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I am trying to implement a spoken language identifier from audio files, using Neural Network. I need to generate one feature vector for each audio file.

From what I have read the best features (for my purpose) to extract from the a .wav audio file are the MFCC.

Does anyone know of a Python code that does such a thing?

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    $\begingroup$ Your question is too broad. We can't really just explain how to pick an appropriate feature extractor without writing a couple thousand lines of code or writing a textbook on speech recognition. That's exactly what I'd recommend here: read a textbook on classical speech recognition. And instead of the classical classificators, you plug in DNNs. $\endgroup$ – Marcus Müller Jan 3 '17 at 12:06
  • $\begingroup$ use python_speech_features; a library to extract features from sounds; look for it on github $\endgroup$ – Anonymous Jul 13 '18 at 20:59
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Have a look at these two python libraries that provide a number of audio features easily from WAV files, including MFCC.

Good luck!

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