train_sgmm2.sh
12.9 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
140
141
142
143
144
145
146
147
148
149
150
151
152
153
154
155
156
157
158
159
160
161
162
163
164
165
166
167
168
169
170
171
172
173
174
175
176
177
178
179
180
181
182
183
184
185
186
187
188
189
190
191
192
193
194
195
196
197
198
199
200
201
202
203
204
205
206
207
208
209
210
211
212
213
214
215
216
217
218
219
220
221
222
223
224
225
226
227
228
229
230
231
232
233
234
235
236
237
238
239
240
241
242
243
244
245
246
247
248
249
250
251
252
253
254
255
256
257
258
259
260
261
262
263
264
265
266
267
268
269
270
271
272
273
274
275
276
277
278
279
280
281
282
283
284
285
286
287
288
289
290
291
292
293
294
295
296
297
298
299
300
#!/bin/bash
# Copyright 2012 Johns Hopkins University (Author: Daniel Povey). Apache 2.0.
# SGMM training, with speaker vectors. This script would normally be called on
# top of fMLLR features obtained from a conventional system, but it also works
# on top of any type of speaker-independent features (based on
# deltas+delta-deltas or LDA+MLLT). For more info on SGMMs, see the paper "The
# subspace Gaussian mixture model--A structured model for speech recognition".
# (Computer Speech and Language, 2011).
# Begin configuration section.
cmd=run.pl
stage=-6 # use this to resume partially finished training
context_opts= # e.g. set it to "--context-width=5 --central-position=2" for a
# quinphone system.
scale_opts="--transition-scale=1.0 --acoustic-scale=0.1 --self-loop-scale=0.1"
num_iters=25 # Total number of iterations of training
num_iters_alimdl=3 # Number of iterations for estimating alignment model.
max_iter_inc=15 # Last iter to increase #substates on.
realign_iters="5 10 15"; # Iters to realign on.
spkvec_iters="5 8 12 17" # Iters to estimate speaker vectors on.
increase_iters="6 10 14"; # Iters on which to increase phn dim and/or spk dim;
# rarely necessary, and if it is, only the 1st will normally be necessary.
rand_prune=0.1 # Randomized-pruning parameter for posteriors, to speed up training.
# Bigger -> more pruning; zero = no pruning.
phn_dim= # You can use this to set the phonetic subspace dim. [default: feat-dim+1]
spk_dim= # You can use this to set the speaker subspace dim. [default: feat-dim]
power=0.25 # Exponent for number of gaussians according to occurrence counts
beam=8
self_weight=0.9
retry_beam=40
leaves_per_group=5 # Relates to the SCTM (state-clustered tied-mixture) aspect:
# average number of pdfs in a "group" of pdfs.
update_m_iter=4
spk_dep_weights=true # [Symmetric SGMM] set this to false if you don't want "u" (i.e. to turn off
# symmetric SGMM.
# 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 [ $# != 7 ]; then
echo "Usage: steps/train_sgmm2.sh <num-leaves> <num-substates> <data> <lang> <ali-dir> <ubm> <exp-dir>"
echo " e.g.: steps/train_sgmm2.sh 5000 8000 data/train_si84 data/lang \\"
echo " exp/tri3b_ali_si84 exp/ubm4a/final.ubm exp/sgmm4a"
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 " --leaves-per-group <#leaves> # Average #leaves shared in one group"
exit 1;
fi
num_pdfs=$1 # final #leaves, at 2nd level of tree.
totsubstates=$2
data=$3
lang=$4
alidir=$5
ubm=$6
dir=$7
num_groups=$[$num_pdfs/$leaves_per_group]
first_spkvec_iter=`echo $spkvec_iters | awk '{print $1}'` || exit 1;
ciphonelist=`cat $lang/phones/context_indep.csl` || exit 1;
# Check some files.
for f in $data/feats.scp $lang/L.fst $alidir/ali.1.gz $alidir/final.mdl $ubm $alidir/num_jobs; do
[ ! -f $f ] && echo "$0: no such file $f" && exit 1;
done
# Set some variables.
oov=`cat $lang/oov.int`
silphonelist=`cat $lang/phones/silence.csl`
if [ "$self_weight" == "1.0" ]; then
numsubstates=$num_groups # Initial #-substates.
