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A convolutional neural net for identifying the language being spoken in short wav audio clips.

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joecomerisnotavailable/Lingua_Franca

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What:

A convolutional neural network for recognizing the language being spoken in short (about 3-10 second) wav recordings by first converting the raw audio to Mel-Frequency Cepstral Coefficient images.

How:

To train: Run train.py --modeldir=[directory_to_save_model] <-v[erbose_logging]>

To test: Drop any desired test audio into the test-audio folder, add the filename and label to the files.csv file there, and run `predict.py --modeldir=[directory_of_saved_model] <-v[erbose_logging]>

Requirements:

argparse tempfile tensorflow >1.8.0 numpy pandas sklearn

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A convolutional neural net for identifying the language being spoken in short wav audio clips.

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