def delta_delta(fbank, sr=8000, feature_size=40):
'''
params:
fbank: [nframe, nfbank]
return : [nframe, nfbank, 3]
'''
del sr, feature_size
assert fbank.ndim == 2
delta = psf.delta(fbank, N=2)
_delta_delta = psf.delta(delta, N=2)
return np.stack([fbank, delta, _delta_delta], axis=-1)
def extract_fbank(samples, sr=8000, winlen=0.025, winstep=0.01,
feature_size=40):
''' extract logfbank with delta and delta-delta
Return:
ndarray of shape [nfrmae, feature_size * 3]
'''
feat = psf.logfbank(
samples,
nfilt=feature_size,
samplerate=sr,
winlen=winlen,
winstep=winstep,
lowfreq=0,
highfreq=None,
preemph=0.97)
delta = psf.delta(feat, N=2)
_delta_delta = psf.delta(delta, N=2)
return np.stack([feat, delta, _delta_delta], axis=-1)