else
numsubstates=$num_pdfs # Initial #-substates.
fi
incsubstates=$[($totsubstates-$numsubstates)/$max_iter_inc] # per-iter increment for #substates
feat_dim=`gmm-info $alidir/final.mdl 2>/dev/null | awk '/feature dimension/{print $NF}'` || exit 1;
[ $feat_dim -eq $feat_dim ] || exit 1; # make sure it's numeric.
[ -z $phn_dim ] && phn_dim=$[$feat_dim+1]
[ -z $spk_dim ] && spk_dim=$feat_dim
nj=`cat $alidir/num_jobs` || exit 1;
splice_opts=`cat $alidir/splice_opts 2>/dev/null` # frame-splicing options.
cmvn_opts=`cat $alidir/cmvn_opts 2>/dev/null`
mkdir -p $dir/log
cp $alidir/splice_opts $dir 2>/dev/null # frame-splicing options.
cp $alidir/cmvn_opts $dir 2>/dev/null # cmn/cmvn option.
echo $nj > $dir/num_jobs
sdata=$data/split$nj;
[[ -d $sdata && $data/feats.scp -ot $sdata ]] || split_data.sh $data $nj || exit 1;
utils/lang/check_phones_compatible.sh $lang/phones.txt $alidir/phones.txt || exit 1;
cp $lang/phones.txt $dir || exit 1;
spkvecs_opt= # Empty option for now, until we estimate the speaker vectors.
gselect_opt="--gselect=ark,s,cs:gunzip -c $dir/gselect.JOB.gz|"
## 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 $cmvn_opts --utt2spk=ark:$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 $cmvn_opts --utt2spk=ark:$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 "$0: invalid feature type $feat_type" && exit 1;
esac
if [ -f $alidir/trans.1 ]; then
echo "$0: using transforms from $alidir"
feats="$feats transform-feats --utt2spk=ark:$sdata/JOB/utt2spk ark,s,cs:$alidir/trans.JOB ark:- ark:- |"
elif [ -f $alidir/raw_trans.1 ]; then
echo "$0: using raw-fMLLR transforms from $alidir"
feats="ark,s,cs:apply-cmvn $cmvn_opts --utt2spk=ark:$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 [ $stage -le -6 ]; then
echo "$0: accumulating tree stats"
$cmd JOB=1:$nj $dir/log/acc_tree.JOB.log \
acc-tree-stats $context_opts --ci-phones=$ciphonelist $alidir/final.mdl "$feats" \
"ark:gunzip -c $alidir/ali.JOB.gz|" $dir/JOB.treeacc || exit 1;
[ "`ls $dir/*.treeacc | wc -w`" -ne "$nj" ] && echo "$0: Wrong #tree-stats" && exit 1;
sum-tree-stats $dir/treeacc $dir/*.treeacc 2>$dir/log/sum_tree_acc.log || exit 1;
rm $dir/*.treeacc
fi
if [ $stage -le -5 ]; then
echo "$0: Getting questions for tree clustering."
# preparing questions, roots file...
cluster-phones $context_opts $dir/treeacc $lang/phones/sets.int $dir/questions.int 2> $dir/log/questions.log || exit 1;
cat $lang/phones/extra_questions.int >> $dir/questions.int
compile-questions $context_opts $lang/topo $dir/questions.int $dir/questions.qst 2>$dir/log/compile_questions.log || exit 1;
echo "$0: Building the tree"
$cmd $dir/log/build_tree.log \
build-tree-two-level $context_opts --binary=false --verbose=1 --max-leaves-first=$num_groups \
--max-leaves-second=$num_pdfs $dir/treeacc $lang/phones/roots.int \
$dir/questions.qst $lang/topo $dir/tree $dir/pdf2group.map || exit 1;
fi
if [ $stage -le -4 ]; then
echo "$0: Initializing the model"
