train_ubm.sh
5.32 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
112
113
114
115
116
117
118
119
120
121
122
123
124
125
126
127
128
129
130
131
132
133
134
135
136
137
138
139
#!/bin/bash
# Copyright 2012 Johns Hopkins University (Author: Daniel Povey). Apache 2.0.
# This trains a UBM (i.e. a mixture of Gaussians), by clustering
# the Gaussians from a trained HMM/GMM system and then doing a few
# iterations of UBM training.
# We mostly use this for SGMM systems.
# Begin configuration section.
nj=4
cmd=run.pl
silence_weight= # You can set it to e.g. 0.0, to weight down silence in training.
stage=-2
num_gselect1=50 # first stage of Gaussian-selection
num_gselect2=25 # second stage.
intermediate_num_gauss=2000
num_iters=3
no_fmllr=false
# 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 [ $# != 5 ]; then
echo "Usage: steps/train_ubm.sh <num-gauss> <data> <lang> <ali-dir> <exp>"
echo " e.g.: steps/train_ubm.sh 400 data/train_si84 data/lang exp/tri2b_ali_si84 exp/ubm3c"
echo "main options (for others, see top of script file)"
echo " --config <config-file> # config containing options"
echo " --cmd (utils/run.pl|utils/queue.pl <queue opts>) # how to run jobs."
echo " --silence-weight <sil-weight> # weight for silence (e.g. 0.5 or 0.0)"
echo " --num-iters <#iters> # Number of iterations of E-M"\
echo " --no-fmllr (true|false) # ignore speaker matrices even if present"
exit 1;
fi
num_gauss=$1
data=$2
lang=$3
alidir=$4
dir=$5
for f in $data/feats.scp $lang/L.fst $alidir/ali.1.gz $alidir/final.mdl; do
[ ! -f $f ] && echo "No such file $f" && exit 1;
done
if [ $[$num_gauss*2] -gt $intermediate_num_gauss ]; then
echo "intermediate_num_gauss was too small $intermediate_num_gauss"
intermediate_num_gauss=$[$num_gauss*2];
echo "setting it to $intermediate_num_gauss"
fi
# Set various variables.
silphonelist=`cat $lang/phones/silence.csl` || exit 1;
nj=`cat $alidir/num_jobs` || exit 1;
mkdir -p $dir/log
echo $nj > $dir/num_jobs
sdata=$data/split$nj;
[[ -d $sdata && $data/feats.scp -ot $sdata ]] || split_data.sh $data $nj || exit 1;
splice_opts=`cat $alidir/splice_opts 2>/dev/null` # frame-splicing options.
## Set up features.
if [ -f $alidir/final.mat ]; then feat_type=lda; else feat_type=delta; fi
echo "$0: 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 $alidir/final.mat ark:- ark:- |"
cp $alidir/final.mat $dir
;;
*) echo "$0: invalid feature type $feat_type" && exit 1;
esac
if [ -f $alidir/trans.1 ]; then
if $no_fmllr; then
echo "$0: deliberately ignoring speaker transforms from $alidir"
else
echo "$0: using transforms from $alidir"
feats="$feats transform-feats --utt2spk=ark:$sdata/JOB/utt2spk ark,s,cs:$alidir/trans.JOB ark:- ark:- |"
fi
elif [ -f $alidir/raw_trans.1 ]; then
echo "$0: using raw-FMLLR transforms from $alidir"
feats="ark,s,cs:apply-cmvn --norm-vars=false --utt2spk=ark:$sdata/JOB/utt2spk scp:$sdata/JOB/cmvn.scp scp:$sdata/JOB/feats.scp ark:- | transform-feats --utt2spk=ark:$sdata/JOB/utt2spk ark,s,cs:$alidir/raw_trans.JOB ark:- ark:- | splice-feats $splice_opts ark:- ark:- | transform-feats $alidir/final.mat ark:- ark:- |"
fi
##
if [ ! -z "$silence_weight" ]; then
weights_opt="--weights='ark,s,cs:gunzip -c $alidir/ali.JOB.gz | ali-to-post ark:- ark:- | weight-silence-post $silence_weight $silphonelist $alidir/final.mdl ark:- ark:- | post-to-weights ark:- ark:- |'"
else
weights_opt=
fi
if [ $stage -le -2 ]; then
echo "$0: clustering model $alidir/final.mdl to get initial UBM"
$cmd $dir/log/cluster.log \
init-ubm --intermediate-num-gauss=$intermediate_num_gauss --ubm-num-gauss=$num_gauss \
--verbose=2 --fullcov-ubm=true $alidir/final.mdl $alidir/final.occs \
$dir/0.ubm || exit 1;
fi
# Do initial phase of Gaussian selection and save it to disk -- later on we'll
# do more Gaussian selection to further prune, as the model changes.
if [ $stage -le -1 ]; then
echo "$0: doing Gaussian selection"
$cmd JOB=1:$nj $dir/log/gselect.JOB.log \
gmm-gselect --n=$num_gselect1 "fgmm-global-to-gmm $dir/0.ubm - |" "$feats" \
"ark:|gzip -c >$dir/gselect.JOB.gz" || exit 1;
fi
x=0
while [ $x -lt $num_iters ]; do
echo "Pass $x"
$cmd JOB=1:$nj $dir/log/acc.$x.JOB.log \
gmm-gselect --n=$num_gselect2 "--gselect=ark,s,cs:gunzip -c $dir/gselect.JOB.gz|" \
"fgmm-global-to-gmm $dir/$x.ubm - |" "$feats" ark:- \| \
fgmm-global-acc-stats $weights_opt --gselect=ark,s,cs:- $dir/$x.ubm "$feats" \
$dir/$x.JOB.acc || exit 1;
lowcount_opt="--remove-low-count-gaussians=false"
[ $[$x+1] -eq $num_iters ] && lowcount_opt= # Only remove low-count Gaussians
# on last iter-- we can't do it earlier, or the Gaussian-selection info would
# be mismatched.
$cmd $dir/log/update.$x.log \
fgmm-global-est $lowcount_opt --verbose=2 $dir/$x.ubm "fgmm-global-sum-accs - $dir/$x.*.acc |" \
$dir/$[$x+1].ubm || exit 1;
rm $dir/$x.*.acc $dir/$x.ubm
x=$[$x+1]
done
rm $dir/gselect.*.gz
rm $dir/final.ubm 2>/dev/null
mv $dir/$x.ubm $dir/final.ubm || exit 1;