decode_segmentation_nnet3.sh
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#!/bin/bash
# Copyright 2014 Guoguo Chen, 2015 GoVivace Inc. (Nagendra Goel)
# 2017 Vimal Manohar
# Apache 2.0
# This script is similar to steps/cleanup/decode_segmentation.sh, but
# does decoding using nnet3 model.
set -e
set -o pipefail
# Begin configuration section.
stage=-1
nj=4 # number of decoding jobs.
acwt=0.1 # Just a default value, used for adaptation and beam-pruning..
post_decode_acwt=1.0 # can be used in 'chain' systems to scale acoustics by 10 so the
# regular scoring script works.
cmd=run.pl
beam=15.0
frames_per_chunk=50
max_active=7000
min_active=200
ivector_scale=1.0
lattice_beam=8.0 # Beam we use in lattice generation. We can reduce this if
# we only need the best path
iter=final
num_threads=1 # if >1, will use gmm-latgen-faster-parallel
scoring_opts=
skip_scoring=false
allow_partial=true
extra_left_context=0
extra_right_context=0
extra_left_context_initial=-1
extra_right_context_final=-1
online_ivector_dir=
minimize=false
# End configuration section.
echo "$0 $@" # Print the command line for logging
[ -f ./path.sh ] && . ./path.sh; # source the path.
. utils/parse_options.sh || exit 1;
if [ $# -ne 3 ]; then
echo "$0: This is a special decoding script for segmentation where we"
echo "use one decoding graph per segment. We assume a file HCLG.fsts.scp exists"
echo "which is the scp file of the graphs for each segment."
echo "This will normally be obtained by steps/cleanup/make_biased_lm_graphs.sh."
echo ""
echo "Usage: $0 [options] <graph-dir> <data-dir> <decode-dir>"
echo " e.g.: $0 --online-ivector-dir exp/nnet3/ivectors_train_si284_split "
echo " exp/nnet3/tdnn/graph_train_si284_split \\"
echo " data/train_si284_split exp/nnet3/tdnn/decode_train_si284_split"
echo ""
echo "where <decode-dir> is assumed to be a sub-directory of the directory"
echo "where the model is."
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 " --iter <iter> # Iteration of model to test."
echo " --cmd (utils/run.pl|utils/queue.pl <queue opts>) # how to run jobs."
echo " --acwt <float> # acoustic scale used for lattice generation "
echo " --scoring-opts <string> # options to local/score.sh"
echo " --num-threads <n> # number of threads to use, default 1."
exit 1;
fi
graphdir=$1
data=$2
dir=$3
mkdir -p $dir/log
if [ -e $dir/$iter.mdl ]; then
srcdir=$dir
elif [ -e $dir/../$iter.mdl ]; then
srcdir=$(dirname $dir)
else
echo "$0: expected either $dir/$iter.mdl or $dir/../$iter.mdl to exist"
exit 1
fi
model=$srcdir/$iter.mdl
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
utils/lang/check_phones_compatible.sh $graph_dir/phones.txt $srcdir/phones.txt || exit 1
for f in $graphdir/HCLG.fsts.scp $data/feats.scp $model $extra_files; do
[ ! -f $f ] && echo "$0: no such file $f" && exit 1;
done
sdata=$data/split$nj;
cmvn_opts=`cat $srcdir/cmvn_opts` || exit 1;
thread_string=
[ $num_threads -gt 1 ] && thread_string="-parallel --num-threads=$num_threads"
mkdir -p $dir/log
[[ -d $sdata && $data/feats.scp -ot $sdata ]] || split_data.sh $data $nj || exit 1;
echo $nj > $dir/num_jobs
# Split HCLG.fsts.scp by input utterance
n1=$(cat $graphdir/HCLG.fsts.scp | wc -l)
n2=$(cat $data/feats.scp | wc -l)
if [ $n1 != $n2 ]; then
echo "$0: expected $n2 graphs in $graphdir/HCLG.fsts.scp, got $n1"
fi
mkdir -p $dir/split_fsts
sort -k1,1 $graphdir/HCLG.fsts.scp > $dir/HCLG.fsts.sorted.scp
utils/filter_scps.pl --no-warn -f 1 JOB=1:$nj \
$sdata/JOB/feats.scp $dir/HCLG.fsts.sorted.scp $dir/split_fsts/HCLG.fsts.JOB.scp
HCLG=scp:$dir/split_fsts/HCLG.fsts.JOB.scp
## Set up features.
echo "$0: feature type is raw"
feats="ark,s,cs:apply-cmvn $cmvn_opts --utt2spk=ark:$sdata/JOB/utt2spk scp:$sdata/JOB/cmvn.scp scp:$sdata/JOB/feats.scp ark:- |"
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=$ivector_period"
fi
if [ "$post_decode_acwt" == 1.0 ]; then
lat_wspecifier="ark:|gzip -c >$dir/lat.JOB.gz"
else
lat_wspecifier="ark:|lattice-scale --acoustic-scale=$post_decode_acwt ark:- ark:- | gzip -c >$dir/lat.JOB.gz"
fi
frame_subsampling_opt=
if [ -f $srcdir/frame_subsampling_factor ]; then
# e.g. for 'chain' systems
frame_subsampling_opt="--frame-subsampling-factor=$(cat $srcdir/frame_subsampling_factor)"
fi
if [ $stage -le 1 ]; then
if [ -f "$graphdir/num_pdfs" ]; then
[ "`cat $graphdir/num_pdfs`" -eq `am-info --print-args=false $model | grep pdfs | awk '{print $NF}'` ] || \
{ echo "Mismatch in number of pdfs with $model"; exit 1; }
fi
$cmd --num-threads $num_threads JOB=1:$nj $dir/log/decode.JOB.log \
nnet3-latgen-faster$thread_string $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 \
--minimize=$minimize --max-active=$max_active --min-active=$min_active --beam=$beam \
--lattice-beam=$lattice_beam --acoustic-scale=$acwt --allow-partial=$allow_partial \
--word-symbol-table=$graphdir/words.txt "$model" \
"$HCLG" "$feats" "$lat_wspecifier" || exit 1;
fi
if [ $stage -le 2 ]; then
if ! $skip_scoring ; then
[ ! -x local/score.sh ] && \
echo "$0: Not scoring because local/score.sh does not exist or not executable." && exit 1;
iter_opt=
[ "$iter" != "final" ] && iter_opt="--iter $iter"
local/score.sh $iter_opt $scoring_opts --cmd "$cmd" $data $graphdir $dir ||
{ echo "$0: Scoring failed. (ignore by '--skip-scoring true')"; exit 1; }
fi
fi
echo "Decoding done."
exit 0;