22000\n", + "fft_size = 1024\n", + "frame_step = 512\n", + "n_mels = 128\n", + "\n", + "batch_size = 100\n", + "epochs = 20\n", + "data_len = len(translations)\n", + "output_dim = len(char_to_int) + 2\n" + ] + }, + { + "cell_type": "code", + "execution_count": 70, + "id": "0e6b2ed2", + "metadata": {}, + "outputs": [], + "source": [ + "dg = DataGenerator(translations, audios, batch_size)\n" + ] + }, + { + "cell_type": "code", + "execution_count": 71, + "id": "dc32da3f", + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Model: \"preprocessin_model\"\n", + "_________________________________________________________________\n", + "Layer (type) Output Shape Param # \n", + "=================================================================\n", + "input (InputLayer) [(None, None)] 0 \n", + "_________________________________________________________________\n", + "log_mel_spectrogram_4 (LogMe (None, None, 128, 1) 0 \n", + "_________________________________________________________________\n", + "batch_normalization_4 (Batch (None, None, 128, 1) 4 \n", + "=================================================================\n", + "Total params: 4\n", + "Trainable params: 2\n", + "Non-trainable params: 2\n", + "_________________________________________________________________\n" + ] + } + ], + "source": [ + "preprocess_model = preprocessin_model(sample_rate, fft_size, frame_step, n_mels)\n", + "preprocess_model.summary()\n" + ] + }, + { + "cell_type": "code", + "execution_count": 72, + "id": "43fa4991", + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Model: \"simple_rnn_model\"\n", + "_________________________________________________________________\n", + "Layer (type) Output Shape Param # \n", + "=================================================================\n", + "the_input (InputLayer) [(None, None, 128)] 0 \n", + "_________________________________________________________________\n", + "rnn (GRU) (None, None, 175) 160125 \n", + "_________________________________________________________________\n", + "softmax (Activation) (None, None, 175) 0 \n", + "=================================================================\n", + "Total params: 160,125\n", + "Trainable params: 160,125\n", + "Non-trainable params: 0\n", + "_________________________________________________________________\n" + ] + } + ], + "source": [ + "speech_model = simple_rnn_model(n_mels, output_dim)\n", + "speech_model.summary()\n", + "# speech_model = BidirectionalRNN(n_mels, output_dim=output_dim)\n", + "# speech_model.summary()" + ] + }, + { + "cell_type": "code", + "execution_count": 75, + "id": "7e0d5d52", + "metadata": {}, + "outputs": [], + "source": [ + "def build_model(output_dim, custom_model, preprocess_model, mfcc=False, calc=None):\n", + "\n", + " input_audios = Input(name='the_input', shape=(None,))\n", + " pre = preprocess_model(input_audios)\n", + " pre = tf.squeeze(pre, [3])\n", + "\n", + " y_pred = custom_model(pre)\n", + " model = Model(inputs=input_audios, outputs=y_pred, name=\"model_builder\")\n", + " model.output_length = calc\n", + "\n", + " return model" + ] + }, + { + "cell_type": "code", + "execution_count": 76, + "id": "bbaf2460", + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Model: \"model_builder\"\n", + "_________________________________________________________________\n", + "Layer (type) Output Shape Param # \n", + "=================================================================\n", + "the_input (InputLayer) [(None, None)] 0 \n", + "_________________________________________________________________\n", + "preprocessin_model (Function (None, None, 128, 1) 4 \n", + "_________________________________________________________________\n", + "tf.compat.v1.squeeze_5 (TFOp (None, None, 128) 0 \n", + "_________________________________________________________________\n", + "simple_rnn_model (Functional (None, None, 175) 160125 \n", + "=================================================================\n", + "Total params: 160,129\n", + "Trainable params: 160,127\n", + "Non-trainable params: 2\n", + "_________________________________________________________________\n" + ] + } + ], + "source": [ + "model = build_model(output_dim, speech_model, preprocess_model)\n", + "model.summary()\n" + ] + }, + { + "cell_type": "code", + "execution_count": 77, + "id": "d11f997b", + "metadata": {}, + "outputs": [], + "source": [ + "import mlflow" + ] + }, + { + "cell_type": "code", + "execution_count": 79, + "id": "9fd2234f", + "metadata": {}, + "outputs": [ + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2021/08/08 13:16:37 INFO mlflow.utils.autologging_utils: Created MLflow autologging run with ID 'd9db32294f5c4678815d6b6efc825325', which will track hyperparameters, performance metrics, model artifacts, and lineage information for the current tensorflow workflow\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Model: \"model_6\"\n", + "__________________________________________________________________________________________________\n", + "Layer (type) Output Shape Param # Connected to \n", + "==================================================================================================\n", + "the_input (InputLayer) [(None, None)] 0 \n", + "__________________________________________________________________________________________________\n", + "preprocessin_model (Functional) (None, None, 128, 1) 4 the_input[0][0] \n", + "__________________________________________________________________________________________________\n", + "tf.compat.v1.squeeze_5 (TFOpLam (None, None, 128) 0 preprocessin_model[1][0] \n", + "__________________________________________________________________________________________________\n", + "input_length (InputLayer) [(None, 1)] 0 \n", + "__________________________________________________________________________________________________\n", + "simple_rnn_model (Functional) (None, None, 175) 160125 tf.compat.v1.squeeze_5[0][0] \n", + "__________________________________________________________________________________________________\n", + "the_labels (InputLayer) [(None, None)] 0 \n", + "__________________________________________________________________________________________________\n", + "lambda_6 (Lambda) (None, 1) 0 input_length[0][0] \n", + "__________________________________________________________________________________________________\n", + "label_length (InputLayer) [(None, 1)] 0 \n", + "__________________________________________________________________________________________________\n", + "ctc (Lambda) (None, 1) 0 simple_rnn_model[1][0] \n", + " the_labels[0][0] \n", + " lambda_6[0][0] \n", + " label_length[0][0] \n", + "==================================================================================================\n", + "Total params: 160,129\n", + "Trainable params: 160,127\n", + "Non-trainable params: 2\n", + "__________________________________________________________________________________________________\n", + "None\n", + "Epoch 1/20\n", + "1/1 [==============================] - 10s 10s/step - loss: 720.1365\n", + "Epoch 2/20\n", + "1/1 [==============================] - 8s 8s/step - loss: 711.0939\n", + "Epoch 3/20\n", + "1/1 [==============================] - 6s 6s/step - loss: 703.3038\n", + "Epoch 4/20\n", + "1/1 [==============================] - 5s 5s/step - loss: 696.7689\n", + "Epoch 5/20\n", + "1/1 [==============================] - 5s 5s/step - loss: 691.0403\n", + "Epoch 6/20\n", + "1/1 [==============================] - 5s 5s/step - loss: 685.7213\n", + "Epoch 7/20\n", + "1/1 [==============================] - 5s 5s/step - loss: 680.5095\n", + "Epoch 8/20\n", + "1/1 [==============================] - 5s 5s/step - loss: 676.0887\n", + "Epoch 9/20\n", + "1/1 [==============================] - 5s 5s/step - loss: 673.8625\n", + "Epoch 10/20\n", + "1/1 [==============================] - 6s 6s/step - loss: 672.7012\n", + "Epoch 11/20\n", + "1/1 [==============================] - 5s 5s/step - loss: 671.8706\n", + "Epoch 12/20\n", + "1/1 [==============================] - 5s 5s/step - loss: 671.2330\n", + "Epoch 13/20\n", + "1/1 [==============================] - 5s 5s/step - loss: 670.7097\n", + "Epoch 14/20\n", + "1/1 [==============================] - 5s 5s/step - loss: 670.1967\n", + "Epoch 15/20\n", + "1/1 [==============================] - 5s 5s/step - loss: 669.3744\n", + "Epoch 16/20\n", + "1/1 [==============================] - 5s 5s/step - loss: 667.4127\n", + "Epoch 17/20\n", + "1/1 [==============================] - 5s 5s/step - loss: 665.1722\n", + "Epoch 18/20\n", + "1/1 [==============================] - 5s 5s/step - loss: 664.1326\n", + "Epoch 19/20\n", + "1/1 [==============================] - 5s 5s/step - loss: 662.3972\n", + "Epoch 20/20\n", + "1/1 [==============================] - 5s 5s/step - loss: 659.3508\n" + ] + } + ], + "source": [ + "mlflow.set_experiment('Speech Model-RNN-baseline')\n", + "mlflow.tensorflow.autolog()\n", + "train(model, 100, dg, epochs=20, batch_size=100)\n" + ] + }, + { + "cell_type": "code", + "execution_count": 1, + "id": "721048e0", + "metadata": {}, + "outputs": [], + "source": [] + }, + { + "cell_type": "code", + "execution_count": 