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egs/wsj/s5/steps/tandem/train_mono.sh
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#!/bin/bash # Copyright 2012 Johns Hopkins University (Author: Daniel Povey) # Korbinian Riedhammer # Apache 2.0 # To be run from .. # Flat start and monophone training, with delta-delta features. # This script applies cepstral mean normalization (per speaker). # Begin configuration section. nj=4 cmd=run.pl scale_opts="--transition-scale=1.0 --acoustic-scale=0.1 --self-loop-scale=0.1" num_iters=40 # Number of iterations of training max_iter_inc=30 # Last iter to increase #Gauss on. totgauss=1000 # Target #Gaussians. boost_silence=1.0 # Factor by which to boost silence likelihoods in alignment realign_iters="1 2 3 4 5 6 7 8 9 10 12 14 16 18 20 23 26 29 32 35 38"; config= # name of config file. stage=-4 power=0.2 # exponent to determine number of gaussians from occurrence counts normft2=true # typically, the tandem features will already be normalized due to pca # End configuration section. echo "$0 $@" # Print the command line for logging if [ -f path.sh ]; then . ./path.sh; fi . parse_options.sh || exit 1; if [ $# != 4 ]; then echo "Usage: steps/tandem/train_mono.sh [options] <data1-dir> <data2-dir> <lang-dir> <exp-dir>" echo " e.g.: steps/tandem/train_mono.sh {mfcc,bottleneck}/data/train.1k data/lang exp/mono" 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." echo " --normft2 (true|false) # apply CMVN to second features?" exit 1; fi data1=$1 data2=$2 lang=$3 dir=$4 oov_sym=`cat $lang/oov.int` || exit 1; mkdir -p $dir/log echo $nj > $dir/num_jobs cp $lang/phones.txt $dir || exit 1; # Set up features. sdata1=$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 $nj || exit 1; # Use deltas on the first tream (most likely this will be MFCCs or alike) feats1="ark,s,cs:apply-cmvn --norm-vars=false --utt2spk=ark:$sdata1/JOB/utt2spk scp:$sdata1/JOB/cmvn.scp scp:$sdata1/JOB/feats.scp ark:- | add-deltas ark:- ark:- |" # Second stream will most likely be bottleneck or posteriors, so normalize # 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 $feats2 ark:- |" fi # paste features feats="ark,s,cs:paste-feats '$feats1' '$feats2' ark:- |" example_feats="`echo '$feats' | sed s/JOB/1/g`"; # get dimension allfeats=$(echo $feats | sed s:JOB:..:g) feat_dim=$(feat-to-dim --print-args=false "$allfeats" - 2> $dir/log/feat_dim) # save stats echo $feats > $dir/tandem echo $normft2 > $dir/normft2 echo "$0: Initializing monophone system." [ ! -f $lang/phones/sets.int ] && exit 1; shared_phones_opt="--shared-phones=$lang/phones/sets.int" if [ $stage -le -3 ]; then # Note: JOB=. makes it use the whole set; we want that to make sure we have phoneme $cmd JOB=1 $dir/log/init.log \ gmm-init-mono $shared_phones_opt "--train-feats=$allfeats" $lang/topo $feat_dim \ $dir/0.mdl $dir/tree || exit 1; fi numgauss=`gmm-info --print-args=false $dir/0.mdl | grep gaussians | awk '{print $NF}'` incgauss=$[($totgauss-$numgauss)/$max_iter_inc] # per-iter increment for #Gauss if [ $stage -le -2 ]; then echo "$0: Compiling training graphs" $cmd JOB=1:$nj $dir/log/compile_graphs.JOB.log \ compile-train-graphs --read-disambig-syms=$lang/phones/disambig.int $dir/tree $dir/0.mdl $lang/L.fst \ "ark:sym2int.pl --map-oov $oov_sym -f 2- $lang/words.txt < $sdata1/JOB/text|" \ "ark:|gzip -c >$dir/fsts.JOB.gz" || exit 1; fi if [ $stage -le -1 ]; then echo "$0: Aligning data equally (pass 0)" $cmd JOB=1:$nj $dir/log/align.0.JOB.log \ align-equal-compiled "ark:gunzip -c $dir/fsts.JOB.gz|" "$feats" ark,t:- \| \ gmm-acc-stats-ali --binary=true $dir/0.mdl "$feats" ark:- \ $dir/0.JOB.acc || exit 1; fi # In the following steps, the --min-gaussian-occupancy=3 option is important, otherwise # we fail to est "rare" phones and later on, they never align properly. if [ $stage -le 0 ]; then gmm-est --min-gaussian-occupancy=3 --mix-up=$numgauss --power=$power \ $dir/0.mdl "gmm-sum-accs - $dir/0.*.acc|" $dir/1.mdl 2> $dir/log/update.0.log || exit 1; rm $dir/0.*.acc fi beam=6 # will change to 10 below after 1st pass # note: using slightly wider beams for WSJ vs. RM. x=1 while [ $x -lt $num_iters ]; do echo "$0: Pass $x" if [ $stage -le $x ]; then if echo $realign_iters | grep -w $x >/dev/null; then echo "$0: Aligning data" mdl="gmm-boost-silence --boost=$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=$[$beam*4] "$mdl" \ "ark:gunzip -c $dir/fsts.JOB.gz|" "$feats" "ark,t:|gzip -c >$dir/ali.JOB.gz" \ || exit 1; fi $cmd JOB=1:$nj $dir/log/acc.$x.JOB.log \ gmm-acc-stats-ali $dir/$x.mdl "$feats" "ark:gunzip -c $dir/ali.JOB.gz|" \ $dir/$x.JOB.acc || exit 1; $cmd $dir/log/update.$x.log \ gmm-est --write-occs=$dir/$[$x+1].occs --mix-up=$numgauss --power=$power $dir/$x.mdl \ "gmm-sum-accs - $dir/$x.*.acc|" $dir/$[$x+1].mdl || exit 1; rm $dir/$x.mdl $dir/$x.*.acc $dir/$x.occs 2>/dev/null fi if [ $x -le $max_iter_inc ]; then numgauss=$[$numgauss+$incgauss]; fi beam=10 x=$[$x+1] done ( cd $dir; rm final.{mdl,occs} 2>/dev/null; ln -s $x.mdl final.mdl; ln -s $x.occs final.occs ) utils/summarize_warnings.pl $dir/log echo "Done training tandem mono-phone system in $dir" # example of showing the alignments: # show-alignments data/lang/phones.txt $dir/30.mdl "ark:gunzip -c $dir/ali.0.gz|" | head -4 |