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egs/wsj/s5/steps/nnet3/align.sh
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#!/bin/bash # Copyright 2012 Brno University of Technology (Author: Karel Vesely) # 2013 Johns Hopkins University (Author: Daniel Povey) # 2015 Vijayaditya Peddinti # 2016 Vimal Manohar # Apache 2.0 # Computes training alignments using nnet3 DNN # Warning: this script uses GPUs by default, and this is generally not # an efficient use of GPUs. Set --use-gpu false to make it run on CPU. # Begin configuration section. nj=4 cmd=run.pl # Begin configuration. scale_opts="--transition-scale=1.0 --acoustic-scale=0.1 --self-loop-scale=0.1" beam=10 retry_beam=40 iter=final use_gpu=true frames_per_chunk=50 extra_left_context=0 extra_right_context=0 extra_left_context_initial=-1 extra_right_context_final=-1 online_ivector_dir= graphs_scp= # End configuration options. echo "$0 $@" # Print the command line for logging [ -f path.sh ] && . ./path.sh # source the path. . parse_options.sh || exit 1; if [ $# != 4 ]; then echo "Usage: $0 <data-dir> <lang-dir> <src-dir> <align-dir>" echo "e.g.: $0 data/train data/lang exp/nnet4 exp/nnet4_ali" echo "Warning: this script uses GPUs by default, and this is generally not" echo "an efficient use of GPUs. Set --use-gpu false to make it run on CPU." echo "" echo "main options (for others, see top of script file)" echo " --config <config-file> # config containing options" echo " --nj <nj> # number of parallel jobs" echo " --cmd (utils/run.pl|utils/queue.pl <queue opts>) # how to run jobs." exit 1; fi data=$1 lang=$2 srcdir=$3 dir=$4 oov=`cat $lang/oov.int` || exit 1; mkdir -p $dir/log echo $nj > $dir/num_jobs sdata=$data/split${nj} [[ -d $sdata && $data/feats.scp -ot $sdata ]] || \ split_data.sh $data $nj || exit 1; if $use_gpu; then queue_opt="--gpu 1" gpu_opt="--use-gpu=yes" else queue_opt="" gpu_opt="--use-gpu=no" fi extra_files= if [ ! -z "$online_ivector_dir" ]; then steps/nnet2/check_ivectors_compatible.sh $srcdir $online_ivector_dir || exit 1 extra_files="$online_ivector_dir/ivector_online.scp $online_ivector_dir/ivector_period" fi for f in $srcdir/tree $srcdir/${iter}.mdl $data/feats.scp $lang/L.fst $extra_files; do [ ! -f $f ] && echo "$0: no such file $f" && exit 1; done cp $srcdir/{tree,${iter}.mdl} $dir || exit 1; utils/lang/check_phones_compatible.sh $lang/phones.txt $srcdir/phones.txt || exit 1; cp $lang/phones.txt $dir || exit 1; ## Set up features. Note: these are different from the normal features ## because we have one rspecifier that has the features for the entire ## training set, not separate ones for each batch. echo "$0: feature type is raw" cmvn_opts=`cat $srcdir/cmvn_opts 2>/dev/null` cp $srcdir/cmvn_opts $dir 2>/dev/null feats="ark,s,cs:apply-cmvn $cmvn_opts --utt2spk=ark:$sdata/JOB/utt2spk scp:$sdata/JOB/cmvn.scp scp:$sdata/JOB/feats.scp ark:- |" ivector_opts= if [ ! -z "$online_ivector_dir" ]; then ivector_period=$(cat $online_ivector_dir/ivector_period) || exit 1; ivector_opts="--online-ivectors=scp:$online_ivector_dir/ivector_online.scp --online-ivector-period=$ivector_period" fi echo "$0: aligning data in $data using model from $srcdir, putting alignments in $dir" frame_subsampling_opt= if [ -f $srcdir/frame_subsampling_factor ]; then # e.g. for 'chain' systems frame_subsampling_factor=$(cat $srcdir/frame_subsampling_factor) frame_subsampling_opt="--frame-subsampling-factor=$frame_subsampling_factor" cp $srcdir/frame_subsampling_factor $dir if [ "$frame_subsampling_factor" -gt 1 ] && \ [ "$scale_opts" == "--transition-scale=1.0 --acoustic-scale=0.1 --self-loop-scale=0.1" ]; then echo "$0: frame-subsampling-factor is not 1 (so likely a chain system)," echo "... but the scale opts are the defaults. You probably want" echo "--scale-opts '--transition-scale=1.0 --acoustic-scale=1.0 --self-loop-scale=1.0'" sleep 1 fi fi if [ ! -z "$graphs_scp" ]; then if [ ! -f $graphs_scp ]; then echo "Could not find graphs $graphs_scp" && exit 1 fi tra="scp:utils/filter_scp.pl $sdata/JOB/utt2spk $graphs_scp |" prog=compile-train-graphs-fsts else tra="ark:utils/sym2int.pl --map-oov $oov -f 2- $lang/words.txt $sdata/JOB/text|"; prog=compile-train-graphs fi $cmd $queue_opt JOB=1:$nj $dir/log/align.JOB.log \ $prog --read-disambig-syms=$lang/phones/disambig.int $dir/tree \ $srcdir/${iter}.mdl $lang/L.fst "$tra" ark:- \| \ nnet3-align-compiled $scale_opts $ivector_opts $frame_subsampling_opt \ --frames-per-chunk=$frames_per_chunk \ --extra-left-context=$extra_left_context \ --extra-right-context=$extra_right_context \ --extra-left-context-initial=$extra_left_context_initial \ --extra-right-context-final=$extra_right_context_final \ $gpu_opt --beam=$beam --retry-beam=$retry_beam \ $srcdir/${iter}.mdl ark:- "$feats" "ark:|gzip -c >$dir/ali.JOB.gz" || exit 1; steps/diagnostic/analyze_alignments.sh --cmd "$cmd" $lang $dir echo "$0: done aligning data." |