3, + "id": "726654f7", + "metadata": {}, + "outputs": [], + "source": [] + }, { "cell_type": "code", "execution_count": null, + "id": "8d33bb32", "metadata": {}, "outputs": [], "source": [] @@ -2452,6 +1877,9 @@ "name": "AS2T.ipynb", "provenance": [] }, + "interpreter": { + "hash": "51d477eca99ce531616b0189382ec1bb5b39235ab0a3993ccfacd0c8fd3459be" + }, "kernelspec": { "display_name": "Python 3", "language": "python", @@ -2467,7 +1895,7 @@ "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", - "version": "3.7.6" + "version": "3.9.4" } }, "nbformat": 4, diff --git a/notebooks/mlruns/0/00861c5cb9864b799eee65ee9a9fe6b7/meta.yaml b/notebooks/mlruns/0/00861c5cb9864b799eee65ee9a9fe6b7/meta.yaml new file mode 100644 index 0000000..bfaf618 --- /dev/null +++ b/notebooks/mlruns/0/00861c5cb9864b799eee65ee9a9fe6b7/meta.yaml @@ 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+name: '' +run_id: de081dc487cb4ed997a02037a887ed6d +run_uuid: de081dc487cb4ed997a02037a887ed6d +source_name: '' +source_type: 4 +source_version: '' +start_time: 1628533782630 +status: 3 +tags: [] +user_id: HP diff --git a/notebooks/mlruns/0/de081dc487cb4ed997a02037a887ed6d/metrics/ctc_loss b/notebooks/mlruns/0/de081dc487cb4ed997a02037a887ed6d/metrics/ctc_loss new file mode 100644 index 0000000..c5fa137 --- /dev/null +++ b/notebooks/mlruns/0/de081dc487cb4ed997a02037a887ed6d/metrics/ctc_loss @@ -0,0 +1 @@ +1628533782708 66.14131164550781 0 diff --git a/notebooks/mlruns/0/de081dc487cb4ed997a02037a887ed6d/tags/mlflow.source.name b/notebooks/mlruns/0/de081dc487cb4ed997a02037a887ed6d/tags/mlflow.source.name new file mode 100644 index 0000000..7fd1aa2 --- /dev/null +++ b/notebooks/mlruns/0/de081dc487cb4ed997a02037a887ed6d/tags/mlflow.source.name @@ -0,0 +1 @@ +C:\Users\HP\Anaconda3\lib\site-packages\ipykernel_launcher.py \ No newline at end of file diff --git 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file:///C:/Users/HP/Desktop/10academy/Week-4/AmharicSTT/notebooks/mlruns/0/e404b7d8846545ec8760c3abff46128e/artifacts +end_time: 1628386258952 +entry_point_name: '' +experiment_id: '0' +lifecycle_stage: active +name: '' +run_id: e404b7d8846545ec8760c3abff46128e +run_uuid: e404b7d8846545ec8760c3abff46128e +source_name: '' +source_type: 4 +source_version: '' +start_time: 1628386258779 +status: 3 +tags: [] +user_id: HP diff --git a/notebooks/mlruns/0/e404b7d8846545ec8760c3abff46128e/metrics/ctc_loss b/notebooks/mlruns/0/e404b7d8846545ec8760c3abff46128e/metrics/ctc_loss new file mode 100644 index 0000000..8bbbfbc --- /dev/null +++ b/notebooks/mlruns/0/e404b7d8846545ec8760c3abff46128e/metrics/ctc_loss @@ -0,0 +1 @@ +1628386258951 49.20677185058594 0 diff --git a/notebooks/mlruns/0/e404b7d8846545ec8760c3abff46128e/tags/mlflow.source.name b/notebooks/mlruns/0/e404b7d8846545ec8760c3abff46128e/tags/mlflow.source.name new file mode 100644 index 0000000..7fd1aa2 --- /dev/null +++ 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b/notebooks/mlruns/0/f7536edac0dc4942ab2c8e9407c3bda4/tags/mlflow.user @@ -0,0 +1 @@ +HP \ No newline at end of file diff --git a/notebooks/mlruns/0/meta.yaml b/notebooks/mlruns/0/meta.yaml new file mode 100644 index 0000000..c26ccd4 --- /dev/null +++ b/notebooks/mlruns/0/meta.yaml @@ -0,0 +1,4 @@ +artifact_location: file:///C:/Users/HP/Desktop/10academy/Week-4/AmharicSTT/notebooks/mlruns/0 +experiment_id: '0' +lifecycle_stage: active +name: Default diff --git a/requirements.txt b/requirements.txt index 755af2b..1ec071b 100644 --- a/requirements.txt +++ b/requirements.txt @@ -8,4 +8,5 @@ streamlit librosa scipy python_speech_features - +tensorflow +mlflow \ No newline at end of file diff --git a/scripts/.gitignore b/scripts/.gitignore new file mode 100644 index 0000000..c18dd8d --- /dev/null +++ b/scripts/.gitignore @@ -0,0 +1 @@ +__pycache__/ diff --git a/scripts/FeatureExtraction.py b/scripts/FeatureExtraction.py index a93426c..8f44487 100644 --- a/scripts/FeatureExtraction.py +++ b/scripts/FeatureExtraction.py @@ -1,5 +1,7 @@ import librosa import librosa.display +import matplotlib.pyplot as plt + class FeatureExtraction: def extract_features(self, audios : dict, sample_rate : int) -> dict: """ @@ -22,10 +24,10 @@ def extract_features(self, audios : dict, sample_rate : int) -> dict: mfcc_features = {} for audio in audios: - mfcc_features[audio] = librosa.feature.mfcc(audios[audio][0], sr=sample_rate) + mfcc_features[audio] = librosa.feature.mfcc(audios[audio], sr=sample_rate) return mfcc_features - def save_mfcc_spectrograms(self, mfccs: dict, path: str) -> int: + def save_mfcc_spectrograms(self, mfccs: dict, sample_rate: int, path: str) -> int: """ The Mel frequency cepstral coefficients (MFCCs) of a signal are a small set of features (usually about 10–20) which concisely describe the overall shape of a @@ -39,7 +41,8 @@ def save_mfcc_spectrograms(self, mfccs: dict, path: str) -> int: Inputs: mfccs - a python dictionary mapping the wav file names to the mfcc - coefficients of the sampled audio files + coefficients of the sampled audio files + sample_rate - the sampling rate for the audio path - the file path to the target directory Returns: @@ -54,10 +57,50 @@ def save_mfcc_spectrograms(self, mfccs: dict, path: str) -> int: ax = plt.Axes(fig, [0., 0., 1., 1.]) ax.set_axis_off() fig.add_axes(ax) - librosa.display.specshow(mfccs[audio], sr=44100, x_axis='time') + librosa.display.specshow(mfccs[audio], sr=sample_rate, x_axis='time') try: - plt.savefig(path+f'{audio}.png', dpi = 100) + plt.savefig(path+f'{audio}.png') except FileNotFoundError: raise FileNotFoundError(f'The directory {path} does not exist') fig.clear() return 0 + + def save_mel_spectrograms(self, audios: dict, sample_rate: int, path: str) -> int: + """ + The Mel frequency cepstral coefficients (MFCCs) of a signal are a small set of + features (usually about 10–20) which concisely describe the overall shape of a + spectral envelope. It models the characteristics of the human voice. + + A Spectrogram captures the nature of the audio as an image by decomposing + it into the set of frequencies that are included in it. + + We plot the MFCC spectrogram for each audio file, and save the plots as .png + image files to the given target directory. + + Inputs: + mfccs - a python dictionary mapping the wav file names to the mfcc + coefficients of the sampled audio files + sample_rate - the sampling rate for the audio + path - the file path to the target directory + + Returns: + 0 if the spectrograms were saved successfully, and + raises a FileNotFoundError if the given path doesn't exist + """ + if type(audios) != dict or type(path) != str: + raise TypeError("""argument mfccs must be of type dict and argument path + must be of type string (str)""") + for audio in audios: + X = librosa.stft(audios[audio], n_fft = 512) + Xdb = librosa.amplitude_to_db(abs(X)) + fig, ax = plt.subplots() + ax = plt.Axes(fig, [0., 0., 1., 1.]) + 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b/scripts/bidirectionalRNN.py @@ -0,0 +1,38 @@ +import tensorflow as tf +from tensorflow.keras.models import Model, Sequential +from tensorflow.keras.layers import * +from tensorflow.keras.preprocessing.sequence import pad_sequences +from tensorflow.keras.optimizers import SGD, Adam, RMSprop +from tensorflow.keras import backend as K + + +def BidirectionalRNN(input_dim, batch_size, sample_rate=22000, + rnn_layers=2, units=400, drop_out=0.5, act='tanh', output_dim=224): + + input_data = Input(name='the_input', shape=( + None, input_dim), batch_size=batch_size) + + x = Bidirectional(LSTM(units, activation=act, + return_sequences=True, implementation=2))(input_data) + + x = BatchNormalization()(x) + x = Dropout(drop_out)(x) + + for i in range(rnn_layers - 2): + x = Bidirectional( + LSTM(units, activation=act, return_sequences=True))(x) + x = BatchNormalization()(x) + x = Dropout(drop_out)(x) + + x = Bidirectional(LSTM(units, activation=act, + return_sequences=True, implementation=2))(x) + x = BatchNormalization()(x) + x = Dropout(drop_out)(x) + + time_dense = TimeDistributed(Dense(output_dim))(x) + + y_pred = Activation('softmax', name='softmax')(time_dense) + + model = Model(inputs=input_data, outputs=y_pred, name="BidirectionalRNN") + + return model diff --git a/scripts/ctc_loss.py b/scripts/ctc_loss.py new file mode 100755 index 0000000..b0fafec --- /dev/null +++ b/scripts/ctc_loss.py @@ -0,0 +1,41 @@ +import tensorflow as tf +from tensorflow.keras.models import Model +from tensorflow.keras.layers import * +from tensorflow.keras import backend as K + + +class CTC_loss: + + def __init__(self, hop_size): + self.hop_size = hop_size + + def ctc_lambda_func(self, args): + y_pred, labels, input_length, label_length = args + return K.ctc_batch_cost(labels, y_pred, input_length, label_length) + + def input_lengths_lambda_func(self, args): + hop_size = self.hop_size + input_length = args + return tf.cast(tf.math.ceil(input_length/hop_size)-1, dtype="float32") + + def add_ctc_loss(self, model_builder): + the_labels = Input(name='the_labels', + shape=(None,), dtype='float32') + input_lengths = Input(name='input_length', + shape=(1,), dtype='float32') + label_lengths = Input(name='label_length', + shape=(1,), dtype='float32') + + input_lengths2 = Lambda(self.input_lengths_lambda_func)(input_lengths) + + if model_builder.output_length: + output_lengths = Lambda( + model_builder.output_length)(input_lengths2) + else: + output_lengths = input_lengths2 + + loss_out = Lambda(self.ctc_lambda_func, output_shape=(1,), name='ctc')( + [model_builder.output, the_labels, output_lengths, label_lengths]) + model = Model(inputs=[model_builder.input, the_labels, + input_lengths, label_lengths], outputs=loss_out) + return model diff --git a/scripts/data_augmentation.py b/scripts/data_augmentation.py old mode 100644 new mode 100755 diff --git a/scripts/data_generator.py b/scripts/data_generator.py new file mode 100755 index 0000000..3a63ce2 --- /dev/null +++ b/scripts/data_generator.py @@ -0,0 +1,102 @@ +from tokenizer import Tokenizer +import numpy as np +import tensorflow as tf + + +class DataGenerator(tf.keras.utils.Sequence): + def __init__(self, translations, audios, batch_size=32, shuffle=True): + self.audios = audios + self.labels = translations + self.batch_size = batch_size + self.len = int(np.floor(len(self.labels) / self.batch_size)) + self.shuffle = shuffle + self.on_epoch_end() + + self.tokenizer = Tokenizer(translations) + self.int_to_char, self.char_to_int = self.tokenizer.build_dict() + + self.cur_index = 0 + + def __len__(self): + return self.len + + def encode_text(self, translations): + encoded_trans = [] + + for t in translations: + encoded = self.tokenizer.encode(t, self.char_to_int) + encoded_trans.append(encoded) + + return encoded_trans + + def get_max_len(self, items): + maximum = 0 + for i in items: + if len(i) > maximum: + maximum = len(i) + + return maximum + + def __data_generation(self, batch_translations, batch_audios): + + self.cur_index = 0 + encoded_trans = self.encode_text(batch_translations) + + maximum_trans_len = self.get_max_len(encoded_trans) + maximum_audio_len = self.get_max_len(batch_audios) + + encoded_trans_np = np.zeros( + (len(encoded_trans), maximum_trans_len), dtype="int64") + padded_audios_np = np.zeros( + (len(batch_audios), maximum_audio_len), dtype="float32") + + label_length = np.zeros(padded_audios_np.shape[0], dtype="int64") + input_length = np.zeros(encoded_trans_np.shape[0], dtype="int64") + + ind = 0 + for trans, audio in zip(encoded_trans, batch_audios): + encoded_trans_np[ind, 0:len(trans)] = trans + label_length[ind] = len(trans) + + padded_audio = np.pad( + audio, (0, maximum_audio_len - len(audio)), mode='constant', constant_values=0) + + padded_audios_np[ind, ] = padded_audio + input_length[ind] = len(audio) + + ind += 1 + + outputs = {'ctc': np.zeros([self.batch_size])} + inputs = {'the_input': tf.convert_to_tensor(padded_audios_np), + 'the_labels': tf.convert_to_tensor(encoded_trans_np), + 'input_length': tf.convert_to_tensor(input_length), + 'label_length': tf.convert_to_tensor(label_length) + } + + return (inputs, outputs) + + def on_epoch_end(self): + + self.indexes = np.arange(self.len*self.batch_size) + + if self.shuffle == True: + + self.indexes = self.indexes.reshape( + int(self.len), int(self.batch_size)) + np.random.shuffle(self.indexes) + + for i in range(self.len): + np.random.shuffle(self.indexes[i]) + + self.indexes = self.indexes.reshape(int(self.len*self.batch_size)) + + def __getitem__(self, index): + indexes = self.indexes[int(index*self.batch_size):int((index+1)*self.batch_size)] + + + batch_labels = [self.labels[int(k)] for k in indexes] + batch_audios = [self.audios[int(k)] for k in indexes] + + + + return self.__data_generation(batch_labels, batch_audios) diff --git a/scripts/data_loader.py b/scripts/data_loader.py old mode 100644 new mode 100755 diff --git a/scripts/dataset_loader.py b/scripts/dataset_loader.py new file mode 100644 index 0000000..18b3df5 --- /dev/null +++ b/scripts/dataset_loader.py @@ -0,0 +1,111 @@ +import librosa #for audio processing +import numpy as np +from matplotlib import image +import os + +def load_audio_files(path : str, sampling_rate : int, to_mono : bool) -> (dict, int): + + """ + Load the audio files and produce a dictionary mapping the audio filenames + to numpy arrays of the audio sampled at the given sample rate. + + Inputs: + path - a path to the directory that contains the audio files + sample_rate - the sampling rate for the audio files + to_mono - a boolean value denoting whether to convert signal to mono + + Returns: + audio_files - audios - a dictionary mapping the wav file names to the sampled audio array + max_length - the maximum length of a sampled audio array in our dataset + """ + + audio_files = {} + max_length = 0 + i = 0 + for file in os.listdir(path): + audio, rate= librosa.load(path+file, sr=sampling_rate, mono = to_mono) + audio_files[file.split('.')[0]] = audio + max_length = max(max_length,len(audio)) + i+=1 + if i%20 == 0: + print('loaded',i,'audio files') + if i == 100: + break + return audio_files, max_length + +def load_transcripts(filepath : str) -> dict: + """ + Load the transcript file and produce a dictionary mapping the audio filenames + to the transcripts for those audio files. + + Inputs: + filepath - a path to the transcript file + + Returns: + transcripts - a python dictionary mapping the wav file names to the transcripts + of those audio files. + """ + transcripts = {} + with open (filepath, encoding="utf-8")as f: + #print(f.readlines()[1]) + for line in f.readlines(): + + text, filename = line.split("") + text, filename = text.strip()[3:], filename.strip()[1:-1] + transcripts[filename] = text + return transcripts + + +def load_spectrograms_with_transcripts(mfcc_features : dict, encoded_transcripts : dict, path : str): + """ + Loads the spectrogram images as numpy arrays + + Inputs: + mfcc_features - a python dictionary mapping the wav file names to the mfcc + coefficients of the sampled audio files + encoded_transcripts - a python dictionary mapping the wav file names to the + encoded transcripts of those audio files. + path - the path to the directory that contains the spectrogram images + + Returns: + X_train - a numpy array containing the mfcc spectrograms of the sampled audio files + y_train - a numpy array containing the encoded transcripts of the sampled audio files + in the same order as they appear in X_train + """ + X_train = [] + y_train = [] + for audio in mfcc_features: + specgram = image.imread(path+f'{audio}.png') + X_train.append(specgram) + y_train.append(encoded_transcripts[audio]) + return np.array(X_train), np.array(y_train) + +def load_spectrograms_with_transcripts_in_batches(mfcc_features : dict, encoded_transcripts : dict, + batch_size : int, batch_no : int, path : str): + """ + Loads the spectrogram images as numpy arrays + + Inputs: + mfcc_features - a python dictionary mapping the wav file names to the mfcc + coefficients of the sampled audio files + encoded_transcripts - a python dictionary mapping the wav file names to the + encoded transcripts of those audio files. + batch_size - the size of the batch when loading + batch_no - the index of the batch + path - the path to the directory that contains the spectrogram images + + Returns: + X_train - a numpy array containing the mfcc spectrograms of the sampled audio files + y_train - a numpy array containing the encoded transcripts of the sampled audio files + in the same order as they appear in X_train + """ + X_train = [] + y_train = [] + audio_names = list(mfcc_features.keys()) + i = batch_size*batch_no + j = batch_size*(batch_no + 1) + for audio in audio_names[i:j]: + specgram = image.imread(path+f'{audio}.png') + X_train.append(specgram) + y_train.append(encoded_transcripts[audio]) + return np.array(X_train), np.array(y_train) diff --git a/scripts/helper.py b/scripts/helper.py old mode 100644 new mode 100755 index 6e0d740..223430f --- a/scripts/helper.py +++ b/scripts/helper.py @@ -1,5 +1,5 @@ import pickle - +import pandas as pd def read_obj(path): with open(path, "rb") as f: diff --git a/scripts/logspectrorgam.py b/scripts/logspectrorgam.py new file mode 100755 index 0000000..466748e --- /dev/null +++ b/scripts/logspectrorgam.py @@ -0,0 +1,82 @@ +import tensorflow as tf + + +class LogMelSpectrogram(tf.keras.layers.Layer): + """Compute log-magnitude mel-scaled spectrograms.""" + + def __init__(self, sample_rate, fft_size, hop_size, n_mels, + f_min=0.0, f_max=None, **kwargs): + super(LogMelSpectrogram, self).