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An NLP based approach to detect and identify languages word-by-word for audio data on local Pakistani languages

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Language-Localization

An NLP based approach to detect and identify languages word-by-word for audio data on local Pakistani languages

Language Localization on Audio Files and Live Audio

Nabeel Danish

A spectogram-based approach to identifying langauges most commonly spoken in Pakistan. This includes Urdu, English, Arabic, Pashto, and Sindhi. The model is contructed as CNN with LSTM layers achieving an accuracy of 95%.

Usage

import the file languageLocalization.py to use in your script

Functions

def languageLocalize(inputFile, extension, chunk_file):
Parameters:

inputFile -- path to file for audio
extension -- audio file extension
chunk_file -- path to folder where the model stores preprocessing data

Return Value:

pred -- python array of strings containing the languauges predicted at positional interval
	pred[i] is the language detected between (i - 1) and (i)th second
	Example:
		pred[3] = 'english' means english detected between 2-3 sec of audio

Live Audio Detection

the notebook contains the script to run live detection on audio.

Dependancies

Tensorflow Keras Numpy Scipy Pydub Librosa

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An NLP based approach to detect and identify languages word-by-word for audio data on local Pakistani languages

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