#!/bin/bash # Copyright 2012 Johns Hopkins University (Author: Daniel Povey) # Apache 2.0 # Decode, limited to the word-sequences that were present in a set # of lattices on disk. The other lattices do not have to be built # with the same tree or the same context size-- however, you do # have to be using the same vocabulary (words.txt)-- if not you'd # have to map the vocabulary somehow. # Note: if the trees are identical, you can use gmm-rescore-lattice. # Mechanism: create an unweighted acceptor (on words) for each utterance, # compose that with G, determinize, and then use compile-train-graphs-fsts # to compile a graph for each utterance, to decode with. # Begin configuration. cmd=run.pl maxactive=7000 beam=20.0 latbeam=7.0 acwt=0.083333 batch_size=75 # Limits memory blowup in compile-train-graphs-fsts scale_opts="--transition-scale=1.0 --self-loop-scale=0.1" # End configuration. 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: steps/decode_si_fromlats.sh [options] " echo "e.g.: steps/decode_si_fromlats.sh data/test_dev93 data/lang_test_tg exp/tri2b/decode_tgpr_dev93 exp/tri2a/decode_tgpr_dev93_fromlats" echo "" echo "main options (for others, see top of script file)" echo " --config # config containing options" echo " --cmd (utils/run.pl|utils/queue.pl ) # how to run jobs." exit 1; fi data=$1 lang=$2 olddir=$3 dir=$4 srcdir=`dirname $dir`; # Assume model directory one level up from decoding directory. mkdir -p $dir/log nj=`cat $olddir/num_jobs` || exit 1; splice_opts=`cat $srcdir/splice_opts 2>/dev/null` sdata=$data/split$nj [[ -d $sdata && $data/feats.scp -ot $sdata ]] || split_data.sh $data $nj || exit 1; echo $nj >$dir/num_jobs for f in $sdata/1/feats.scp $sdata/1/cmvn.scp $srcdir/final.mdl $olddir/lat.1.gz \ $srcdir/tree $lang/L_disambig.fst $lang/phones.txt; do [ ! -f $f ] && echo "decode_si_fromlats.sh: no such file $f" && exit 1; done if [ -f $srcdir/final.mat ]; then feat_type=lda; else feat_type=delta; fi echo "decode_si.sh: feature type is $feat_type" case $feat_type in delta) feats="ark,s,cs:apply-cmvn --norm-vars=false --utt2spk=ark:$sdata/JOB/utt2spk scp:$sdata/JOB/cmvn.scp scp:$sdata/JOB/feats.scp ark:- | add-deltas ark:- ark:- |";; lda) feats="ark,s,cs:apply-cmvn --norm-vars=false --utt2spk=ark:$sdata/JOB/utt2spk scp:$sdata/JOB/cmvn.scp scp:$sdata/JOB/feats.scp ark:- | splice-feats $splice_opts ark:- ark:- | transform-feats $srcdir/final.mat ark:- ark:- |";; *) echo "Invalid feature type $feat_type" && exit 1; esac $cmd JOB=1:$nj $dir/log/decode_lats.JOB.log \ lattice-to-fst "ark:gunzip -c $olddir/lat.JOB.gz|" ark:- \| \ fsttablecompose "fstproject --project_output=true $lang/G.fst | fstarcsort |" ark:- ark:- \| \ fstdeterminizestar ark:- ark:- \| \ compile-train-graphs-fsts --read-disambig-syms=$lang/phones/disambig.int \ --batch-size=$batch_size $scale_opts $srcdir/tree $srcdir/final.mdl $lang/L_disambig.fst ark:- ark:- \| \ gmm-latgen-faster --max-active=$maxactive --beam=$beam --lattice-beam=$latbeam --acoustic-scale=$acwt \ --allow-partial=true --word-symbol-table=$lang/words.txt \ $srcdir/final.mdl ark:- "$feats" "ark:|gzip -c > $dir/lat.JOB.gz" || exit 1; [ ! -x local/score.sh ] && \ echo "Not scoring because local/score.sh does not exist or not executable." && exit 1; local/score.sh --cmd "$cmd" $data $lang $dir exit 0;