Blame view
Scripts/steps/tandem/train_sgmm.sh
12.1 KB
ec85f8892 first commit |
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 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 132 133 134 135 136 137 138 139 140 141 142 143 144 145 146 147 148 149 150 151 152 153 154 155 156 157 158 159 160 161 162 163 164 165 166 167 168 169 170 171 172 173 174 175 176 177 178 179 180 181 182 183 184 185 186 187 188 189 190 191 192 193 194 195 196 197 198 199 200 201 202 203 204 205 206 207 208 209 210 211 212 213 214 215 216 217 218 219 220 221 222 223 224 225 226 227 228 229 230 231 232 233 234 235 236 237 238 239 240 241 242 243 244 245 246 247 248 249 250 251 252 253 254 255 256 257 258 259 260 261 262 263 264 265 266 267 268 269 270 271 272 273 274 275 276 277 278 279 280 281 282 283 284 285 286 287 288 289 290 291 292 293 294 295 296 297 298 299 300 301 302 303 304 305 306 307 308 309 310 311 312 |
#!/bin/bash # Copyright 2012 Johns Hopkins University (Author: Daniel Povey). Apache 2.0. # Korbinian Riedhammer # 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. nj=4 cmd=run.pl stage=-6 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 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_dim_iters="6 8"; # 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. 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=0.2 # Exponent for number of gaussians according to occurrence counts beam=8 retry_beam=40 cluster_thresh=-1 # for build-tree control final bottom-up clustering of leaves normft2=true # 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 [ $# != 8 ]; then echo "Usage: steps/tandem/train_sgmm.sh <num-leaves> <num-substates> <data1> <data2> <lang> <ali-dir> <ubm> <exp-dir>" echo " e.g.: steps/tandem/train_sgmm.sh 3500 10000 {mfcc,bottleneck},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" exit 1; fi num_leaves=$1 totsubstates=$2 data1=$3 data2=$4 lang=$5 alidir=$6 ubm=$7 dir=$8 # Check some files. for f in $data1/feats.scp $data2/feats.scp $lang/L.fst $alidir/ali.1.gz $alidir/final.mdl $ubm; do [ ! -f $f ] && echo "$0: no such file $f" && exit 1; done # Set some variables. oov=`cat $lang/oov.int` silphonelist=`cat $lang/phones/silence.csl` numsubstates=$num_leaves # Initial #-substates. 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; mkdir -p $dir/log echo $nj > $dir/num_jobs sdata1=$data1/split$nj; sdata2=$data2/split$nj; [[ -d $sdata1 && $data1/feats.scp -ot $sdata1 ]] || split_data.sh $data1 $nj || exit 1; [[ -d $sdata2 && $data2/feats.scp -ot $sdata2 ]] || split_data.sh $data2 $nj || 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. splice_opts=`cat $alidir/splice_opts 2>/dev/null` # frame-splicing options. normft2=`cat $alidir/normft2 2>/dev/null` if [ -f $alidir/final.mat ]; then feat_type=lda; else feat_type=delta; fi case $feat_type in delta) echo "$0: feature type is $feat_type" ;; lda) echo "$0: feature type is $feat_type" cp $alidir/{lda,final}.mat $dir/ || exit 1; ;; *) echo "$0: invalid feature type $feat_type" && exit 1; esac # set up feature stream 1; this are usually spectral features, so we will add # deltas or splice them feats1="ark,s,cs:apply-cmvn --norm-vars=false --utt2spk=ark:$sdata1/JOB/utt2spk scp:$sdata1/JOB/cmvn.scp scp:$sdata1/JOB/feats.scp ark:- |" if [ "$feat_type" == "delta" ]; then feats1="$feats1 add-deltas ark:- ark:- |" elif [ "$feat_type" == "lda" ]; then feats1="$feats1 splice-feats $splice_opts ark:- ark:- | transform-feats $dir/lda.mat ark:- ark:- |" fi # set up feature stream 2; this are usually bottleneck or posterior features, # which may be normalized if desired feats2="scp:$sdata2/JOB/feats.scp" if [ "$normft2" == "true" ]; then feats2="ark,s,cs:apply-cmvn --norm-vars=false --utt2spk=ark:$sdata2/JOB/utt2spk scp:$sdata2/JOB/cmvn.scp $feats2 ark:- |" fi # assemble tandem features feats="ark,s,cs:paste-feats '$feats1' '$feats2' ark:- |" # add transformation, if applicable if [ "$feat_type" == "lda" ]; then feats="$feats transform-feats $dir/final.mat ark:- ark:- |" fi # splicing/normalization options cp $alidir/{splice_opts,normft2,tandem} $dir 2>/dev/null if [ -f $alidir/trans.1 ]; then echo "$0: using transforms from $alidir" feats="$feats transform-feats --utt2spk=ark:$sdata1/JOB/utt2spk ark,s,cs:$alidir/trans.JOB ark:- ark:- |" fi ## if [ $stage -le -6 ]; then echo "$0: accumulating tree stats" $cmd JOB=1:$nj $dir/log/acc_tree.JOB.log \ acc-tree-stats --ci-phones=$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 $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 $lang/topo $dir/questions.int $dir/questions.qst 2>$dir/log/compile_questions.log || exit 1; echo "$0: Building the tree" $cmd $dir/log/build_tree.log \ build-tree --verbose=1 --max-leaves=$num_leaves \ --cluster-thresh=$cluster_thresh $dir/treeacc $lang/phones/roots.int \ $dir/questions.qst $lang/topo $dir/tree || 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 $dir/log/init_sgmm.log \ sgmm-init --phn-space-dim=$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 \ sgmm-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 < $sdata1/JOB/text|" $cmd JOB=1:$nj $dir/log/compile_graphs.JOB.log \ compile-train-graphs $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 \ sgmm-align-compiled $spkvecs_opt $scale_opts "$gselect_opt" \ --utt2spk=ark:$sdata1/JOB/utt2spk --beam=$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:- \| \ sgmm-est-spkvecs --rand-prune=$rand_prune --spk2utt=ark:$sdata1/JOB/spk2utt \ $spkvecs_opt "$gselect_opt" $dir/$x.mdl "$feats" ark,s,cs:- \ ark:$dir/tmp_vecs.JOB '&&' mv $dir/tmp_vecs.JOB $dir/vecs.JOB || exit 1; fi spkvecs_opt[$n]="--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 `echo $spkvec_iters | awk '{print $1}'` ]; then # Update N if we have speaker-vector space and x is odd, # and we've already updated the speaker vectors... flags=vNwcSt else # otherwise update M. flags=vMwcSt fi if [ $stage -le $x ]; then $cmd JOB=1:$nj $dir/log/acc.$x.JOB.log \ sgmm-acc-stats $spkvecs_opt --utt2spk=ark:$sdata1/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 \ sgmm-est --update-flags=$flags --split-substates=$numsubstates $increase_dim_opts \ --power=$power --write-occs=$dir/$[$x+1].occs $dir/$x.mdl "sgmm-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:- \| \ sgmm-post-to-gpost $spkvecs_opt "$gselect_opt" \ --utt2spk=ark:$sdata1/JOB/utt2spk $final_mdl "$feats" ark,s,cs:- ark:- \| \ sgmm-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 \ sgmm-est --update-flags=$flags --remove-speaker-space=true --power=$power $cur_alimdl \ "sgmm-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 |