train_diag_ubm.sh
5.08 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
#!/bin/bash
# Copyright Johns Hopkins University (Author: Daniel Povey), 2012.
# Apache 2.0.
# Train a diagonal mixture of Gaussians. This is trained without
# reference to class labels-- except that, optionally, you can down-weight
# silence phones, and alignments are needed for that.
#
# The current use for this is in fMMI training.
# Begin configuration section.
nj=4
cmd=run.pl
num_iters=3
silence_weight=
stage=-2
# The value "intermediate" is a number of Gaussians we first obtain by clustering
# the Gaussians within each state of the model, before clustering down to
# $num_Gauss. This is for efficiency. It's not a very important parameter,
# as far as I know.
intermediate=2000
num_gselect=50 # Number of Gaussian-selection indices to use while training
# the model.
# 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 [ $# != 5 ]; then
echo "Usage: steps/train_diag_ubm.sh <num-gauss> <data> <lang> <alignment-dir|src-dir> <dir>"
echo " e.g.: steps/train_diag_ubm.sh 400 data/train_si84 data/lang exp/tri2b_ali_si84 exp/ubm3c"
echo "Options: "
echo " --silence-weight <sil-weight> # default 1.0. Use to down-weight silence."
echo " --cmd (utils/run.pl|utils/queue.pl <queue opts>) # how to run jobs."
echo " --nj <num-job> # number of parallel jobs to run."
echo " --num-iters <niter> # number of iterations of training (default: $num_iters)"
echo " --stage <stage> # stage to do partial re-run from."
exit 1;
fi
num_gauss=$1
data=$2
lang=$3
alidir=$4
dir=$5
silphonelist=`cat $lang/phones/silence.csl` || exit 1;
sdata=$data/split$nj
splice_opts=`cat $alidir/splice_opts 2>/dev/null`
cmvn_opts=`cat $alidir/cmvn_opts 2>/dev/null`
delta_opts=`cat $alidir/delta_opts 2>/dev/null`
mkdir -p $dir/log
[[ -d $sdata && $data/feats.scp -ot $sdata ]] || split_data.sh $data $nj || exit 1;
echo $nj > $dir/num_jobs
utils/lang/check_phones_compatible.sh $lang/phones.txt $alidir/phones.txt || exit 1;
cp $lang/phones.txt $dir || exit 1;
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 $cmvn_opts --utt2spk=ark:$sdata/JOB/utt2spk scp:$sdata/JOB/cmvn.scp scp:$sdata/JOB/feats.scp ark:- | add-deltas $delta_opts ark:- ark:- |";;
lda) feats="ark,s,cs:apply-cmvn $cmvn_opts --utt2spk=ark:$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 "Invalid feature type $feat_type" && exit 1;
esac
if [ -f $alidir/trans.1 ]; then
echo Using transforms from $alidir;
[ "$nj" -ne "`cat $alidir/num_jobs`" ] && \
echo "The number of jobs differs from alignment directory $alidir." && exit 1;
feats="$feats transform-feats --utt2spk=ark:$sdata/JOB/utt2spk ark:$alidir/trans.JOB ark:- ark:- |"
fi
if [ ! -z "$silence_weight" ]; then
[ ! -f $alidir/ali.1.gz ] && \
echo "You specified weighting for silence but $alidir/ali.1.gz does not exist." && exit 1;
[ "$nj" -ne "`cat $alidir/num_jobs`" ] && \
echo "You specified silence weight but $alidir has different #jobs." && exit 1;
weights="--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=
fi
# $intermediate should be more than $num_gauss..
[ $[$num_gauss*2] -gt $intermediate ] && intermediate=$[$num_gauss*2] \
&& echo "Setting intermediate=$intermediate (it was too small)";
if [ $stage -le -2 ]; then
echo "Clustering Gaussians in $alidir/final.mdl"
$cmd $dir/log/cluster.log \
init-ubm --fullcov-ubm=false --intermediate-num-gauss=$intermediate \
--ubm-num-gauss=$num_gauss $alidir/final.mdl $alidir/final.occs $dir/0.dubm || exit 1;
fi
# Store Gaussian selection indices on disk-- this speeds up the training passes.
if [ $stage -le -1 ]; then
echo Getting Gaussian-selection info
$cmd JOB=1:$nj $dir/log/gselect.JOB.log \
gmm-gselect --n=$num_gselect $dir/0.dubm "$feats" \
"ark:|gzip -c >$dir/gselect.JOB.gz" || exit 1;
fi
for x in `seq 0 $[$num_iters-1]`; do
echo "Training pass $x"
if [ $stage -le $x ]; then
# Accumulate stats.
$cmd JOB=1:$nj $dir/log/acc.$x.JOB.log \
gmm-global-acc-stats $weights "--gselect=ark,s,cs:gunzip -c $dir/gselect.JOB.gz|" \
$dir/$x.dubm "$feats" $dir/$x.JOB.acc || exit 1;
if [ $x -lt $[$num_iters-1] ]; then # Don't remove low-count Gaussians till last iter,
opt="--remove-low-count-gaussians=false" # or gselect info won't be valid any more.
fi
$cmd $dir/log/update.$x.log \
gmm-global-est $opt $dir/$x.dubm "gmm-global-sum-accs - $dir/$x.*.acc|" \
$dir/$[$x+1].dubm || exit 1;
rm $dir/$x.*.acc $dir/$x.dubm
fi
done
rm $dir/gselect.*.gz
mv $dir/$num_iters.dubm $dir/final.dubm || exit 1;
exit 0;