# Note: if phn_dim > feat_dim+1 or spk_dim > feat_dim, these dims
# will be truncated on initialization.
$cmd $dir/log/init_sgmm.log \
sgmm2-init --spk-dep-weights=$spk_dep_weights --self-weight=$self_weight \
--pdf-map=$dir/pdf2group.map --phn-space-dim=$phn_dim \
--spk-space-dim=$spk_dim $lang/topo $dir/tree $ubm $dir/0.mdl || exit 1;
fi
if [ $stage -le -3 ]; then
echo "$0: doing Gaussian selection"
$cmd JOB=1:$nj $dir/log/gselect.JOB.log \
sgmm2-gselect $dir/0.mdl "$feats" \
"ark,t:|gzip -c >$dir/gselect.JOB.gz" || exit 1;
fi
if [ $stage -le -2 ]; then
echo "$0: compiling training graphs"
text="ark:sym2int.pl --map-oov $oov -f 2- $lang/words.txt < $sdata/JOB/text|"
$cmd JOB=1:$nj $dir/log/compile_graphs.JOB.log \
compile-train-graphs --read-disambig-syms=$lang/phones/disambig.int $dir/tree $dir/0.mdl $lang/L.fst \
"$text" "ark:|gzip -c >$dir/fsts.JOB.gz" || exit 1;
fi
if [ $stage -le -1 ]; then
echo "$0: converting alignments"
$cmd JOB=1:$nj $dir/log/convert_ali.JOB.log \
convert-ali $alidir/final.mdl $dir/0.mdl $dir/tree "ark:gunzip -c $alidir/ali.JOB.gz|" \
"ark:|gzip -c >$dir/ali.JOB.gz" || exit 1;
fi
x=0
while [ $x -lt $num_iters ]; do
echo "$0: training pass $x ... "
if echo $realign_iters | grep -w $x >/dev/null && [ $stage -le $x ]; then
echo "$0: re-aligning data"
$cmd JOB=1:$nj $dir/log/align.$x.JOB.log \
sgmm2-align-compiled $spkvecs_opt $scale_opts "$gselect_opt" \
--utt2spk=ark:$sdata/JOB/utt2spk --beam=$beam --retry-beam=$retry_beam \
$dir/$x.mdl "ark:gunzip -c $dir/fsts.JOB.gz|" "$feats" \
"ark:|gzip -c >$dir/ali.JOB.gz" || exit 1;
fi
if [ $spk_dim -gt 0 ] && echo $spkvec_iters | grep -w $x >/dev/null; then
if [ $stage -le $x ]; then
$cmd JOB=1:$nj $dir/log/spkvecs.$x.JOB.log \
ali-to-post "ark:gunzip -c $dir/ali.JOB.gz|" ark:- \| \
weight-silence-post 0.01 $silphonelist $dir/$x.mdl ark:- ark:- \| \
sgmm2-est-spkvecs --rand-prune=$rand_prune --spk2utt=ark:$sdata/JOB/spk2utt \
$spkvecs_opt "$gselect_opt" $dir/$x.mdl "$feats" ark,s,cs:- \
ark:$dir/tmp_vecs.JOB '&&' mv $dir/tmp_vecs.JOB $dir/vecs.JOB || exit 1;
fi
spkvecs_opt="--spk-vecs=ark:$dir/vecs.JOB"
fi
if [ $x -eq 0 ]; then
flags=vwcSt # on the first iteration, don't update projections M or N
elif [ $spk_dim -gt 0 -a $[$x%2] -eq 1 -a $x -ge $first_spkvec_iter ]; then
# Update N if we have speaker-vector space and x is odd,
# and we've already updated the speaker vectors...
flags=vNwSct
else
if [ $x -ge $update_m_iter ]; then
flags=vMwSct # udpate M.
else
flags=vwSct # no M on early iters, if --update-m-iter option given.
