decode_fmmi.sh.svn-base
4.86 KB
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
104
105
106
107
108
109
110
111
#!/bin/bash
# Copyright 2012 Johns Hopkins University (Author: Daniel Povey)
# Apache 2.0
# Decoding of fMMI or fMPE models (feature-space discriminative training).
# If transform-dir supplied, expects e.g. fMLLR transforms in that dir.
# Begin configuration section.
stage=1
iter=final
nj=4
cmd=run.pl
maxactive=7000
beam=13.0
latbeam=6.0
acwt=0.083333 # note: only really affects pruning (scoring is on lattices).
ngselect=2; # Just use the 2 top Gaussians for fMMI/fMPE. Should match train.
transform_dir=
num_threads=1 # if >1, will use gmm-latgen-faster-parallel
parallel_opts= # If you supply num-threads, you should supply this too.
scoring_opts=
# End configuration section.
echo "$0 $@" # Print the command line for logging
[ -f ./path.sh ] && . ./path.sh; # source the path.
. parse_options.sh || exit 1;
if [ $# != 3 ]; then
echo "Usage: steps/decode_fmmi.sh [options] <graph-dir> <data-dir> <decode-dir>"
echo "... where <decode-dir> is assumed to be a sub-directory of the directory"
echo " where the model is."
echo "e.g.: steps/decode_fmmi.sh exp/mono/graph_tgpr data/test_dev93 exp/mono/decode_dev93_tgpr"
echo ""
echo "This script works on CMN + (delta+delta-delta | LDA+MLLT) features; it works out"
echo "what type of features you used (assuming it's one of these two)"
echo "You can also use fMLLR features-- you have to supply --transform-dir option."
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 " --transform-dir <transform-dir> # where to find fMLLR transforms."
echo " --scoring-opts <string> # options to local/score.sh"
echo " # speaker-adapted decoding"
echo " --num-threads <n> # number of threads to use, default 1."
echo " --parallel-opts <opts> # e.g. '-pe smp 4' if you supply --num-threads 4"
exit 1;
fi
graphdir=$1
data=$2
dir=$3
srcdir=`dirname $dir`; # The model directory is one level up from decoding directory.
sdata=$data/split$nj;
splice_opts=`cat $srcdir/splice_opts 2>/dev/null`
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 > $dir/num_jobs
model=$srcdir/$iter.mdl
for f in $sdata/1/feats.scp $sdata/1/cmvn.scp $model $graphdir/HCLG.fst; do
[ ! -f $f ] && echo "decode_fmmi.sh: no such file $f" && exit 1;
done
if [ -f $srcdir/final.mat ]; then feat_type=lda; else feat_type=delta; fi
echo "decode_fmmi.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 $feat_type" && exit 1;
esac
if [ ! -z "$transform_dir" ]; then # add transforms to features...
echo "Using fMLLR transforms from $transform_dir"
[ ! -f $transform_dir/trans.1 ] && echo "Expected $transform_dir/trans.1 to exist."
[ "`cat $transform_dir/num_jobs`" -ne $nj ] && \
echo "Mismatch in number of jobs with $transform_dir";
feats="$feats transform-feats --utt2spk=ark:$sdata/JOB/utt2spk ark:$transform_dir/trans.JOB ark:- ark:- |"
fi
fmpefeats="$feats fmpe-apply-transform $srcdir/$iter.fmpe ark:- 'ark,s,cs:gunzip -c $dir/gselect.JOB.gz|' ark:- |"
if [ $stage -le 1 ]; then
# Get Gaussian selection info.
$cmd JOB=1:$nj $dir/log/gselect.JOB.log \
gmm-gselect --n=$ngselect $srcdir/$iter.fmpe "$feats" \
"ark:|gzip -c >$dir/gselect.JOB.gz" || exit 1;
fi
if [ $stage -le 2 ]; then
$cmd $parallel_opts JOB=1:$nj $dir/log/decode.JOB.log \
gmm-latgen-faster$thread_string --max-active=$maxactive --beam=$beam --lattice-beam=$latbeam \
--acoustic-scale=$acwt --allow-partial=true --word-symbol-table=$graphdir/words.txt \
$model $graphdir/HCLG.fst "$fmpefeats" "ark:|gzip -c > $dir/lat.JOB.gz" || exit 1;
fi
if [ $stage -le 3 ]; then
[ ! -x local/score.sh ] && \
echo "Not scoring because local/score.sh does not exist or not executable." && exit 1;
local/score.sh $scoring_opts --cmd "$cmd" $data $graphdir $dir
fi
exit 0;