__init__(**kwargs) + self.sample_rate = sample_rate + self.fft_size = fft_size + self.hop_size = hop_size + self.n_mels = n_mels + self.f_min = f_min + self.f_max = f_max if f_max else sample_rate / 2 + self.mel_filterbank = tf.signal.linear_to_mel_weight_matrix( + num_mel_bins=self.n_mels, + num_spectrogram_bins=fft_size // 2 + 1, + sample_rate=self.sample_rate, + lower_edge_hertz=self.f_min, + upper_edge_hertz=self.f_max) + + def build(self, input_shape): + self.non_trainable_weights.append(self.mel_filterbank) + super(LogMelSpectrogram, self).build(input_shape) + + def call(self, waveforms): + """Forward pass. + Parameters + ---------- + waveforms : tf.Tensor, shape = (None, n_samples) + A Batch of mono waveforms. + Returns + ------- + log_mel_spectrograms : (tf.Tensor), shape = (None, time, freq, ch) + The corresponding batch of log-mel-spectrograms + """ + def _tf_log10(x): + numerator = tf.math.log(x) + denominator = tf.math.log(tf.constant(10, dtype=numerator.dtype)) + return numerator / denominator + + def power_to_db(magnitude, amin=1e-16, top_db=80.0): + """ + https://librosa.github.io/librosa/generated/librosa.core.power_to_db.html + """ + ref_value = tf.reduce_max(magnitude) + log_spec = 10.0 * _tf_log10(tf.maximum(amin, magnitude)) + log_spec -= 10.0 * _tf_log10(tf.maximum(amin, ref_value)) + log_spec = tf.maximum(log_spec, tf.reduce_max(log_spec) - top_db) + + return log_spec + + spectrograms = tf.signal.stft(waveforms, + frame_length=self.fft_size, + frame_step=self.hop_size, + pad_end=False) + + magnitude_spectrograms = tf.abs(spectrograms) + + mel_spectrograms = tf.matmul(tf.square(magnitude_spectrograms), + self.mel_filterbank) + + log_mel_spectrograms = power_to_db(mel_spectrograms) + + # add channel dimension + log_mel_spectrograms = tf.expand_dims(log_mel_spectrograms, 3) + + return log_mel_spectrograms + + def get_config(self): + config = { + 'fft_size': self.fft_size, + 'hop_size': self.hop_size, + 'n_mels': self.n_mels, + 'sample_rate': self.sample_rate, + 'f_min': self.f_min, + 'f_max': self.f_max, + } + config.update(super(LogMelSpectrogram, self).get_config()) + + return config diff --git a/scripts/mlruns/0/874ec96382b84a88a8fb8adc79b507a9/meta.yaml b/scripts/mlruns/0/874ec96382b84a88a8fb8adc79b507a9/meta.yaml new file 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+1628555848702 263.6120910644531 0 diff --git a/scripts/mlruns/0/96ee31afa0d5441cb01919fa0bce281a/tags/mlflow.source.name b/scripts/mlruns/0/96ee31afa0d5441cb01919fa0bce281a/tags/mlflow.source.name new file mode 100644 index 0000000..0ccac23 --- /dev/null +++ b/scripts/mlruns/0/96ee31afa0d5441cb01919fa0bce281a/tags/mlflow.source.name @@ -0,0 +1 @@ +.\train.py \ No newline at end of file diff --git a/scripts/mlruns/0/96ee31afa0d5441cb01919fa0bce281a/tags/mlflow.source.type b/scripts/mlruns/0/96ee31afa0d5441cb01919fa0bce281a/tags/mlflow.source.type new file mode 100644 index 0000000..0c2c1fe --- /dev/null +++ b/scripts/mlruns/0/96ee31afa0d5441cb01919fa0bce281a/tags/mlflow.source.type @@ -0,0 +1 @@ +LOCAL \ No newline at end of file diff --git a/scripts/mlruns/0/96ee31afa0d5441cb01919fa0bce281a/tags/mlflow.user b/scripts/mlruns/0/96ee31afa0d5441cb01919fa0bce281a/tags/mlflow.user new file mode 100644 index 0000000..ef6b35d --- /dev/null +++ b/scripts/mlruns/0/96ee31afa0d5441cb01919fa0bce281a/tags/mlflow.user @@ -0,0 +1 @@ +HP \ No newline at end of file diff --git a/scripts/mlruns/0/meta.yaml b/scripts/mlruns/0/meta.yaml new file mode 100644 index 0000000..411c4a3 --- /dev/null +++ b/scripts/mlruns/0/meta.yaml @@ -0,0 +1,4 @@ +artifact_location: file:///C:/Users/HP/Desktop/10academy/Week-4/AmharicSTT/scripts/mlruns/0 +experiment_id: '0' +lifecycle_stage: active +name: Default diff --git a/scripts/model2.py b/scripts/model2.py new file mode 100644 index 0000000..96e6a71 --- /dev/null +++ b/scripts/model2.py @@ -0,0 +1,129 @@ +from tensorflow.keras.layers import * +from tensorflow.keras.models import Model + +import tensorflow as tf +from tensorflow.keras.layers import * + +from logspectrorgam import LogMelSpectrogram + + +def simple_rnn_model(input_dim, output_dim=224): + + input_data = Input(name='the_input', shape=(None, input_dim)) + simp_rnn = GRU(output_dim, return_sequences=True, + implementation=2, name='rnn')(input_data) + y_pred = Activation('softmax', name='softmax')(simp_rnn) + model = Model(inputs=input_data, outputs=y_pred, name="simple_rnn_model") + model.output_length = lambda x: x + return model + + +def BidirectionalRNN2(input_dim, batch_size, sample_rate=8000, + rnn_layers=4, units=400, drop_out=0.5, act='tanh', output_dim=224): + + input_data = Input(name='the_input', shape=( + None, input_dim)) + + x = Bidirectional(LSTM(units, activation=act, + return_sequences=True, implementation=2))(input_data) + + x = BatchNormalization()(x) + x = Dropout(drop_out)(x) + + for i in range(rnn_layers - 2): + x = Bidirectional( + LSTM(units, activation=act, return_sequences=True))(x) + x = BatchNormalization()(x) + x = Dropout(drop_out)(x) + + x = Bidirectional(LSTM(units, activation=act, + return_sequences=True, implementation=2))(x) + x = BatchNormalization()(x) + x = Dropout(drop_out)(x) + + time_dense = TimeDistributed(Dense(output_dim))(x) + + y_pred = Activation('softmax', name='softmax')(time_dense) + + model = Model(inputs=input_data, outputs=y_pred, name="BidirectionalRNN") + + return model + + +def cnn_rnn_model(input_dim, filters, kernel_size, conv_stride, + conv_border_mode, units, output_dim=29): + """ Build a recurrent + convolutional network for speech + """ + # Main acoustic input + input_data = Input(name='the_input', shape=(None, input_dim)) + # Add convolutional layer + conv_1d = Conv1D(filters, kernel_size, + strides=conv_stride, + padding=conv_border_mode, + activation='relu', + name='conv1d')(input_data) + # Add batch normalization + bn_cnn = BatchNormalization(name='bn_conv_1d')(conv_1d) + # Add a recurrent layer + simp_rnn = SimpleRNN(units, activation='relu', + return_sequences=True, name='rnn')(bn_cnn) + # TODO: Add batch normalization + + bn_rnn = BatchNormalization()(simp_rnn) + # TODO: Add a TimeDistributed(Dense(output_dim)) layer + time_dense = TimeDistributed(Dense(output_dim))(bn_rnn) + # Add softmax activation layer + y_pred = Activation('softmax', name='softmax')(time_dense) + # Specify the model + model = Model(inputs=input_data, outputs=y_pred) + model.output_length = lambda x: cnn_output_length( + x, kernel_size, conv_border_mode, conv_stride) + # model.output_length = lambda x: x + + return model + + +def CNN_net(n_mels): + + input_data = Input(name='the_input', shape=( + None, n_mels, 1)) + + y = Conv2D(128, (7, 7), padding='same')(input_data) # was 32 + y = Activation('relu')(y) + y = BatchNormalization()(y) + y = MaxPooling2D((1, 2))(y) + + y = Conv2D(64, (5, 5), padding='same')(y) # was 32 + y = Activation('relu')(y) + y = BatchNormalization()(y) + y = MaxPooling2D((1, 2))(y) + + y = Conv2D(64, (3, 3), padding='same')(y) # was 32 + y = Activation('relu')(y) + y = BatchNormalization()(y) + y = MaxPooling2D((1, 2))(y) + + y = Reshape((-1, y.shape[-1] * y.shape[-2]))(y) + + model = Model(inputs=input_data, outputs=y, name="cnn") + return model, model.output.shape + + +def preprocessin_model(sample_rate, fft_size, frame_step, n_mels, mfcc=False): + + input_data = Input(name='input', shape=(None,), dtype="float32") + featLayer = LogMelSpectrogram( + fft_size=fft_size, + hop_size=frame_step, + n_mels=n_mels, + + sample_rate=sample_rate, + f_min=0.0, + + f_max=int(sample_rate / 2), + )(input_data) + + x = BatchNormalization(axis=2)(featLayer) + model = Model(inputs=input_data, outputs=x, name="preprocessin_model") + + return model diff --git a/scripts/model_helper.py b/scripts/model_helper.py new file mode 100644 index 0000000..e1006fd --- /dev/null +++ b/scripts/model_helper.py @@ -0,0 +1,89 @@ +from tensorflow.keras.layers import * +from jiwer import wer +from tensorflow.keras import backend as K +from tensorflow.keras.optimizers import SGD +from tensorflow.keras.callbacks import ModelCheckpoint +from tensorflow.keras.models import Model +import tensorflow as tf +from ctc_loss import CTC_loss + +frame_step = 256 +ctc = CTC_loss(frame_step) + + +def build_model(output_dim, custom_model, preprocess_model, mfcc=False, calc=None): + + input_audios = Input(name='the_input', shape=(None,)) + pre = preprocess_model(input_audios) + pre = tf.squeeze(pre, [3]) + + y_pred = custom_model(pre) + model = Model(inputs=input_audios, outputs=y_pred, name="model_builder") + model.output_length = calc + + return model + + +def build_model2(output_dim, cnn_model, custom_model, preprocess_model, mfcc=False, calc=None): + + input_audios = Input(name='the_input', shape=(None,)) + pre = preprocess_model(input_audios) + pre = tf.squeeze(pre, [3]) + + cnn_output = cnn_model(pre) + + y_pred = custom_model(cnn_output) + model = Model(inputs=input_audios, outputs=y_pred, name="model_builder") + model.output_length = calc + + return model + + +def train(model_builder, + data_gen, + batch_size=32, + epochs=20, + verbose=1, + save_path="../models/model.h5", + optimizer=SGD(learning_rate=0.01, decay=1e-6, + momentum=0.9, nesterov=True, clipnorm=5), + ): + + model = ctc.add_ctc_loss(model_builder) + + checkpointer = ModelCheckpoint(filepath=save_path, verbose=0) + model.compile(loss={'ctc': lambda y_true, + y_pred: y_pred}, optimizer=optimizer) + print(model.summary()) + + hist = model.fit_generator(generator=data_gen, + callbacks=[checkpointer], + + epochs=epochs, + verbose=verbose, + use_multiprocessing=False) + return model + + +def predict(model, audio, tokenizer, int_to_char, actual=None): + + pred_audios = tf.convert_to_tensor([audio]) + + y_pred = model.predict(pred_audios) + + input_shape = tf.keras.backend.shape(y_pred) + input_length = tf.ones( + shape=input_shape[0]) * tf.keras.backend.cast(input_shape[1], 'float32') + prediction = tf.keras.backend.ctc_decode( + y_pred, input_length, greedy=False)[0][0] + + pred = K.eval(prediction).flatten().tolist() + pred = [i for i in pred if i != -1] + + predicted_text = tokenizer.decode_text(pred, int_to_char) + + error = None + if actual != None: + error = wer(actual, predicted_text) + + return predicted_text, error diff --git a/scripts/models.py b/scripts/models.py new file mode 100644 index 0000000..8e2d5b9 --- /dev/null +++ b/scripts/models.py @@ -0,0 +1,182 @@ +import tensorflow as tf +import tensorflow.keras.layers as layers +from tensorflow.keras.layers import Input, Conv2D, Dense, LSTM, MaxPooling2D, Bidirectional + +class CTCLayer(layers.Layer): + def __init__(self, name=None): + super().