(frames, nfft, norm=1)
return log_power
Compute the log power spectrum of each frame in frames. If frames is an NxD matrix, output will be Nx(NFFT/2+1).

    :param frames: the array of frames. Each row is a frame.
    :param NFFT: the FFT length to use. If NFFT > frame_len, the frames are zero-padded.
    :param norm: If norm=1, the log power spectrum is normalised so that the max value (across all frames) is 0.
    :returns: If frames is an NxD matrix, output will be Nx(NFFT/2+1). Each row will be the log power spectrum of the corresponding frame.
Compute the log power spectrum of each frame in frames. If frames is an NxD matrix, output will be Nx(NFFT/2+1).
Compute the log power spectrum of each frame in frames . If frames is an NxD matrix output will be Nx ( NFFT / 2 + 1 ) .
def logpowspec(frames, nfft, norm=1):
  """Compute the log power spectrum of each frame in frames. If frames is an NxD matrix, output will be Nx(NFFT/2+1).

    :param frames: the array of frames. Each row is a frame.
    :param NFFT: the FFT length to use. If NFFT > frame_len, the frames are zero-padded.
    :param norm: If norm=1, the log power spectrum is normalised so that the max value (across all frames) is 0.
    :returns: If frames is an NxD matrix, output will be Nx(NFFT/2+1). Each row will be the log power spectrum of the corresponding frame.
    """
  power = powspec(frames, nfft)
  power[power <= 1e-30] = 1e-30
  log_power = 10 * numpy.log10(power)
  if norm:
    return log_power - numpy.max(log_power)
  return log_power
def logpowspec ( frames , nfft , norm = 1 ) : power = powspec ( frames , nfft ) power [ power <= 1e-30 ] = 1e-30 log_power = 10 * numpy . log10 ( power ) if norm : return log_power - numpy . max ( log_power ) return log_power