fi
fi
$spk_dep_weights && [ $x -ge $first_spkvec_iter ] && flags=${flags}u; # update
# spk-weight projections "u".
if [ $stage -le $x ]; then
$cmd JOB=1:$nj $dir/log/acc.$x.JOB.log \
sgmm2-acc-stats $spkvecs_opt --utt2spk=ark:$sdata/JOB/utt2spk \
--update-flags=$flags "$gselect_opt" --rand-prune=$rand_prune \
$dir/$x.mdl "$feats" "ark,s,cs:gunzip -c $dir/ali.JOB.gz | ali-to-post ark:- ark:-|" \
$dir/$x.JOB.acc || exit 1;
fi
# The next option is needed if the user specifies a phone or speaker sub-space
# dimension that's higher than the "normal" one.
increase_dim_opts=
if echo $increase_dim_iters | grep -w $x >/dev/null; then
increase_dim_opts="--increase-phn-dim=$phn_dim --increase-spk-dim=$spk_dim"
# Note: the command below might have a null effect on some iterations.
if [ $spk_dim -gt $feat_dim ]; then
cmd JOB=1:$nj $dir/log/copy_vecs.$x.JOB.log \
copy-vector --print-args=false --change-dim=$spk_dim \
ark:$dir/vecs.JOB ark:$dir/vecs_tmp.$JOB '&&' \
mv $dir/vecs_tmp.JOB $dir/vecs.JOB || exit 1;
fi
fi
if [ $stage -le $x ]; then
$cmd $dir/log/update.$x.log \
sgmm2-est --update-flags=$flags --split-substates=$numsubstates \
$increase_dim_opts --power=$power --write-occs=$dir/$[$x+1].occs \
$dir/$x.mdl "sgmm2-sum-accs - $dir/$x.*.acc|" $dir/$[$x+1].mdl || exit 1;
rm $dir/$x.mdl $dir/$x.*.acc $dir/$x.occs 2>/dev/null
fi
if [ $x -lt $max_iter_inc ]; then
numsubstates=$[$numsubstates+$incsubstates]
fi
x=$[$x+1];
done
rm $dir/final.mdl $dir/final.occs 2>/dev/null
ln -s $x.mdl $dir/final.mdl
ln -s $x.occs $dir/final.occs
if [ $spk_dim -gt 0 ]; then
# We need to create an "alignment model" that's been trained
# without the speaker vectors, to do the first-pass decoding with.
# in test time.
# We do this for a few iters, in this recipe.
final_mdl=$dir/$x.mdl
cur_alimdl=$dir/$x.mdl
while [ $x -lt $[$num_iters+$num_iters_alimdl] ]; do
echo "$0: building alignment model (pass $x)"
if [ $x -eq $num_iters ]; then # 1st pass of building alimdl.
flags=MwcS # don't update v the first time. Note-- we never update transitions.
# they wouldn't change anyway as we use the same alignment as previously.
else
flags=vMwcS
fi
if [ $stage -le $x ]; then
$cmd JOB=1:$nj $dir/log/acc_ali.$x.JOB.log \
ali-to-post "ark:gunzip -c $dir/ali.JOB.gz|" ark:- \| \
sgmm2-post-to-gpost $spkvecs_opt "$gselect_opt" \
--utt2spk=ark:$sdata/JOB/utt2spk $final_mdl "$feats" ark,s,cs:- ark:- \| \
sgmm2-acc-stats-gpost --rand-prune=$rand_prune --update-flags=$flags \
$cur_alimdl "$feats" ark,s,cs:- $dir/$x.JOB.aliacc || exit 1;
$cmd $dir/log/update_ali.$x.log \
sgmm2-est --update-flags=$flags --remove-speaker-space=true --power=$power \
$cur_alimdl "sgmm2-sum-accs - $dir/$x.*.aliacc|" $dir/$[$x+1].alimdl || exit 1;
rm $dir/$x.*.aliacc || exit 1;
[ $x -gt $num_iters ] && rm $dir/$x.alimdl
fi
cur_alimdl=$dir/$[$x+1].alimdl
x=$[$x+1]
done
rm $dir/final.alimdl 2>/dev/null
ln -s $x.alimdl $dir/final.alimdl
fi
utils/summarize_warnings.pl $dir/log
echo Done