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55 lines
1.8 KiB
55 lines
1.8 KiB
3 years ago
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.. python_speech_features documentation master file, created by
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sphinx-quickstart on Thu Oct 31 16:49:58 2013.
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You can adapt this file completely to your liking, but it should at least
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contain the root `toctree` directive.
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Welcome to python_speech_features's documentation!
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==================================================
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This library provides common speech features for ASR including MFCCs and filterbank energies.
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If you are not sure what MFCCs are, and would like to know more have a look at this MFCC tutorial:
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http://www.practicalcryptography.com/miscellaneous/machine-learning/guide-mel-frequency-cepstral-coefficients-mfccs/.
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You will need numpy and scipy to run these files. The code for this project is available at https://github.com/jameslyons/python_speech_features .
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Supported features:
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- :py:meth:`python_speech_features.mfcc` - Mel Frequency Cepstral Coefficients
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- :py:meth:`python_speech_features.fbank` - Filterbank Energies
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- :py:meth:`python_speech_features.logfbank` - Log Filterbank Energies
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- :py:meth:`python_speech_features.ssc` - Spectral Subband Centroids
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To use MFCC features::
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from python_speech_features import mfcc
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from python_speech_features import logfbank
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import scipy.io.wavfile as wav
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(rate,sig) = wav.read("file.wav")
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mfcc_feat = mfcc(sig,rate)
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fbank_feat = logfbank(sig,rate)
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print(fbank_feat[1:3,:])
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From here you can write the features to a file etc.
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Functions provided in python_speech_features module
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-------------------------------------
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.. automodule:: python_speech_features.base
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:members:
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Functions provided in sigproc module
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------------------------------------
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.. automodule:: python_speech_features.sigproc
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:members:
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Indices and tables
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==================
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* :ref:`genindex`
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* :ref:`search`
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