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#!/bin/bash | ||
. ./cmd.sh || exit 1; | ||
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nj=16 # number of parallel jobs in feature extraction | ||
sampling_rate=16000 # sampling frequency | ||
fmax= # maximum frequency | ||
fmin= # minimum frequency | ||
num_mels=80 # number of mel basis | ||
fft_size=1024 # number of fft points | ||
hop_size=256 # number of shift points | ||
win_length= # window length | ||
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train_set="train" # name of training data directory | ||
dev_set="val" # name of development data directory | ||
eval_set="val" # name of evaluation data directory | ||
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stage=0 | ||
stop_stage=100 | ||
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. parse_options.sh || exit 1; # This allows you to pass command line arguments, e.g. --fmax 7600 | ||
set -eo pipefail | ||
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datadir=$PWD/data | ||
featdir=$PWD/feats | ||
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if [ "${stage}" -le 0 ] && [ "${stop_stage}" -ge 0 ]; then | ||
echo "Fbank Feature Extraction" | ||
for x in ${train_set} ${dev_set} ${eval_set} ; do | ||
utils/fix_data_dir.sh ${datadir}/${x} | ||
make_fbank.sh --cmd "${train_cmd}" --nj ${nj} \ | ||
--fs ${sampling_rate} \ | ||
--fmax "${fmax}" \ | ||
--fmin "${fmin}" \ | ||
--n_fft ${fft_size} \ | ||
--n_shift ${hop_size} \ | ||
--win_length "${win_length}" \ | ||
--n_mels ${num_mels} \ | ||
${datadir}/${x} \ | ||
exp/make_fbank/${x} \ | ||
${featdir}/fbank/${x} | ||
mv ${datadir}/${x}/feats.scp ${featdir}/fbank/${x} | ||
done | ||
fi | ||
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if [ "${stage}" -le 1 ] && [ "${stop_stage}" -ge 1 ]; then | ||
echo "Cepstral Mean Variance Normalization" | ||
feat_name=fbank | ||
compute-cmvn-stats.py scp:${featdir}/${feat_name}/${train_set}/feats.scp ${featdir}/${feat_name}/${train_set}/cmvn.ark | ||
for x in ${train_set} ${dev_set} ${eval_set} ; do | ||
echo "Applying normalization for dataset ${x}" | ||
mkdir -p ${featdir}/normed_${feat_name}/${x} ; | ||
apply-cmvn.py --norm-vars=true --compress True \ | ||
${featdir}/${feat_name}/${train_set}/cmvn.ark \ | ||
scp:${featdir}/${feat_name}/${x}/feats.scp \ | ||
ark,scp:${featdir}/normed_${feat_name}/${x}/feats.ark,${featdir}/normed_${feat_name}/${x}/feats.scp | ||
done | ||
fi |