# config for high-resolution MFCC features, intended for neural network training.
# Note: we keep all cepstra, so it has the same info as filterbank features,
# but MFCC is more easily compressible (because less correlated) which is why
# we prefer this method.
--use-energy=false       # use average of log energy, not energy.
--sample-frequency=16000 # AISHELL-2 is sampled at 16kHz
--num-mel-bins=40        # similar to Google's setup.
--num-ceps=40            # there is no dimensionality reduction.
--low-freq=20            # low cutoff frequency for mel bins
--high-freq=-400         # high cutoff frequency, relative to Nyquist of 8000 (=7600)
