Kaldi 提取MFCC40维的参数设置

来源：星星旅游

1. 数据准备：wave文件，，获取wav.scp，spk2utt，utt2spk三个文件

find /*/16kwav -name '*.wav' | awk -F '/' '{print $NF " " $0}' > ./data/wav.scp

find /*/16kwav -name '*.wav' | awk -F '/' '{print $NF " " $NF}' > ./data/spk2utt

find /*/16kwav -name '*.wav' | awk -F '/' '{print $NF " " $NF}' > ./data/utt2spk

2. 特征提取

首先需要更改conf/mfcc.conf文件参数，更改如下：

# 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)

接下来运行如下命令：

utils/fix_data_dir.sh /*/data

./steps/make_mfcc.sh /*/data ./ts_log /*/data/mfcc

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