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forked from `<https://github.com/jameslyons/python_speech_features>`_
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check the readme therein for the usages
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It has been modified to produce the same results as with the compute-mfcc-feats and compute-fbank-feats (check their default parameters first) commands in Kaldi.
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-------------------------------
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The compute-mfcc-feats pipeline:
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src/featbin/Compute-mfcc-feats.cc
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Mfcc mfcc(mfcc_opts) --> src/feat/Feature-mfcc.h
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struct MfccOptions
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typedef OfflineFeatureTpl<MfccComputer> Mfcc --> src/feat/Feature-common.h
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MfccComputer() --> src/feat/Feature-mfcc.cc
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ComputeDctMatrix() --> src/matrix/Matrix-functions.cc
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ComputeLifterCoeffs() --> src/feat/Mel-computations.cc
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for each utterance:
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mfcc.ComputeFeatures()
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src/feat/Feature-common-inl.h
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OfflineFeatureTpl<F>::ComputeFeatures()
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Compute()
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ExtractWindow() --> src/feat/Feature-window.cc
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ProcessWindow()
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Dither, remove_dc_offset, log_energy_pre_window, Preemphasize, window
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computer_.Compute() --> src/feat/Feature-mfcc.cc
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MfccComputer::Compute()
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const MelBanks &mel_banks --> Mel-computations.cc
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srfft_
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ComputerPowerSpectrum()
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mel_banks.Compute()
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mel_energies_.ApplyLog()
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dct, cepstral_lifter
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