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egs/wsj/s5/steps/tandem/train_sat.sh
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#!/bin/bash # Copyright 2012 Johns Hopkins University (Author: Daniel Povey). Apache 2.0. # Korbinian Riedhammer # This does Speaker Adapted Training (SAT), i.e. train on # fMLLR-adapted features. It can be done on top of either LDA+MLLT, or # delta and delta-delta features. If there are no transforms supplied # in the alignment directory, it will estimate transforms itself before # building the tree (and in any case, it estimates transforms a number # of times during training). # Begin configuration section. stage=-5 fmllr_update_type=full cmd=run.pl 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 likelihoods in alignment realign_iters="10 20 30"; fmllr_iters="2 4 6 12"; silence_weight=0.0 # Weight on silence in fMLLR estimation. num_iters=35 # Number of iterations of training max_iter_inc=25 # Last iter to increase #Gauss on. power=0.2 # Exponent for number of gaussians according to occurrence counts cluster_thresh=-1 # for build-tree control final bottom-up clustering of leaves normft2=true # End configuration section. echo "$0 $@" # Print the command line for logging [ -f path.sh ] && . ./path.sh . parse_options.sh || exit 1; if [ $# != 7 ]; then echo "Usage: steps/tandem/train_sat.sh <#leaves> <#gauss> <data1> <data2> <lang> <ali-dir> <exp-dir>" echo " e.g.: steps/tandem/train_sat.sh 2500 15000 {mfcc,bottleneck}/data/train_si84 data/lang exp/tri2b_ali_si84 exp/tri3b" echo "Main options (for others, see top of script file)" echo " --cmd (utils/run.pl|utils/queue.pl <queue opts>) # how to run jobs." echo " --config <config-file> # config containing options" echo " --stage <stage> # stage to do partial re-run from." exit 1; fi numleaves=$1 totgauss=$2 data1=$3 data2=$4 lang=$5 alidir=$6 dir=$7 for f in $data1/feats.scp $data2/feats.scp $lang/phones.txt $alidir/final.mdl $alidir/ali.1.gz; do [ ! -f $f ] && echo "train_tandem_sat.sh: no such file $f" && exit 1; done numgauss=$numleaves incgauss=$[($totgauss-$numgauss)/$max_iter_inc] # per-iter #gauss increment oov=`cat $lang/oov.int` nj=`cat $alidir/num_jobs` || exit 1; silphonelist=`cat $lang/phones/silence.csl` ciphonelist=`cat $lang/phones/context_indep.csl` || exit 1; mkdir -p $dir/log utils/lang/check_phones_compatible.sh $lang/phones.txt $alidir/phones.txt || exit 1; cp $lang/phones.txt $dir || exit 1; echo $nj >$dir/num_jobs 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; # Set up features. # We will use the same settings as with the alidir splice_opts=`cat $alidir/splice_opts 2>/dev/null` # frame-splicing options. normft2=`cat $alidir/normft2 2>/dev/null` if [ -f $alidir/final.mat ]; then feat_type=lda; else feat_type=delta; fi case $feat_type in delta) echo "$0: feature type is $feat_type" ;; lda) echo "$0: feature type is $feat_type" cp $alidir/{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 $feats2 ark:- |" fi # assemble tandem features sifeats="ark,s,cs:paste-feats '$feats1' '$feats2' ark:- |" # add