code: def lmfe(signal, sampling_frequency, frame_length=0.020, frame_stride=0.01,
           num_filters=40, fft_length=512, low_frequency=0, high_frequency=None):
      
  
      feature, frame_energies = mfe(signal,
                                    sampling_frequency=sampling_frequency,
                                    frame_length=frame_length,
                                    frame_stride=frame_stride,
                                    num_filters=num_filters,
                                    fft_length=fft_length,
                                    low_frequency=low_frequency,
                                    high_frequency=high_frequency)
      feature = np.log(feature)
  
      return feature
docs: Compute log Mel-filterbank energy features from an audio signal.
  
  
      Args:
           signal (array): the audio signal from which to compute features.
               Should be an N x 1 array
           sampling_frequency (int): the sampling frequency of the signal
               we are working with.
           frame_length (float): the length of each frame in seconds.
               Default is 0.020s
           frame_stride (float): the step between successive frames in seconds.
               Default is 0.02s (means no overlap)
           num_filters (int): the number of filters in the filterbank,
               default 40.
           fft_length (int): number of FFT points. Default is 512.
           low_frequency (float): lowest band edge of mel filters.
               In Hz, default is 0.
           high_frequency (float): highest band edge of mel filters.
               In Hz, default is samplerate/2
  
      Returns:
                array: Features - The log energy of fiterbank of size num_frames x num_filters frame_log_energies. The log energy of each frame num_frames x 1