| # 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. | |
| --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... this is high-bandwidth data, so | |
| # there might be some information at the low end. | |
| --high-freq=7600 # high cutoff frequently, relative to Nyquist of 8000 (=7600) | |
| --allow_downsample=true | |