Merging some changes into sandbox [I think]

git-svn-id: https://svn.code.sf.net/p/kaldi/code/sandbox/discrim@502 5e6a8d80-dfce-4ca6-a32a-6e07a63d50c8

egs/rm/s3/steps/decode_deltas.sh

@@ -52,7 +52,7 @@ fi
 # CMVN stats-- we make them part of a pipe.
 feats="ark:compute-cmvn-stats --spk2utt=ark:$data/spk2utt scp:$data/feats.scp ark:- | apply-cmvn --norm-vars=false --utt2spk=ark:$data/utt2spk ark:- scp:$data/feats.scp ark:- | add-deltas ark:- ark:- |"
 
-# For Resource Management, we use beam of 25 and acwt of 1/10.
+# For Resource Management, we use beam of 20 and acwt of 1/10.
 # More normal, LVCSR setups would have a beam of 13 and acwt of 1/15 or so.
 # If you decode with a beam of 20 on an LVCSR setup it will be very slow.
 

egs/rm/s3/steps/train_mono.sh

@@ -91,7 +91,7 @@ while [ $x -lt $numiters ]; do
   fi
   gmm-acc-stats-ali --binary=false $dir/$x.mdl "$feats" ark:$dir/cur.ali $dir/$x.acc 2> $dir/acc.$x.log  || exit 1;
   gmm-est --write-occs=$dir/$[$x+1].occs --mix-up=$numgauss $dir/$x.mdl $dir/$x.acc $dir/$[$x+1].mdl 2> $dir/update.$x.log || exit 1;
-  rm $dir/$x.mdl $dir/$x.acc $dir/$x.occs
+  rm $dir/$x.mdl $dir/$x.acc $dir/$x.occs 2>/dev/null
   if [ $x -le $maxiterinc ]; then
      numgauss=$[$numgauss+$incgauss];
   fi

egs/wsj/s1/run.sh

@@ -490,3 +490,11 @@ done
 # cat exp/decode_tri2a_tgpr_eval92/scoring/hyp.sys
 
 
+# notes on timing of alignment... trying it in tri2a for 500 utts.  Took
+# [with retry-beam=40]
+# the results below seem to show that beam = 6 is the fastest...
+# of course this assumes the retry-beam is 40.
+# 20.9 sec @ beam = 7
+# 13.8 sec @ beam = 6
+# 14.4 sec @ beam = 5
+# 14.4 sec @ beam = 4
\ No newline at end of file

egs/wsj/s1/steps/rescore_rnnlm_example.sh

@@ -35,9 +35,10 @@ echo "Compiling LM fst"
     grep -v '</s> <s>' | \
     grep -v '</s> </s>' | \
     arpa2fst - | fstprint | \
-    scripts/remove_oovs.pl data/oovs_srilm.3g.kn.gz.txt | \
+    scripts/remove_oovs.pl data/oovs_tg.txt | \
     scripts/eps2disambig.pl |  fstcompile --isymbols=$WORDSYM --osymbols=$WORDSYM \
-     --keep_isymbols=false --keep_osymbols=false > $TMP/G.fst
+     --keep_isymbols=false --keep_osymbols=false | \
+   fstproject --project_output=true > $TMP/G.fst
 
 echo "Extracting $NBEST best"
 