transformation, if applicable if [ "$feat_type" == "lda" ]; then sifeats="$sifeats transform-feats $dir/final.mat ark:- ark:- |" fi # splicing/normalization options cp $alidir/{splice_opts,tandem,normft2} $dir 2>/dev/null ## Get initial fMLLR transforms (possibly from alignment dir) if [ -f $alidir/trans.1 ]; then echo "$0: Using transforms from $alidir" feats="$sifeats transform-feats --utt2spk=ark:$sdata1/JOB/utt2spk ark,s,cs:$alidir/trans.JOB ark:- ark:- |" cur_trans_dir=$alidir else if [ $stage -le -4 ]; then echo "$0: obtaining initial fMLLR transforms since not present in $alidir" $cmd JOB=1:$nj $dir/log/fmllr.0.JOB.log \ ali-to-post "ark:gunzip -c $alidir/ali.JOB.gz|" ark:- \| \ weight-silence-post $silence_weight $silphonelist $alidir/final.mdl ark:- ark:- \| \ gmm-est-fmllr --fmllr-update-type=$fmllr_update_type \ --spk2utt=ark:$sdata1/JOB/spk2utt $alidir/final.mdl "$sifeats" \ ark:- ark:$dir/trans.JOB || exit 1; fi feats="$sifeats transform-feats --utt2spk=ark:$sdata1/JOB/utt2spk ark,s,cs:$dir/trans.JOB ark:- ark:- |" cur_trans_dir=$dir fi if [ $stage -le -3 ]; then # Get tree stats. echo "$0: Accumulating tree stats" $cmd JOB=1:$nj $dir/log/acc_tree.JOB.log \ acc-tree-stats --ci-phones=$ciphonelist $alidir/final.mdl "$feats" \ "ark:gunzip -c $alidir/ali.JOB.gz|" $dir/JOB.treeacc || exit 1; [ "`ls $dir/*.treeacc | wc -w`" -ne "$nj" ] && echo "$0: Wrong #tree-accs" && exit 1; $cmd $dir/log/sum_tree_acc.log \ sum-tree-stats $dir/treeacc $dir/*.treeacc || exit 1; rm $dir/*.treeacc fi if [ $stage -le -2 ]; then echo "$0: Getting questions for tree clustering." # preparing questions, roots file... cluster-phones $dir/treeacc $lang/phones/sets.int $dir/questions.int 2> $dir/log/questions.log || exit 1; cat $lang/phones/extra_questions.int >> $dir/questions.int compile-questions $lang/topo $dir/questions.int $dir/questions.qst 2>$dir/log/compile_questions.log || exit 1; echo "$0: Building the tree" $cmd $dir/log/build_tree.log \ build-tree --verbose=1 --max-leaves=$numleaves \ --cluster-thresh=$cluster_thresh $dir/treeacc $lang/phones/roots.int \ $dir/questions.qst $lang/topo $dir/tree || exit 1; gmm-init-model --write-occs=$dir/1.occs \ $dir/tree $dir/treeacc $lang/topo $dir/1.mdl 2> $dir/log/init_model.log || exit 1; grep 'no stats' $dir/log/init_model.log && echo "$0: This is a bad warning."; rm $dir/treeacc fi if [ $stage -le -1 ]; then # Convert the alignments. echo "$0: Converting alignments from $alidir to use current tree" $cmd JOB=1:$nj $dir/log/convert.JOB.log \ convert-ali $alidir/final.mdl $dir/1.mdl $dir/tree \ "ark:gunzip -c $alidir/ali.JOB.gz|" "ark:|gzip -c >$dir/ali.JOB.gz" || exit 1; fi if [ $stage -le 0 ]; then echo "$0: Compiling graphs of transcripts" $cmd JOB=1:$nj $dir/log/compile_graphs.JOB.log \ compile-train-graphs --read-disambig-syms=$lang/phones/disambig.int $dir/tree $dir/1.mdl $lang/L.fst \ "ark:utils/sym2int.pl --map-oov $oov -f 2- $lang/words.txt < $sdata1/JOB/text |" \ "ark:|gzip -c >$dir/fsts.JOB.gz" || exit 1; fi x=1 while [ $x -lt $num_iters ]; do echo Pass $x if echo $realign_iters | grep -w $x >/dev/null && [ $stage -le $x ]; then echo Aligning data mdl="gmm-boost-silence --boost=$boost_silence `cat $lang/phones/optional_silence.csl` $dir/$x.mdl - |" $cmd JOB=1:$nj $dir/log/align.