Staging

.gitignore

@@ -1 +1,3 @@
 /data
+/notebooks/mlruns/
+/models/*

README.md

@@ -6,25 +6,9 @@
 
 <p>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.</p>
 
+## 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"```

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()