egs/wsj/s1/steps/train_sgmm3e.sh

+#!/bin/bash
+# Copyright 2010-2011 Microsoft Corporation  Arnab Ghoshal
+
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+#  http://www.apache.org/licenses/LICENSE-2.0
+#
+# THIS CODE IS PROVIDED *AS IS* BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY
+# KIND, EITHER EXPRESS OR IMPLIED, INCLUDING WITHOUT LIMITATION ANY IMPLIED
+# WARRANTIES OR CONDITIONS OF TITLE, FITNESS FOR A PARTICULAR PURPOSE,
+# MERCHANTABLITY OR NON-INFRINGEMENT.
+# See the Apache 2 License for the specific language governing permissions and
+# limitations under the License.
+
+
+# sgmm3e is as sgmm3b but on splice+LDA+ET features, not delta+accel
+# sgmm3b is as sgmm3a (SGMM with half SI-284), but adding speaker vectors.
+
+
+
+if [ -f path.sh ]; then . path.sh; fi
+
+dir=exp/sgmm3e
+srcdir=exp/tri2k
+mat=$srcdir/lda.mat
+ubm=exp/ubm3d/final.ubm
+srcmodel=$srcdir/final.mdl
+srcalimodel=$srcdir/final.alimdl
+ldamat=$srcdir/lda.mat
+defaultmat=$srcdir/default.mat
+et=$srcdir/final.et
+
+scale_opts="--transition-scale=1.0 --acoustic-scale=0.1 --self-loop-scale=0.1"
+
+numiters=35 # Total number of iterations.
+realign_iters="5 15 25"; # realign a bit earlier than we did in tri2a, 
+    # since SGMM system quite different
+    # from normal triphone system.
+spkvec_iters="5 8 12 17 22 32"
+maxiterinc=20 # By this iter, we have all the substates.
+numleaves=6000 # was 2k for GMM system: incresaing it for SGMM system.
+numsubstates=6000 # initial #-substates
+totsubstates=35000 # a little less than #Gauss for baseline GMM system (40k)
+incsubstates=$[($totsubstates-$numsubstates)/$maxiterinc] # per-iter increment for #substates
+
+phn_dim=50
+phn_dim_iter=3 # iter to increase phn dim.
+
+silphonelist=`cat data/silphones.csl`
+randprune=0.1
+
+mkdir -p $dir
+cp data/train.scp $dir
+cp data/train.tra $dir
+
+scripts/filter_scp.pl $dir/train.scp data/train.utt2spk > $dir/train.utt2spk
+scripts/utt2spk_to_spk2utt.pl $dir/train.utt2spk > $dir/train.spk2utt
+
+scripts/split_scp.pl --utt2spk=$dir/train.utt2spk $dir/train{,1,2,3}.scp
+scripts/split_scp.pl --utt2spk=$dir/train.utt2spk $dir/train{,1,2,3}.tra
+scripts/split_scp.pl --utt2spk=$dir/train.utt2spk $dir/train{,1,2,3}.utt2spk
+
+for n in 1 2 3 ""; do # The "" handles the un-split one.  Creating spk2utt files..
+  scripts/utt2spk_to_spk2utt.pl $dir/train$n.utt2spk > $dir/train$n.spk2utt
+done
+
+# also see featspart below, used for sub-parts of the features;
+# try to keep them in sync.
+
+feats="ark,s,cs:splice-feats --print-args=false scp:$dir/train.scp ark:- | transform-feats $ldamat ark:- ark:- | transform-feats --utt2spk=ark:$dir/train.utt2spk \"ark:cat $dir/?.trans|\" ark:- ark:- |"
+for n in 1 2 3; do
+  featspart[$n]="ark,s,cs:splice-feats --print-args=false scp:$dir/train${n}.scp ark:- | transform-feats $ldamat ark:- ark:- | transform-feats --utt2spk=ark:$dir/train$n.utt2spk ark:$dir/$n.trans ark: ark:- |"
+  defaultfeatspart[$n]="ark,s,cs:splice-feats --print-args=false scp:$dir/train${n}.scp ark:- | transform-feats $defaultmat ark:- ark:- |"
