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egs/chime4/s5_1ch/local/rnnlm/run_lstm_back.sh
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#!/bin/bash
# Copyright 2012 Johns Hopkins University (author: Daniel Povey)
# 2015 Guoguo Chen
# 2017 Hainan Xu
# 2017 Szu-Jui Chen
# This script trains LMs on the reversed Chime4 data, which we
# call it backward model.
# Begin configuration section.
affix=1a
dir=exp/rnnlm_lstm_${affix}_back
embedding_dim=2048
lstm_rpd=512
lstm_nrpd=512
stage=-10
train_stage=-10
# variables for lattice rescoring
ngram_order=4 # approximate the lattice-rescoring by limiting the max-ngram-order
# if it's set, it merges histories in the lattice if they share
# the same ngram history and this prevents the lattice from
# exploding exponentially
. cmd.sh
. utils/parse_options.sh
srcdir=data/local/local_lm
lexicon=data/local/dict/lexiconp.txt
text_dir=data/rnnlm/text_nosp_${affix}_back
mkdir -p $dir/config
set -e
for f in $lexicon; do
[ ! -f $f ] && \
echo "$0: expected file $f to exist; search for local/wsj_extend_dict.sh in run.sh" && exit 1
done
#prepare training and dev data
if [ $stage -le 0 ]; then
mkdir -p $text_dir
cat $srcdir/train.rnn | awk '{for(i=NF;i>0;i--) printf("%s ",$i); print""}'> $text_dir/chime4.txt.tmp
sed -e "s/<RNN_UNK>/<UNK>/g" $text_dir/chime4.txt.tmp > $text_dir/chime4.txt
rm $text_dir/chime4.txt.tmp
cat $srcdir/valid.rnn | awk '{for(i=NF;i>0;i--) printf("%s ",$i); print""}'> $text_dir/dev.txt
fi
if [ $stage -le 1 ]; then
cp data/lang_chain/words.txt $dir/config/words.txt
n=`cat $dir/config/words.txt | wc -l`
echo "<brk> $n" >> $dir/config/words.txt
# words that are not present in words.txt but are in the training or dev data, will be
# mapped to <SPOKEN_NOISE> during training.
echo "<UNK>" >$dir/config/oov.txt
cat > $dir/config/data_weights.txt <<EOF
chime4 1 1.0
EOF
rnnlm/get_unigram_probs.py --vocab-file=$dir/config/words.txt \
--unk-word="<UNK>" \
--data-weights-file=$dir/config/data_weights.txt \
$text_dir | awk 'NF==2' >$dir/config/unigram_probs.txt
# choose features
rnnlm/choose_features.py --unigram-probs=$dir/config/unigram_probs.txt \
--use-constant-feature=true \
--special-words='<s>,</s>,<UNK>,<brk>' \
$dir/config/words.txt > $dir/config/features.txt
cat >$dir/config/xconfig <<EOF
input dim=$embedding_dim name=input
relu-renorm-layer name=tdnn1 dim=$embedding_dim input=Append(0, IfDefined(-1))
fast-lstmp-layer name=lstm1 cell-dim=$embedding_dim recurrent-projection-dim=$lstm_rpd non-recurrent-projection-dim=$lstm_nrpd
relu-renorm-layer name=tdnn2 dim=$embedding_dim input=Append(0, IfDefined(-3))
fast-lstmp-layer name=lstm2 cell-dim=$embedding_dim recurrent-projection-dim=$lstm_rpd non-recurrent-projection-dim=$lstm_nrpd
relu-renorm-layer name=tdnn3 dim=$embedding_dim input=Append(0, IfDefined(-3))
output-layer name=output include-log-softmax=false dim=$embedding_dim
EOF
rnnlm/validate_config_dir.sh $text_dir $dir/config
fi
if [ $stage -le 2 ]; then
rnnlm/prepare_rnnlm_dir.sh $text_dir $dir/config $dir
fi
if [ $stage -le 3 ]; then
rnnlm/train_rnnlm.sh --num-jobs-initial 1 --num-jobs-final 3 \
--stage $train_stage --num-epochs 10 --cmd "$train_cmd" $dir
fi
exit 0
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