__init__(name=name) + self.loss_fn = tf.keras.backend.ctc_batch_cost + + def call(self, y_true, y_pred): + # Compute the training-time loss value and add it + # to the layer using `self.add_loss()`. + batch_len = tf.cast(tf.shape(y_true)[0], dtype="int64") + input_length = tf.cast(tf.shape(y_pred)[1], dtype="int64") + label_length = tf.cast(tf.shape(y_true)[1], dtype="int64") + + input_length = input_length * tf.ones(shape=(batch_len, 1), dtype="int64") + label_length = label_length * tf.ones(shape=(batch_len, 1), dtype="int64") + + loss = self.loss_fn(y_true, y_pred, input_length, label_length) + self.add_loss(loss) + + # At test time, just return the computed predictions + return y_pred + +def model_1(encoder): + input_img = layers.Input( + shape=(288, 432, 4), name="image", dtype="float32" + ) + labels = layers.Input(name="label", shape=(None,), dtype="float32") + + # First conv block + x = layers.Conv2D( + 32, + (3, 3), + activation="relu", + kernel_initializer="he_normal", + padding="same", + name="Conv1", + )(input_img) + x = layers.MaxPooling2D((2, 2), name="pool1")(x) + + # We have used two max pool with pool size and strides 2. + # Hence, downsampled feature maps are 4x smaller. The number of + # filters in the last layer is 64. Reshape accordingly before + # passing the output to the RNN part of the model + if tf.__version__ >= '2.3': + new_shape = (x.type_spec.shape[-3], x.type_spec.shape[-2]*x.type_spec.shape[-1]) + else: + new_shape = (x.shape[-3], x.shape[-2]*x.shape[-1]) + x = layers.Reshape(target_shape=new_shape, name="reshape")(x) + x = layers.Dense(64, activation="relu", name="dense1")(x) + x = layers.Dropout(0.2)(x) + + # RNNs + x = layers.Bidirectional(layers.LSTM(128, return_sequences=True, dropout=0.25))(x) + x = layers.Bidirectional(layers.LSTM(64, return_sequences=True, dropout=0.25))(x) + + # Output layer + x = layers.Dense( + len(encoder.classes_) + 1, activation="softmax", name="dense2" + )(x) + + # Add CTC layer for calculating CTC loss at each step + output = CTCLayer(name="ctc_loss")(labels, x) + + # Define the model + model = tf.keras.models.Model( + inputs=[input_img, labels], outputs=output, name="ocr_model_v1" + ) + # Optimizer + opt = tf.keras.optimizers.Adam() + # Compile the model and return + model.compile(optimizer=opt) + + return model + +def model_2(encoder): + input_img = layers.Input( + shape=(480, 640, 4), name="image", dtype="float32" + ) + labels = layers.Input(name="label", shape=(None,), dtype="float32") + + # First conv block + x = layers.Conv2D( + 32, + (3, 3), + activation="relu", + kernel_initializer="he_normal", + padding="same", + name="Conv1", + )(input_img) + x = layers.MaxPooling2D((2, 2), name="pool1")(x) + + # We have used two max pool with pool size and strides 2. + # Hence, downsampled feature maps are 4x smaller. The number of + # filters in the last layer is 64. Reshape accordingly before + # passing the output to the RNN part of the model + if tf.__version__ >= '2.3': + new_shape = (x.type_spec.shape[-3], x.type_spec.shape[-2]*x.type_spec.shape[-1]) + else: + new_shape = (x.shape[-3], x.shape[-2]*x.shape[-1]) + x = layers.Reshape(target_shape=new_shape, name="reshape")(x) + x = layers.Dense(64, activation="relu", name="dense1")(x) + x = layers.Dropout(0.2)(x) + + # RNNs + x = layers.Bidirectional(layers.LSTM(128, return_sequences=True, dropout=0.25))(x) + x = layers.Bidirectional(layers.LSTM(64, return_sequences=True, dropout=0.25))(x) + + # Output layer + x = layers.Dense( + len(encoder.classes_) + 1, activation="softmax", name="dense2" + )(x) + + # Add CTC layer for calculating CTC loss at each step + output = CTCLayer(name="ctc_loss")(labels, x) + + # Define the model + model = tf.keras.models.Model( + inputs=[input_img, labels], outputs=output, name="ocr_model_v1" + ) + # Optimizer + opt = tf.keras.optimizers.Adam() + # Compile the model and return + model.compile(optimizer=opt) + + return model + +def model_3(encoder): + input_img = layers.Input( + shape=(480, 640, 4), name="image", dtype="float32" + ) + labels = layers.Input(name="label", shape=(None,), dtype="float32") + + # First conv block + x = layers.Conv2D( + 64, + (3, 3), + activation="relu", + kernel_initializer="he_normal", + padding="same", + name="Conv1", + )(input_img) + x = layers.MaxPooling2D((2, 2), name="pool1")(x) + x = layers.BatchNormalization()(x) + # We have used two max pool with pool size and strides 2. + # Hence, downsampled feature maps are 4x smaller. The number of + # filters in the last layer is 64. Reshape accordingly before + # passing the output to the RNN part of the model + if tf.__version__ >= '2.3': + new_shape = (x.type_spec.shape[-3], x.type_spec.shape[-2]*x.type_spec.shape[-1]) + else: + new_shape = (x.shape[-3], x.shape[-2]*x.shape[-1]) + x = layers.Reshape(target_shape=new_shape, name="reshape")(x) + x = layers.Dense(64, activation="relu", name="dense1")(x) + x = layers.Dropout(0.2)(x) + + # RNNs + x = layers.Bidirectional(layers.LSTM(128, return_sequences=True, dropout=0.25))(x) + x = layers.BatchNormalization()(x) + x = layers.Bidirectional(layers.LSTM(128, return_sequences=True, dropout=0.25))(x) + x = layers.BatchNormalization()(x) + + # Output layer + x = layers.TimeDistributed(layers.Dense( + len(encoder.classes_) + 1, activation="softmax", name="dense2" + ))(x) + + # Add CTC layer for calculating CTC loss at each step + output = CTCLayer(name="ctc_loss")(labels, x) + + # Define the model + model = tf.keras.models.Model( + inputs=[input_img, labels], outputs=output, name="ocr_model_v1" + ) + # Optimizer + opt = tf.keras.optimizers.Adam() + # Compile the model and return + model.compile(optimizer=opt) + + return model diff --git a/scripts/new_model.py b/scripts/new_model.py new file mode 100644 index 0000000..00a0b75 --- /dev/null +++ b/scripts/new_model.py @@ -0,0 +1,181 @@ +import tensorflow as tf +import tensorflow.keras.layers as layers + +NUM_FFT = 512 +NUM_FREQS = 257 +# some tentative constants +NUM_MEL = 60 +SAMPLE_RATE = 44100 +F_MIN = 0 +F_MAX = 12000 + +class LogMelgramLayer(tf.keras.layers.Layer): + def __init__(self, num_fft, hop_length, **kwargs): + super(LogMelgramLayer, self).__init__(**kwargs) + self.num_fft = num_fft + self.hop_length = hop_length + + assert num_fft // 2 + 1 == NUM_FREQS + lin_to_mel_matrix = tf.signal.linear_to_mel_weight_matrix( + num_mel_bins=NUM_MEL, + num_spectrogram_bins=NUM_FREQS, + sample_rate=SAMPLE_RATE, + lower_edge_hertz=F_MIN, + upper_edge_hertz=F_MAX, + ) + + self.lin_to_mel_matrix = lin_to_mel_matrix + + def build(self, input_shape): + self.non_trainable_weights.append(self.lin_to_mel_matrix) + super(LogMelgramLayer, self).build(input_shape) + + def call(self, input): + """ + Args: + input (tensor): Batch of mono waveform, shape: (None, N) + Returns: + log_melgrams (tensor): Batch of log mel-spectrograms, shape: (None, num_frame, mel_bins, channel=1) + """ + + def _tf_log10(x): + numerator = tf.math.log(x) + denominator = tf.math.log(tf.constant(10, dtype=numerator.dtype)) + return numerator / denominator + + # tf.signal.stft seems to be applied along the last axis + stfts = tf.signal.stft( + input, frame_length=self.num_fft, frame_step=self.hop_length + ) + mag_stfts = tf.abs(stfts) + + melgrams = tf.tensordot(tf.square(mag_stfts), self.lin_to_mel_matrix, axes=[2, 0]) + log_melgrams = _tf_log10(melgrams + 10**-5) + return tf.expand_dims(log_melgrams, 3) + + def get_config(self): + config = {'num_fft': self.num_fft, 'hop_length': self.hop_length} + base_config = super(LogMelgramLayer, self).get_config() + return dict(list(config.items()) + list(base_config.items())) + +class CTCLayer(layers.Layer): + def __init__(self, name=None, **kwargs): + super().__init__(name=name) + self.loss_fn = tf.keras.backend.ctc_batch_cost + + def call(self, y_true, y_pred): + # Compute the training-time loss value and add it + # to the layer using `self.add_loss()`. + batch_len = tf.cast(tf.shape(y_true)[0], dtype="int64") + input_length = tf.cast(tf.shape(y_pred)[1], dtype="int64") + label_length = tf.cast(tf.shape(y_true)[1], dtype="int64") + + input_length = input_length * tf.ones(shape=(batch_len, 1), dtype="int64") + label_length = label_length * tf.ones(shape=(batch_len, 1), dtype="int64") + + loss = self.loss_fn(y_true, y_pred, input_length, label_length) + self.add_loss(loss) + + # At test time, just return the computed predictions + return y_pred + +def my_model(encoder, max_length): + inputs = layers.Input( + shape=(max_length,), name="image", dtype="float32" + ) + labels = layers.Input(name="label", shape=(None,), dtype="float32") + + log_melgram_layer = LogMelgramLayer( + num_fft=512, + hop_length=128, + ) + + log_melgrams = log_melgram_layer(inputs) + + # First conv block + x = layers.Conv2D( + 128, + (3, 3), + activation="relu", + kernel_initializer="he_normal", + padding="same", + name="Conv1", + )(log_melgrams) + + x = layers.MaxPooling2D((2, 2), name="pool1")(x) + + x = layers.BatchNormalization()(x) + # Second conv block + x = layers.Conv2D( + 256, + (3, 3), + activation="relu", + kernel_initializer="he_normal", + padding="same", + name="Conv2", + )(x) + x = layers.MaxPooling2D((2, 2), name="pool2")(x) + + x = layers.BatchNormalization()(x) + + x = layers.Conv2D( + 256, + (3, 3), + activation="relu", + kernel_initializer="he_normal", + padding="same", + name="Conv3", + )(x) + + x = layers.MaxPooling2D((2, 2), name="pool3")(x) + + x = layers.Conv2D( + 256, + (3, 3), + activation="relu", + kernel_initializer="he_normal", + padding="same", + name="Conv4", + )(x) + + x = layers.BatchNormalization()(x) + + # We have used two max pool with pool size and strides 2. + # Hence, downsampled feature maps are 4x smaller. The number of + # filters in the last layer is 64. Reshape accordingly before + # passing the output to the RNN part of the model + if tf.