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egs/wsj/s5/steps/tandem/align_si.sh
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#!/bin/bash # Copyright 2012 Johns Hopkins University (Author: Daniel Povey) # Korbinian Riedhammer # Apache 2.0 # Computes training alignments using a model with delta or # LDA+MLLT features. # If you supply the "--use-graphs true" option, it will use the training # graphs from the source directory (where the model is). In this # case the number of jobs must match with the source directory. # Begin configuration section. nj=4 cmd=run.pl use_graphs=false # Begin configuration. scale_opts="--transition-scale=1.0 --acoustic-scale=0.1 --self-loop-scale=0.1" beam=10 retry_beam=40 boost_silence=1.0 # Factor by which to boost silence during alignment. # 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 [ $# != 5 ]; then echo "usage: steps/tandem/align_si.sh <data1-dir> <data2-dir> <lang-dir> <src-dir> <align-dir>" echo "e.g.: steps/tandem/align_si.sh {mfcc,bottleneck}/data/train data/lang exp/tri1 exp/tri1_ali" 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 " --use-graphs true # use graphs in src-dir" echo " --cmd (utils/run.pl|utils/queue.pl <queue opts>) # how to run jobs." exit 1; fi data1=$1 data2=$2 lang=$3 srcdir=$4 dir=$5 oov=`cat $lang/oov.int` || exit 1; mkdir -p $dir/log echo $nj > $dir/num_jobs utils/lang/check_phones_compatible.sh $lang/phones.txt $srcdir/phones.txt || exit 1; cp $lang/phones.txt $dir || exit 1; # Set up the features sdata1=$data1/split$nj sdata2=$data2/split$nj [[ -d $sdata1 && $data1/feats.scp -ot $sdata1 ]] || split_data.sh $data1 $nj || exit 1; [[ -d $sdata2 && $data2/feats.scp -ot $sdata2 ]] || split_data.sh $data2 $nj || exit 1; cp $srcdir/{tree,final.mdl} $dir || exit 1; cp $srcdir/final.occs $dir; # Get some info on the feature types splice_opts=`cat $srcdir/splice_opts 2>/dev/null` # frame-splicing options. normft2=`cat $srcdir/normft2 2>/dev/null` || exit 1; if [ -f $srcdir/final.mat ]; then feat_type=lda; else feat_type=delta; fi # for lda-type features, we need to copy both the lda (for baseft) and mllt # transformation (for the pasted features) case $feat_type in delta) echo "$0: feature type is $feat_type" ;; lda) echo "$0: feature type is $feat_type" cp $srcdir/{lda,final}.mat $dir/ || exit 1; ;; *) echo "$0: invalid feature type $feat_type" && exit 1; esac # set up feature stream 1; this are usually spectral features, so we will add # deltas or splice them feats1="ark,s,cs:apply-cmvn --norm-vars=false --utt2spk=ark:$sdata1/JOB/utt2spk scp:$sdata1/JOB/cmvn.scp scp:$sdata1/JOB/feats.scp ark:- |" if [ "$feat_type" == "delta" ]; then feats1="$feats1 add-deltas ark:- ark:- |" elif [ "$feat_type" == "lda" ]; then feats1="$feats1 splice-feats $splice_opts ark:- ark:- | transform-feats $dir/lda.mat ark:- ark:- |" fi # set up feature stream 2; this are usually bottleneck or posterior features, # which may be normalized if desired feats2="scp:$sdata2/JOB/feats.scp" if [ "$normft2" == "true" ]; then feats2="ark,s,cs:apply-cmvn --norm-vars=false --utt2spk=ark:$sdata2/JOB/utt2spk scp:$sdata2/JOB/cmvn.scp $feats2 ark:- |" fi # assemble tandem features feats="ark,s,cs:paste-feats '$feats1' '$feats2' ark:- |" # add transformation, if applicable if [ "$feat_type" == "lda" ]; then feats="$feats transform-feats $dir/final.mat ark:- ark:- |" fi # splicing/normalization options cp $srcdir/{tandem,splice_opts,normft2} $dir 2>/dev/null echo "$0: aligning data in $data using model from $srcdir, putting alignments in $dir" mdl="gmm-boost-silence --boost=$boost_silence `cat $lang/phones/optional_silence.csl` $dir/final.mdl - |" if $use_graphs; then [ $nj != "`cat $srcdir/num_jobs`" ] && echo "$0: mismatch in num-jobs" && exit 1; [ ! -f $srcdir/fsts.1.gz ] && echo "$0: no such file $srcdir/fsts.1.gz" && exit 1; $cmd JOB=1:$nj $dir/log/align.JOB.log \ gmm-align-compiled $scale_opts --beam=$beam --retry-beam=$retry_beam "$mdl" \ "ark:gunzip -c $srcdir/fsts.JOB.gz|" "$feats" "ark:|gzip -c >$dir/ali.JOB.gz" || exit 1; else tra="ark:utils/sym2int.pl --map-oov $oov -f 2- $lang/words.txt $sdata1/JOB/text|"; # We could just use gmm-align in the next line, but it's less efficient as it compiles the # training graphs one by one. $cmd JOB=1:$nj $dir/log/align.JOB.log \ compile-train-graphs --read-disambig-syms=$lang/phones/disambig.int $dir/tree $dir/final.mdl $lang/L.fst "$tra" ark:- \| \ gmm-align-compiled $scale_opts --beam=$beam --retry-beam=$retry_beam "$mdl" ark:- \ "$feats" "ark,t:|gzip -c >$dir/ali.JOB.gz" || exit 1; fi echo "$0: done aligning data." |