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updated base.py. (winfunc added in logfbank) #67

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merged 1 commit into from Jul 24, 2018
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updated base.py. (winfunc added in logfbank) #67

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6 changes: 4 additions & 2 deletions python_speech_features/base.py
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Expand Up @@ -64,7 +64,8 @@ def fbank(signal,samplerate=16000,winlen=0.025,winstep=0.01,
return feat,energy

def logfbank(signal,samplerate=16000,winlen=0.025,winstep=0.01,
nfilt=26,nfft=512,lowfreq=0,highfreq=None,preemph=0.97):
nfilt=26,nfft=512,lowfreq=0,highfreq=None,preemph=0.97,
winfunc=lambda x:numpy.ones((x,))):
"""Compute log Mel-filterbank energy features from an audio signal.

:param signal: the audio signal from which to compute features. Should be an N*1 array
Expand All @@ -76,9 +77,10 @@ def logfbank(signal,samplerate=16000,winlen=0.025,winstep=0.01,
:param lowfreq: lowest band edge of mel filters. In Hz, default is 0.
:param highfreq: highest band edge of mel filters. In Hz, default is samplerate/2
:param preemph: apply preemphasis filter with preemph as coefficient. 0 is no filter. Default is 0.97.
:param winfunc: the analysis window to apply to each frame. By default no window is applied. You can use numpy window functions here e.g. winfunc=numpy.hamming
:returns: A numpy array of size (NUMFRAMES by nfilt) containing features. Each row holds 1 feature vector.
"""
feat,energy = fbank(signal,samplerate,winlen,winstep,nfilt,nfft,lowfreq,highfreq,preemph)
feat,energy = fbank(signal,samplerate,winlen,winstep,nfilt,nfft,lowfreq,highfreq,preemph,winfunc)
return numpy.log(feat)

def ssc(signal,samplerate=16000,winlen=0.025,winstep=0.01,
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