def magspec(signal, samplerate, conf):
'''
Compute magnitude spectrogram features from an audio signal.
Args:
signal: the audio signal from which to compute features. Should be an
N*1 array
samplerate: the samplerate of the signal we are working with.
conf: feature configuration
Returns:
A numpy array of size (NUMFRAMES by numfreq) containing features. Each
row holds 1 feature vector, a numpy vector containing the magnitude
spectrum of the corresponding frame
'''
signal = sigproc.preemphasis(signal, float(conf['preemph']))
winfunc = _get_winfunc(conf['winfunc'])
frames = sigproc.framesig(signal,
float(conf['winlen']) * samplerate,
float(conf['winstep']) * samplerate, winfunc)
magspec = sigproc.magspec(frames, int(conf['nfft']))
return magspec
def do_mfcc(self, fft_n, mffc_ch):
""" produces magnitude-> pow.spec on a freq scale """
self.nfft = fft_n
self.nmffc = mffc_ch
self.mag = sigproc.magspec(self.samples, self.nfft)
self.powspec2 = np.square(self.mag)
self.powspec1 = sigproc.powspec(self.samples,self.nfft)
self.bank = get_filterbanks(nfilt=self.nmffc, nfft=self.nfft, samplerate=self.hz)
self.mfc = np.dot(self.powspec1, self.bank.T)
return self.mfc