__version__ >= '2.3': + new_shape = (x.type_spec.shape[-3], x.type_spec.shape[-2]*x.type_spec.shape[-1]) + else: + new_shape = (x.shape[-3], x.shape[-2]*x.shape[-1]) + x = layers.Reshape(target_shape=new_shape, name="reshape")(x) + + x = layers.Dense(256, activation="relu", name="dense1")(x) + x = layers.Dropout(0.2)(x) + + x = layers.Dense(128, activation="relu", name="dense2")(x) + x = layers.Dropout(0.2)(x) + + # RNNs + x = layers.LSTM(256, return_sequences=True, dropout=0.25)(x) + x = layers.BatchNormalization()(x) + x = layers.LSTM(256, return_sequences=True, dropout=0.25)(x) + x = layers.BatchNormalization()(x) + # Output layer + x = layers.Dense( + len(encoder.classes_) + 1, activation="softmax", name="dense_final" + )(x) + + # Add CTC layer for calculating CTC loss at each step + output = CTCLayer(name="ctc_loss")(labels, x) + + # Define the model + model = tf.keras.models.Model( + inputs=[inputs, labels], outputs=output, name="stt_model_v2" + ) + # Optimizer + opt = tf.keras.optimizers.Adam() + # Compile the model and return + model.compile(optimizer=opt) + + return model \ No newline at end of file diff --git a/scripts/pages/home.png b/scripts/pages/home.png new file mode 100644 index 0000000..948860c Binary files /dev/null and b/scripts/pages/home.png differ diff --git a/scripts/pages/home.py b/scripts/pages/home.py new file mode 100644 index 0000000..bebc9d1 --- /dev/null +++ b/scripts/pages/home.py @@ -0,0 +1,23 @@ +''' This is the home page''' + +# Libraries +import streamlit as st + +def write(): + with st.spinner("Loading Home ..."): + + st.markdown("

Amharic speech recognition

", unsafe_allow_html=True) + st.write( + """ + + + Speech recognition technology allows for hands-free control of smartphones, speakers, and even vehicles in a wide variety of languages. Companies have moved towards the goal of enabling machines to understand and respond to more and more of our verbalized commands. There are many matured speech recognition systems available, such as Google Assistant, Amazon Alexa, and Apple’s Siri. However, all of those voice assistants work for limited languages only. + """ ) + + st.write( + """ + The World Food Program wants to deploy an intelligent form that collects nutritional information of food bought and sold at markets in two different countries in Africa - Ethiopia and Kenya. The design of this intelligent form requires selected people to use this web app, and whenever they buy food, they use their voice to activate the app to register the list of items they just bought in their own language. The intelligent systems in the app are expected to live to transcribe the speech-to-text and organize the information in an easy-to-process way. + """ + ) + + st.image('scripts/pages/home.png', use_column_width=True) diff --git a/scripts/pages/model_summary.py b/scripts/pages/model_summary.py new file mode 100644 index 0000000..17a004d --- /dev/null +++ b/scripts/pages/model_summary.py @@ -0,0 +1,26 @@ + + +# Libraries +import streamlit as st +import tensorflow as tf +from scripts.new_model import LogMelgramLayer, CTCLayer + +def load_model(): + model = tf.keras.models.load_model('./models/new_model_v1_2000.h5', + custom_objects = { + 'LogMelgramLayer': LogMelgramLayer , + 'CTCLayer': CTCLayer} + ) + return model + +def write(): + with st.spinner("Loading..."): + + st.markdown("

Amharic speech recognition

", unsafe_allow_html=True) + + st.header("Model summary") + model = load_model() + stringlist = [] + model.summary(print_fn=lambda x: stringlist.append(x)) + short_model_summary = "\n".join(stringlist) + st.write(short_model_summary) diff --git a/scripts/pages/new_model.py b/scripts/pages/new_model.py new file mode 100644 index 0000000..00a0b75 --- /dev/null +++ b/scripts/pages/new_model.py @@ -0,0 +1,181 @@ +import tensorflow as tf +import tensorflow.keras.layers as layers + +NUM_FFT = 512 +NUM_FREQS = 257 +# some tentative constants +NUM_MEL = 60 +SAMPLE_RATE = 44100 +F_MIN = 0 +F_MAX = 12000 + +class LogMelgramLayer(tf.keras.layers.Layer): + def __init__(self, num_fft, hop_length, **kwargs): + super(LogMelgramLayer, self).__init__(**kwargs) + self.num_fft = num_fft + self.hop_length = hop_length + + assert num_fft // 2 + 1 == NUM_FREQS + lin_to_mel_matrix = tf.signal.linear_to_mel_weight_matrix( + num_mel_bins=NUM_MEL, + num_spectrogram_bins=NUM_FREQS, + sample_rate=SAMPLE_RATE, + lower_edge_hertz=F_MIN, + upper_edge_hertz=F_MAX, + ) + + self.lin_to_mel_matrix = lin_to_mel_matrix + + def build(self, input_shape): + self.non_trainable_weights.append(self.lin_to_mel_matrix) + super(LogMelgramLayer, self).build(input_shape) + + def call(self, input): + """ + Args: + input (tensor): Batch of mono waveform, shape: (None, N) + Returns: + log_melgrams (tensor): Batch of log mel-spectrograms, shape: (None, num_frame, mel_bins, channel=1) + """ + + def _tf_log10(x): + numerator = tf.math.log(x) + denominator = tf.math.log(tf.constant(10, dtype=numerator.dtype)) + return numerator / denominator + + # tf.signal.stft seems to be applied along the last axis + stfts = tf.signal.stft( + input, frame_length=self.num_fft, frame_step=self.hop_length + ) + mag_stfts = tf.abs(stfts) + + melgrams = tf.tensordot(tf.square(mag_stfts), self.lin_to_mel_matrix, axes=[2, 0]) + log_melgrams = _tf_log10(melgrams + 10**-5) + return tf.expand_dims(log_melgrams, 3) + + def get_config(self): + config = {'num_fft': self.num_fft, 'hop_length': self.hop_length} + base_config = super(LogMelgramLayer, self).get_config() + return dict(list(config.items()) + list(base_config.items())) + +class CTCLayer(layers.Layer): + def __init__(self, name=None, **kwargs): + super().__init__(name=name) + self.loss_fn = tf.keras.backend.ctc_batch_cost + + def call(self, y_true, y_pred): + # Compute the training-time loss value and add it + # to the layer using `self.add_loss()`. + batch_len = tf.cast(tf.shape(y_true)[0], dtype="int64") + input_length = tf.cast(tf.shape(y_pred)[1], dtype="int64") + label_length = tf.cast(tf.shape(y_true)[1], dtype="int64") + + input_length = input_length * tf.ones(shape=(batch_len, 1), dtype="int64") + label_length = label_length * tf.ones(shape=(batch_len, 1), dtype="int64") + + loss = self.loss_fn(y_true, y_pred, input_length, label_length) + self.add_loss(loss) + + # At test time, just return the computed predictions + return y_pred + +def my_model(encoder, max_length): + inputs = layers.Input( + shape=(max_length,), name="image", dtype="float32" + ) + labels = layers.Input(name="label", shape=(None,), dtype="float32") + + log_melgram_layer = LogMelgramLayer( + num_fft=512, + hop_length=128, + ) + + log_melgrams = log_melgram_layer(inputs) + + # First conv block + x = layers.Conv2D( + 128, + (3, 3), + activation="relu", + kernel_initializer="he_normal", + padding="same", + name="Conv1", + )(log_melgrams) + + x = layers.MaxPooling2D((2, 2), name="pool1")(x) + + x = layers.BatchNormalization()(x) + # Second conv block + x = layers.Conv2D( + 256, + (3, 3), + activation="relu", + kernel_initializer="he_normal", + padding="same", + name="Conv2", + )(x) + x = layers.MaxPooling2D((2, 2), name="pool2")(x) + + x = layers.BatchNormalization()(x) + + x = layers.Conv2D( + 256, + (3, 3), + activation="relu", + kernel_initializer="he_normal", + padding="same", + name="Conv3", + )(x) + + x = layers.MaxPooling2D((2, 2), name="pool3")(x) + + x = layers.Conv2D( + 256, + (3, 3), + activation="relu", + kernel_initializer="he_normal", + padding="same", + name="Conv4", + )(x) + + x = layers.BatchNormalization()(x) + + # We have used two max pool with pool size and strides 2. + # Hence, downsampled feature maps are 4x smaller. The number of + # filters in the last layer is 64. Reshape accordingly before + # passing the output to the RNN part of the model + if tf.