run_nnet2_common.sh
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#!/bin/bash
# this script contains some common (shared) parts of the run_nnet*.sh scripts.
. ./cmd.sh
stage=0
set -e
. ./cmd.sh
. ./path.sh
. ./utils/parse_options.sh
if [ $stage -le 1 ]; then
# Create high-resolution MFCC features (with 40 cepstra instead of 13).
# this shows how you can split across multiple file-systems. we'll split the
# MFCC dir across multiple locations. You might want to be careful here, if you
# have multiple copies of Kaldi checked out and run the same recipe, not to let
# them overwrite each other.
mfccdir=mfcc
if [[ $(hostname -f) == *.clsp.jhu.edu ]] && [ ! -d $mfccdir/storage ]; then
utils/create_split_dir.pl /export/b0{1,2,3,4}/$USER/kaldi-data/egs/librispeech-$(date +'%m_%d_%H_%M')/s5/$mfccdir/storage $mfccdir/storage
fi
for datadir in train_960 dev_clean dev_other; do
utils/copy_data_dir.sh data/$datadir data/${datadir}_hiresp
steps/make_mfcc_pitch_online.sh --nj 150 --mfcc-config conf/mfcc_hires.conf \
--online-pitch-config conf/online_pitch.conf \
--cmd "$train_cmd" data/${datadir}_hiresp exp/make_hiresp/$datadir $mfccdir || exit 1;
steps/compute_cmvn_stats.sh data/${datadir}_hiresp exp/make_hiresp/$datadir $mfccdir || exit 1;
# dump plain MFCC features by selecting MFCC-only part
steps/select_feats.sh 0-39 data/${datadir}_hiresp data/${datadir}_hires exp/make_hires/$datadir $mfccdir || exit 1;
steps/compute_cmvn_stats.sh data/${datadir}_hires exp/make_hires/$datadir $mfccdir || exit 1;
done
# now create some data subsets.
# mixed is the clean+other data.
# 30k is 1/10 of the data (around 100 hours), 60k is 1/5th of it (around 200 hours).
utils/subset_data_dir.sh data/train_960_hires 30000 data/train_mixed_hires_30k
utils/subset_data_dir.sh data/train_960_hires 60000 data/train_mixed_hires_60k
fi
# The stages where we build the iVector extractor are the same as the
# non-pitch system, because the features given to the iVector extractor don't use pitch.
steps/online/run_nnet2_common.sh --stage 2 || exit 1;
exit 0;