(powspec,
               sr=8000,
               feature_size=40,
               nfft=512,
               lowfreq=0,
               highfreq=None)
return feat
powspec: [audio_channels, spectrogram_length, spectrogram_feat_dim]
      return : [auido_chnnels, nframe, nfbank]
powspec: [audio_channels, spectrogram_length, spectrogram_feat_dim]
      return : [auido_chnnels, nframe, nfbank]
powspec : [ audio_channels spectrogram_length spectrogram_feat_dim ] return : [ auido_chnnels nframe nfbank ]
def fbank_feat(powspec,
               sr=8000,
               feature_size=40,
               nfft=512,
               lowfreq=0,
               highfreq=None):
  ''' powspec: [audio_channels, spectrogram_length, spectrogram_feat_dim]
      return : [auido_chnnels, nframe, nfbank]
  '''
  del nfft

  true_fn = lambda: tf.expand_dims(powspec, 0)
  false_fn = lambda: powspec
  powspec = tf.cond(tf.equal(tf.rank(powspec), 2), true_fn, false_fn)

  feat = py_x_ops.fbank(
      powspec,
      sr,
      filterbank_channel_count=feature_size,
      lower_frequency_limit=lowfreq,
      upper_frequency_limit=highfreq,
  )
  return feat
def fbank_feat ( powspec , sr = 8000 , feature_size = 40 , nfft = 512 , lowfreq = 0 , highfreq = None ) : del nfft true_fn = lambda : tf . expand_dims ( powspec , 0 ) false_fn = lambda : powspec powspec = tf . cond ( tf . equal ( tf . rank ( powspec ) , 2 ) , true_fn , false_fn ) feat = py_x_ops . fbank ( powspec , sr , filterbank_channel_count = feature_size , lower_frequency_limit = lowfreq , upper_frequency_limit = highfreq , ) return feat