__version__ >= '2.3': + new_shape = (x.type_spec.shape[-3], x.type_spec.shape[-2]*x.type_spec.shape[-1]) + else: + new_shape = (x.shape[-3], x.shape[-2]*x.shape[-1]) + x = layers.Reshape(target_shape=new_shape, name="reshape")(x) + + x = layers.Dense(256, activation="relu", name="dense1")(x) + x = layers.Dropout(0.2)(x) + + x = layers.Dense(128, activation="relu", name="dense2")(x) + x = layers.Dropout(0.2)(x) + + # RNNs + x = layers.LSTM(256, return_sequences=True, dropout=0.25)(x) + x = layers.BatchNormalization()(x) + x = layers.LSTM(256, return_sequences=True, dropout=0.25)(x) + x = layers.BatchNormalization()(x) + # Output layer + x = layers.Dense( + len(encoder.classes_) + 1, activation="softmax", name="dense_final" + )(x) + + # Add CTC layer for calculating CTC loss at each step + output = CTCLayer(name="ctc_loss")(labels, x) + + # Define the model + model = tf.keras.models.Model( + inputs=[inputs, labels], outputs=output, name="stt_model_v2" + ) + # Optimizer + opt = tf.keras.optimizers.Adam() + # Compile the model and return + model.compile(optimizer=opt) + + return model \ No newline at end of file diff --git a/scripts/pages/record_audio.py b/scripts/pages/record_audio.py new file mode 100644 index 0000000..84d99c9 --- /dev/null +++ b/scripts/pages/record_audio.py @@ -0,0 +1,58 @@ +import streamlit as st +import streamlit as st +import sounddevice as sd +import wavio +import librosa.display +from scripts.pages.test_model import * +def record(duration=10, fs=48000): + sd.default.samplerate = fs + sd.default.channels = 1 + myrecording = sd.rec(int(duration * fs)) + sd.wait(duration) + return myrecording + +def save_record(path_myrecording, myrecording, fs): + wavio.write(path_myrecording, myrecording, fs, sampwidth=2) + return None +def read_audio(file): + with open(file, "rb") as audio_file: + audio_bytes = audio_file.read() + return audio_bytes + +def write(): + st.markdown("

Amharic speech recognition

", unsafe_allow_html=True) + + st.header("Record your own voice") + + filename = st.text_input("Choose a filename: ") + + if st.button(f"Click to Record"): + if filename == "": + st.warning("Choose a filename.") + else: + record_state = st.text("Recording...") + duration = 5 # seconds + fs = 48000 + myrecording = record(duration, fs) + record_state.text(f"Saving sample as {filename}.mp3") + + path_myrecording = f"data/wav/{filename}.mp3" + + save_record(path_myrecording, myrecording, fs) + record_state.text(f"Done! Saved sample as {filename}.mp3") + st.audio(read_audio(path_myrecording)) + st.header("Transcribed text ") + with st.spinner("Processing....."): + write1() + + + st.balloons() + + + + + + + + + diff --git a/scripts/pages/recorded_audio.py b/scripts/pages/recorded_audio.py new file mode 100644 index 0000000..ab2d934 --- /dev/null +++ b/scripts/pages/recorded_audio.py @@ -0,0 +1,22 @@ +import streamlit as st +from scripts.pages.test_model import * +from pydub import AudioSegment + +def write(): + st.markdown("

Amharic speech recognition

", unsafe_allow_html=True) + + uploaded_file = st.file_uploader("Select file from your directory") + if uploaded_file is not None: + + audio_bytes = uploaded_file.read() + st.audio(audio_bytes, format='audio/wav') + file_var = AudioSegment.from_wav(uploaded_file) + file_var.export('./data/wav/new.wav', format='wav') + + st.header("Transcribed text ") + with st.spinner("Processing....."): + write1() + + + st.balloons() + diff --git a/scripts/pages/test_model.py b/scripts/pages/test_model.py new file mode 100644 index 0000000..4fb30e0 --- /dev/null +++ b/scripts/pages/test_model.py @@ -0,0 +1,63 @@ +from scripts.dataset_loader import * +from scripts.resize_and_augment import * +from scripts.transcript_encoder import * +import numpy as np +import os, shutil +import logging +import pickle +import tensorflow as tf +from scripts.new_model import LogMelgramLayer, CTCLayer +import streamlit as st + + + +def perform_predictions(path): + sample_rate = 44100 + audio_files, maximum_length = load_audio_files(path, sample_rate, True) + logging.info('loaded audio files') + audio_files = resize_audios_mono(audio_files, 440295) + enc = open('./models/encoder.pkl', 'rb') + char_encoder = pickle.load(enc) + print('model summary') + + def load_model(): + model = tf.keras.models.load_model('./models/new_model_v1_2000.h5', + custom_objects = { + 'LogMelgramLayer': LogMelgramLayer , + 'CTCLayer': CTCLayer} + ) + return model + model = load_model() + #print(model.summary()) + + def load_data(audio_files): + X_train = [] + y_train = [] + for audio in audio_files: + X_train.append(audio_files[audio]) + + return np.array(X_train), np.array(y_train) + + X_test,y_test = load_data(audio_files) + + if len(y_test) == 0: + y_test = np.array([[0]*70]) + predicted = model.predict([X_test,[y_test]]) + predicted_trans = decode_predicted(predicted, char_encoder) + + return predicted_trans +def write1(): + st.write(perform_predictions('./data/wav/')[-1]) + folder = './data/wav' + for filename in os.listdir(folder): + file_path = os.path.join(folder, filename) + try: + if os.path.isfile(file_path) or os.path.islink(file_path): + os.unlink(file_path) + elif os.path.isdir(file_path): + shutil.rmtree(file_path) + except Exception as e: + print('Failed to delete %s. Reason: %s' % (file_path, e)) + + + diff --git a/scripts/resize_and_augment.py b/scripts/resize_and_augment.py new file mode 100644 index 0000000..7524fde --- /dev/null +++ b/scripts/resize_and_augment.py @@ -0,0 +1,67 @@ +import numpy as np + +def resize_audios_mono(audios : dict, max_length : int) -> dict: + """ + Here we pad the sampled audio with zeros so tha all of the sampled audios + have equal length + + Inputs: + audios - a dictionary mapping the wav file names to the sampled audio array + max_length - the maximum length of a sampled audio array in our dataset + + Returns: + audios - a python dictionary mapping the wav file names to the padded + audio samples + """ + for name in audios: + audios[name] = np.pad(audios[name], + (0, max_length-len(audios[name])), + mode = 'constant') + return audios + + +def augment_audio(audios : dict, sample_rate : int) -> dict: + """ + Here we shift the wave by sample_rate/10 factor. This will move the wave to the + right by given factor along time axis. For achieving this I have used numpy’s + roll function to generate time shifting. + + Inputs: + audios - a dictionary mapping the wav file names to the sampled audio array + sample_rate - the sample rate for the audio + + Returns: + audios - a python dictionary mapping the wav file names to the augmented + audio samples + """ + for name in audios: + audios[name] = np.roll(audios[name], int(sample_rate/10)) + return audios + +# def equalize_transcript_dimension(y, truncate_len): +# """ +# Make all transcripts have equal number of characters by padding the the short +# ones with spaces +# """ +# max_len = max([len(trans) for trans in y]) +# print("maximum number of characters in a transcript:", max_len) +# new_y = [] +# for trans in y: +# new_y.append(np.pad(trans, +# (0, max_len-len(trans)), +# mode = 'constant')[:truncate_len]) +# return np.array(new_y) + +def equalize_transcript_dimension(encoded_transcripts, truncate_len): + """ + Make all transcripts have equal number of characters by padding the the short + ones with spaces + """ + max_len = max([len(encoded_transcripts[trans]) for trans in encoded_transcripts]) + print("maximum number of characters in a transcript:", max_len) + new_trans = {} + for trans in encoded_transcripts: + new_trans[trans] = np.pad(encoded_transcripts[trans], + (0, max_len-len(encoded_transcripts[trans])), + mode = 'constant')[:truncate_len] + return new_trans \ No newline at end of file diff --git a/scripts/simpleRNN.py b/scripts/simpleRNN.py new file mode 100755 index 0000000..e0ac3dd --- /dev/null +++ b/scripts/simpleRNN.py @@ -0,0 +1,17 @@ +import tensorflow as tf +from tensorflow.keras.models import Model, Sequential +from tensorflow.keras.layers import * +from tensorflow.keras.preprocessing.sequence import pad_sequences +from tensorflow.keras.optimizers import SGD, Adam, RMSprop +from tensorflow.keras import backend as K + + +def simple_rnn_model(input_dim, output_dim=224): + + input_data = Input(name='the_input', shape=(None, input_dim)) + simp_rnn = GRU(output_dim, return_sequences=True, + implementation=2, name='rnn')(input_data) + y_pred = Activation('softmax', name='softmax')(simp_rnn) + model = Model(inputs=input_data, outputs=y_pred, name="simple_rnn_model") + model.output_length = lambda x: x + return model diff --git a/scripts/speech_model_infer.py b/scripts/speech_model_infer.py new file mode 100644 index 0000000..d3cd0ee --- /dev/null +++ b/scripts/speech_model_infer.py @@ -0,0 +1,84 @@ +from librosa.core import audio +import streamlit as st +import os +import sys + +from tokenizer import Tokenizer +import helper as helper +from model_helper import predict, build_model2 +from model2 import CNN_net, BidirectionalRNN2, preprocessin_model +import librosa +import tensorflow as tf + + +# sys.path.append(os.path.abspath(os.path.join('./scripts'))) + +class Speech_Model_Infer: + + def __init__(self) -> None: + + self.sample_rate = 8000 + self.fft_size = 512 + self.frame_step = 256 + self.n_mels = 128 + self.output_dim = 223 + self.batch_size = 32 + + self.preprocess_model = preprocessin_model( + self.sample_rate, self.fft_size, self.frame_step, self.n_mels) + + self.cnn_model, self.cnn_shape = CNN_net(self.n_mels) + self.BI_RNN_2 = BidirectionalRNN2( + 1024, batch_size=self.batch_size, output_dim=self.output_dim) + + self.cnn_bi_rnn_model = build_model2( + self.output_dim, self.cnn_model, self.BI_RNN_2, self.preprocess_model) + self.cnn_bi_rnn_model.load_weights("../models/cnn-bi-rnn.h5") + + self.int_to_char = helper.read_obj("../int_to_char.pkl") + self.char_to_int = helper.read_obj("../char_to_int.pkl") + + self.tokenizer = Tokenizer(None) + + def predict(self, audio_file): + + wav, _ = librosa.load(audio_file, sr=self.sample_rate) + pred, _ = predict(self.cnn_bi_rnn_model, wav, + self.tokenizer, self.int_to_char, None) + return pred + + + +if __name__ == "__main__": + audio_obj = helper.read_obj("../data/test_audio_dict.pkl") + trans_obj = helper.read_obj("../data/test_translation_dict.pkl") + + audios = [] + translations = [] + + for label in audio_obj: + audios.append(audio_obj[label][0]) + translations.append(trans_obj[label]) + + SI = Speech_Model_Infer() + tokenizer = SI.tokenizer + cnn_bi_rnn_model = SI.cnn_bi_rnn_model + int_to_char = SI.int_to_char + + for i in range(10): + + actual_translation = translations[i] + sample_test_audio = audios[i] + + predicted, error = predict(cnn_bi_rnn_model, sample_test_audio, + tokenizer, int_to_char, actual=actual_translation) + + print("actual", actual_translation) + print("predicted", predicted) + print(f"WER: {error:.2f}") + + print() + + +# translations.append(translation_obj[label]) +# print(SI.predict("./test2.wav")) diff --git a/scripts/test_model.py b/scripts/test_model.py new file mode 100644 index 0000000..a683f9b --- /dev/null +++ b/scripts/test_model.py @@ -0,0 +1,52 @@ +from dataset_loader import load_audio_files, load_transcripts, load_spectrograms_with_transcripts, load_spectrograms_with_transcripts_in_batches +from resize_and_augment import resize_audios_mono, augment_audio, equalize_transcript_dimension +from transcript_encoder import fit_label_encoder, encode_transcripts, decode_predicted +import numpy as np +import os +import logging +import pickle +import tensorflow as tf +from new_model import LogMelgramLayer, CTCLayer +import streamlit as st + + +def perform_predictions(path): + sample_rate = 44100 + audio_files, maximum_length = load_audio_files(path, sample_rate, True) + logging.info('loaded audio files') + audio_files = resize_audios_mono(audio_files, 440295) + enc = open('./models/encoder.pkl', 'rb') + char_encoder = pickle.load(enc) + print('model summary') + + def load_model(): + model = tf.keras.models.load_model('./models/new_model_v1_2000.h5', + custom_objects = { + 'LogMelgramLayer': LogMelgramLayer , + 'CTCLayer': CTCLayer} + ) + return model + model = load_model() + print(model.summary()) + + def load_data(audio_files): + X_train = [] + y_train = [] + for audio in audio_files: + X_train.append(audio_files[audio]) + + return np.array(X_train), np.array(y_train) + + X_test,y_test = load_data(audio_files) + + + if len(y_test) == 0: + y_test = np.array([[0]*70]) + predicted = model.predict([X_test,[y_test]]) + predicted_trans = decode_predicted(predicted, char_encoder) + + return predicted_trans + +z=perform_predictions('./data/wav/') +pribt(type(z)) + diff --git a/scripts/tokenizer.py b/scripts/tokenizer.py new file mode 100755 index 0000000..560ed31 --- /dev/null +++ b/scripts/tokenizer.py @@ -0,0 +1,45 @@ +from collections import Counter + + +class Tokenizer: + + def __init__(self, translations): + self.translations = translations + self.unk = -1 + + def build_dict(self): + text = '' + for t in self.translations: + text += t + + char_counts = Counter(text) + sorted_vocab = sorted(char_counts, key=char_counts.get, reverse=True) + int_to_char = {ii: word for ii, word in enumerate(sorted_vocab, 1)} + + char_to_int = {word: ii for ii, word in int_to_char.items()} + + return int_to_char, char_to_int + + def encode(self, sent, char_to_int): + + encoded = [] + char_list = list(sent) + for c in char_list: + try: + encoded.append(char_to_int[c]) + + except KeyError: + encoded.append(self.unk) + return encoded + + def decode_text(self, encoded_chars, int_to_char): + + decoded = '' + for e in encoded_chars: + try: + decoded += int_to_char[e] + + except KeyError: + decoded += '' + + return decoded diff --git a/scripts/train.py b/scripts/train.py new file mode 100644 index 0000000..036b8bb --- /dev/null +++ b/scripts/train.py @@ -0,0 +1,77 @@ +import sys + +from dataset_loader import load_audio_files, load_transcripts, load_spectrograms_with_transcripts, load_spectrograms_with_transcripts_in_batches +from resize_and_augment import resize_audios_mono, augment_audio, equalize_transcript_dimension +from FeatureExtraction import FeatureExtraction +from transcript_encoder import fit_label_encoder, encode_transcripts, decode_predicted +from models import model_1, model_2, model_3 + +import librosa #for audio processing +import librosa.display +import IPython.display as ipd +import matplotlib.pyplot as plt +import numpy as np +import warnings +import os +import mlflow +import mlflow.keras +import logging +len(os.listdir('../data/train/wav/')) + +sample_rate = 8000 + +audio_files, maximum_length = load_audio_files('../data/train/wav/', sample_rate, True) +logging.info('loaded audio files') + +print("The longest audio is", maximum_length/sample_rate, 'seconds long') +print("max length", maximum_length) + +demo_audio = list(audio_files.keys())[0] + +transcripts = load_transcripts("../data/train/trsTrain.txt") +logging.info('loaded transcripts') + +audio_files = resize_audios_mono(audio_files, maximum_length) +print("resized shape", audio_files[demo_audio].shape) + +audio_files = augment_audio(audio_files, sample_rate) +print("augmented shape", audio_files[demo_audio].shape) + +feature_extractor = FeatureExtraction() +mfcc_features = feature_extractor.extract_features(audio_files, sample_rate) + +feature_extractor.save_mfcc_spectrograms(mfcc_features, sample_rate, '../data/train/mfcc_spectros/') +print('Saved mfcc spectros') +feature_extractor.save_mel_spectrograms(audio_files, sample_rate, '../data/train/mel_spectros/') +print('saved mel spectros') + +char_encoder = fit_label_encoder(transcripts) +transcripts_encoded = encode_transcripts(transcripts, char_encoder) +enc_aug_transcripts = equalize_transcript_dimension(transcripts_encoded, 100) +print('model summary') +model = model_3(char_encoder) +print(model.summary()) + +import math + +data_batch_size = 9 +training_batch_size = 9 +number_of_epochs = 100 + +number_of_batches = math.ceil(len(mfcc_features)/data_batch_size) + +for i in range(number_of_epochs): + for j in range(number_of_batches): + print(f'Epoch {i+1}: training batch {j}') + X_train, y_train = load_spectrograms_with_transcripts_in_batches(mfcc_features, + enc_aug_transcripts, data_batch_size, j, + '../data/train/mel_spectros/') + history = model.fit([X_train, y_train], batch_size = training_batch_size, epochs = 1) +with mlflow.start_run() as run: + mlflow.log_metric("ctc_loss", history.history['loss'][-1]) + +predicted = model.predict([X_train,y_train]) +predicted_trans = decode_predicted(predicted, char_encoder) +real_trans = [''.join(char_encoder.inverse_transform(y)) for y in y_train] +print("pridicted:",predicted_trans[0]) +print("actual:",real_trans[0]) \ No newline at end of file diff --git a/scripts/transcript_encoder.py b/scripts/transcript_encoder.py new file mode 100644 index 0000000..2d63f46 --- /dev/null +++ b/scripts/transcript_encoder.py @@ -0,0 +1,59 @@ +from sklearn.preprocessing import LabelEncoder +import numpy as np + +def fit_label_encoder(transcripts : dict) -> LabelEncoder: + """ + This function encodes the amharic characters in the given dictiionary of + transcripts into integers. + + Input: + transcripts - a python dictionary mapping the wav file names to the transcripts + of those audio files. + Returns: + encoder - an sklearn label encoder that has been fitted with all the characters + in the transcripts. + """ + characters = [] + for audio in transcripts: + characters.extend(list(transcripts[audio])) + encoder = LabelEncoder() + encoder.fit_transform(characters) + return encoder + +def encode_transcripts(transcripts : dict, encoder : LabelEncoder) -> dict: + """ + This function takes an sklearn label encoder that has already been fitted with + the amharic characters from the transcripts, along with the original transcript + and encodes the transcripts for each audio using the given label encoder. + + Input: + transcripts - a python dictionary mapping the wav file names to the transcripts + of those audio files. + encoder - an sklearn label encoder that has been fitted with all the characters + in the transcripts. + + Returns: + transcripts_encoded - a python dictionary mapping the wav file names to the encoded transcripts + of those audio files. + """ + transcripts_encoded = {} + for audio in transcripts: + transcripts_encoded[audio] = encoder.transform(list(transcripts[audio])) + return transcripts_encoded + +def decode_predicted(pred,encoder): + """ + remove the blank character from the predictions and decode the integers back to + amharic characters. + """ + dec = [] + for a in pred: + l = [np.argmax(b) for b in a] + newl = [] + for i in range(len(l)-1): + if l[i]!=222 and l[i+1]!=l[i]: + newl.append(l[i]) + if l[-1] != 222: + newl.append(l[-1]) + dec.append(''.join(encoder.inverse_transform(newl)).strip()) + return dec \ No newline at end of file