+  ldafeatspart[$n]="ark,s,cs:splice-feats --print-args=false scp:$dir/train${n}.scp ark:- | transform-feats $ldamat ark:- ark:- |"
+done
+
+if [ ! -f $ubm ]; then
+  echo "No UBM in $ubm";
+  exit 1
+fi
+
+cp $srcdir/topo $dir
+
+echo "Creating training graphs for model from $srcdir"
+rm -f $dir/.error
+for n in 1 2 3; do
+  compile-train-graphs $srcdir/tree $srcmodel  data/L.fst ark:$dir/train${n}.tra \
+     "ark:|gzip -c > $dir/srcgraphs${n}.fsts.gz" \
+     2>$dir/compile_src_graphs.${n}.log || touch $dir/.error &
+done
+wait
+[ -f $dir/.error ] &&  echo source-dir compile-graphs error && exit 1
+
+
+# Align all training data using old alignment model.
+
+echo "Aligning all training data with old alignment model"
+
+rm -f $dir/.error
+for n in 1 2 3; do
+   gmm-align-compiled $scale_opts --beam=8 --retry-beam=40 $srcalimodel \
+       "ark:gunzip -c $dir/srcgraphs${n}.fsts.gz|" "${defaultfeatspart[$n]}" \
+       "ark:|gzip -c >$dir/pre.${n}.ali.gz" \
+           2> $dir/pre_align.${n}.log || touch $dir/.error &
+done
+wait;
+[ -f $dir/.error ] &&  echo align error RE old system && exit 1
+
+echo "Computing ET transforms"
+
+for n in 1 2 3; do
+  ( ali-to-post "ark:gunzip -c $dir/pre.${n}.ali.gz|" ark:- | \
+    weight-silence-post 0.0 $silphonelist $srcalimodel ark:- ark:- | \
+    gmm-post-to-gpost $srcalimodel "${defaultfeatspart[$n]}" ark,o:- ark:- | \
+    gmm-est-et --spk2utt=ark:$dir/train$n.spk2utt --verbose=1 $srcmodel $et \
+    "${ldafeatspart[$n]}" ark,s,cs:- ark:$dir/$n.trans ark,t:$dir/$n.warp ) \
+       2> $dir/et_trans.$n.log || touch $dir/.error &
+done
+wait 
+[ -f $dir/.error ] && echo error aligning data && exit 1
+
+rm $dir/pre.${n}.ali.gz # remove first-pass alignments
+
+echo "Aligning all training data with old adapted model"
+
+rm -f $dir/.error
+for n in 1 2 3; do
+   gmm-align-compiled $scale_opts --beam=8 --retry-beam=40 $srcmodel \
+       "ark:gunzip -c $dir/srcgraphs${n}.fsts.gz|" "${featspart[$n]}" \
+       "ark:|gzip -c >$dir/0.${n}.ali.gz" \
+        2> $dir/old_align.${n}.log || touch $dir/.error &
+done
+wait;
+[ -f $dir/.error ] &&  echo align error RE old system && exit 1
+rm $dir/srcgraphs*.fsts.gz # These graphs no longer needed.
+
+
+acc-tree-stats  --ci-phones=$silphonelist $srcmodel "$feats" \
+  "ark:gunzip -c $dir/0.?.ali.gz|" $dir/treeacc 2> $dir/acc.tree.log  || exit 1;
+
+# The next few commands are involved with making the questions
+# for tree clustering.  The extra complexity vs. the RM recipe has
+# to do with the desire to ask questions about the "real" phones
+# ignoring things like stress and position-in-word, and ask questions
+# separately about stress and position-in-word.
+
+# Don't include silences as things to be clustered -> --nosil option.
+scripts/make_shared_phones.sh --nosil | scripts/sym2int.pl data/phones.txt > $dir/phone_sets.list
+cluster-phones $dir/treeacc $dir/phone_sets.list $dir/questions.txt 2> $dir/cluster_phones.log || exit 1;
