run.sh
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#!/bin/bash -e
# Copyright 2014 QCRI (author: Ahmed Ali)
# Apache 2.0
num_jobs=120
num_decode_jobs=40
decode_gmm=true
stage=0
overwrite=false
dir1=/export/corpora/LDC/LDC2013S02/
dir2=/export/corpora/LDC/LDC2013S07/
dir3=/export/corpora/LDC/LDC2014S07/
text1=/export/corpora/LDC/LDC2013T17/
text2=/export/corpora/LDC/LDC2013T04/
text3=/export/corpora/LDC/LDC2014T17/
galeData=GALE
. ./cmd.sh ## You'll want to change cmd.sh to something that will work on your system.
## This relates to the queue.
. ./path.sh
. ./utils/parse_options.sh # e.g. this parses the above options
# if supplied.
if [ $stage -le 0 ]; then
if [ -f data/train/text ] && ! $overwrite; then
echo "$0: Not processing, probably script have run from wrong stage"
echo "Exiting with status 1 to avoid data corruption"
exit 1;
fi
echo "$0: Preparing data..."
local/prepare_data.sh --dir1 $dir1 --dir2 $dir2 --dir3 $dir3 \
--text1 $text1 --text2 $text2 --text3 $text3
echo "$0: Preparing lexicon and LM..."
local/prepare_dict.sh
utils/prepare_lang.sh data/local/dict "<UNK>" data/local/lang data/lang
local/prepare_lm.sh
utils/format_lm.sh data/lang data/local/lm/lm.gz \
data/local/dict/lexicon.txt data/lang_test
fi
mfccdir=mfcc
if [ $stage -le 1 ]; then
echo "$0: Preparing the test and train feature files..."
for x in train test ; do
steps/make_mfcc.sh --cmd "$train_cmd" --nj $num_jobs \
data/$x exp/make_mfcc/$x $mfccdir
utils/fix_data_dir.sh data/$x # some files fail to get mfcc for many reasons
steps/compute_cmvn_stats.sh data/$x exp/make_mfcc/$x $mfccdir
done
fi
if [ $stage -le 2 ]; then
echo "$0: creating sub-set and training monophone system"
utils/subset_data_dir.sh data/train 10000 data/train.10K || exit 1;
steps/train_mono.sh --nj 40 --cmd "$train_cmd" \
data/train.10K data/lang exp/mono || exit 1;
fi
if [ $stage -le 3 ]; then
echo "$0: Aligning data using monophone system"
steps/align_si.sh --nj $num_jobs --cmd "$train_cmd" \
data/train data/lang exp/mono exp/mono_ali || exit 1;
echo "$0: training triphone system with delta features"
steps/train_deltas.sh --cmd "$train_cmd" \
2500 30000 data/train data/lang exp/mono_ali exp/tri1 || exit 1;
fi
if [ $stage -le 4 ] && $decode_gmm; then
utils/mkgraph.sh data/lang_test exp/tri1 exp/tri1/graph
steps/decode.sh --nj $num_decode_jobs --cmd "$decode_cmd" \
exp/tri1/graph data/test exp/tri1/decode
fi
if [ $stage -le 5 ]; then
echo "$0: Aligning data and retraining and realigning with lda_mllt"
steps/align_si.sh --nj $num_jobs --cmd "$train_cmd" \
data/train data/lang exp/tri1 exp/tri1_ali || exit 1;
steps/train_lda_mllt.sh --cmd "$train_cmd" 4000 50000 \
data/train data/lang exp/tri1_ali exp/tri2b || exit 1;
fi
if [ $stage -le 6 ] && $decode_gmm; then
utils/mkgraph.sh data/lang_test exp/tri2b exp/tri2b/graph
steps/decode.sh --nj $num_decode_jobs --cmd "$decode_cmd" \
exp/tri2b/graph data/test exp/tri2b/decode
fi
if [ $stage -le 7 ]; then
echo "$0: Aligning data and retraining and realigning with sat_basis"
steps/align_si.sh --nj $num_jobs --cmd "$train_cmd" \
data/train data/lang exp/tri2b exp/tri2b_ali || exit 1;
steps/train_sat_basis.sh --cmd "$train_cmd" \
5000 100000 data/train data/lang exp/tri2b_ali exp/tri3b || exit 1;
steps/align_fmllr.sh --nj $num_jobs --cmd "$train_cmd" \
data/train data/lang exp/tri3b exp/tri3b_ali || exit 1;
fi
if [ $stage -le 8 ] && $decode_gmm; then
utils/mkgraph.sh data/lang_test exp/tri3b exp/tri3b/graph
steps/decode_fmllr.sh --nj $num_decode_jobs --cmd \
"$decode_cmd" exp/tri3b/graph data/test exp/tri3b/decode
fi
if [ $stage -le 9 ]; then
echo "$0: Training a regular chain model using the e2e alignments..."
local/chain/run_tdnn.sh
fi
echo "$0: training succedded"
exit 0