$x.JOB.log \ gmm-align-compiled $scale_opts --beam=$beam --retry-beam=$retry_beam "$mdl" \ "ark:gunzip -c $dir/fsts.JOB.gz|" "$feats" \ "ark:|gzip -c >$dir/ali.JOB.gz" || exit 1; fi if echo $fmllr_iters | grep -w $x >/dev/null; then if [ $stage -le $x ]; then echo Estimating fMLLR transforms # We estimate a transform that's additional to the previous transform; # we'll compose them. $cmd JOB=1:$nj $dir/log/fmllr.$x.JOB.log \ ali-to-post "ark:gunzip -c $dir/ali.JOB.gz|" ark:- \| \ weight-silence-post $silence_weight $silphonelist $dir/$x.mdl ark:- ark:- \| \ gmm-est-fmllr --fmllr-update-type=$fmllr_update_type \ --spk2utt=ark:$sdata1/JOB/spk2utt $dir/$x.mdl \ "$feats" ark:- ark:$dir/tmp_trans.JOB || exit 1; for n in `seq $nj`; do ! ( compose-transforms --b-is-affine=true \ ark:$dir/tmp_trans.$n ark:$cur_trans_dir/trans.$n ark:$dir/composed_trans.$n \ && mv $dir/composed_trans.$n $dir/trans.$n && \ rm $dir/tmp_trans.$n ) 2>$dir/log/compose_transforms.$x.log \ && echo "$0: Error composing transforms" && exit 1; done fi feats="$sifeats transform-feats --utt2spk=ark:$sdata1/JOB/utt2spk ark:$dir/trans.JOB ark:- ark:- |" cur_trans_dir=$dir fi if [ $stage -le $x ]; then $cmd JOB=1:$nj $dir/log/acc.$x.JOB.log \ gmm-acc-stats-ali $dir/$x.mdl "$feats" \ "ark,s,cs:gunzip -c $dir/ali.JOB.gz|" $dir/$x.JOB.acc || exit 1; [ `ls $dir/$x.*.acc | wc -w` -ne "$nj" ] && echo "$0: Wrong #accs" && exit 1; $cmd $dir/log/update.$x.log \ gmm-est --power=$power --write-occs=$dir/$[$x+1].occs --mix-up=$numgauss $dir/$x.mdl \ "gmm-sum-accs - $dir/$x.*.acc |" $dir/$[$x+1].mdl || exit 1; rm $dir/$x.mdl $dir/$x.*.acc rm $dir/$x.occs fi [ $x -le $max_iter_inc ] && numgauss=$[$numgauss+$incgauss]; x=$[$x+1]; done if [ $stage -le $x ]; then # Accumulate stats for "alignment model"-- this model is # computed with the speaker-independent features, but matches Gaussian-for-Gaussian # with the final speaker-adapted model. $cmd JOB=1:$nj $dir/log/acc_alimdl.JOB.log \ ali-to-post "ark:gunzip -c $dir/ali.JOB.gz|" ark:- \| \ gmm-acc-stats-twofeats $dir/$x.mdl "$feats" "$sifeats" \ ark,s,cs:- $dir/$x.JOB.acc || exit 1; [ `ls $dir/$x.*.acc | wc -w` -ne "$nj" ] && echo "$0: Wrong #accs" && exit 1; # Update model. $cmd $dir/log/est_alimdl.log \ gmm-est --power=$power --remove-low-count-gaussians=false $dir/$x.mdl \ "gmm-sum-accs - $dir/$x.*.acc|" $dir/$x.alimdl || exit 1; rm $dir/$x.*.acc fi rm $dir/final.{mdl,alimdl,occs} 2>/dev/null ln -s $x.mdl $dir/final.mdl ln -s $x.occs $dir/final.occs ln -s $x.alimdl $dir/final.alimdl utils/summarize_warnings.pl $dir/log ( echo "$0: Likelihood evolution:" for x in `seq $[$num_iters-1]`; do tail -n 30 $dir/log/acc.$x.*.log | awk '/Overall avg like/{l += $(NF-3)*$(NF-1); t += $(NF-1); } /Overall average logdet/{d += $(NF-3)*$(NF-1); t2 += $(NF-1);} END{ d /= t2; l /= t; printf("%s ", d+l); } ' done echo ) | tee $dir/log/summary.log echo Done |