+scripts/int2sym.pl data/phones.txt < $dir/questions.txt > $dir/questions_syms.txt
+scripts/make_extra_questions.sh | cat $dir/questions_syms.txt - > $dir/questions_syms_all.txt
+scripts/sym2int.pl data/phones.txt < $dir/questions_syms_all.txt > $dir/questions_all.txt
+
+compile-questions $dir/topo $dir/questions_all.txt $dir/questions.qst 2>$dir/compile_questions.log || exit 1;
+
+scripts/make_roots.sh > $dir/roots_syms.txt
+scripts/sym2int.pl --ignore-oov data/phones.txt  < $dir/roots_syms.txt > $dir/roots.txt
+
+build-tree --verbose=1 --max-leaves=$numleaves \
+  $dir/treeacc $dir/roots.txt \
+  $dir/questions.qst $dir/topo $dir/tree  2> $dir/train_tree.log || exit 1;
+
+# the sgmm-init program accepts a GMM, so we just create a temporary GMM "0.gmm"
+
+gmm-init-model  --write-occs=$dir/0.occs  \
+    $dir/tree $dir/treeacc $dir/topo $dir/0.gmm 2> $dir/init_gmm.log || exit 1;
+
+sgmm-init --spk-space-dim=40 $dir/topo $dir/tree $ubm $dir/0.mdl 2> $dir/init_sgmm.log || exit 1;
+
+rm $dir/0.gmm
+
+rm $dir/treeacc
+
+for n in 1 2 3; do
+  sgmm-gselect $dir/0.mdl "${featspart[$n]}" ark,t:- 2>$dir/gselect$n.log | \
+   gzip -c > $dir/gselect${n}.gz || touch $dir/.error &
+done
+wait
+[ -f $dir/.error ] && echo "Error in gselect phase" && exit 1;
+
+
+# Convert alignments generated from previous model, to use as 
+# initial alignments.
+
+for n in 1 2 3; do
+  convert-ali $srcmodel $dir/0.mdl $dir/tree \
+      "ark:gunzip -c $dir/0.$n.ali.gz|" \
+      "ark:|gzip -c > $dir/cur$n.ali.gz" \
+     2>$dir/convert.$n.log || exit 1; # don't parallelize: mostly I/O.
+done
+rm $dir/0.?.ali.gz
+
+# Make training graphs
+echo "Compiling training graphs"
+
+rm -f $dir/.error
+for n in 1 2 3; do
+  compile-train-graphs $dir/tree $dir/0.mdl  data/L.fst ark:$dir/train${n}.tra \
+     "ark:|gzip -c > $dir/graphs${n}.fsts.gz" \
+     2>$dir/compile_graphs.${n}.log || touch $dir/.error &
+done
+wait
+[ -f $dir/.error ] &&  echo compile-graphs error && exit 1
+
+x=0
+while [ $x -lt $numiters ]; do
+   echo "Pass $x"
+   if echo $realign_iters | grep -w $x >/dev/null; then
+     echo "Aligning data"
+     rm -f $dir/.error
+     for n in 1 2 3; do
+       sgmm-align-compiled ${spkvecs_opt[$n]} --utt2spk=ark:$dir/train$n.utt2spk \
+            "--gselect=ark,s,cs:gunzip -c $dir/gselect$n.gz|" \
+           $scale_opts --beam=8 --retry-beam=40 $dir/$x.mdl \
+           "ark:gunzip -c $dir/graphs${n}.fsts.gz|" "${featspart[$n]}" \
+           "ark:|gzip -c >$dir/cur${n}.ali.gz" 2> $dir/align.$x.$n.log \
+             || touch $dir/.error &
+     done
+     wait 
+     [ -f $dir/.error ] && echo error aligning data && exit 1
+   fi
+   if echo $spkvec_iters | grep -w $x >/dev/null; then
+     echo "Computing speaker vectors"
+     for n in 1 2 3; do
+      ( ali-to-post "ark:gunzip -c $dir/cur${n}.ali.gz|" ark:- | \
+        weight-silence-post 0.01 $silphonelist $dir/$x.mdl ark:- ark:- | \
+        sgmm-est-spkvecs --spk2utt=ark:$dir/train$n.spk2utt ${spkvecs_opt[$n]} \
+         "--gselect=ark,s,cs:gunzip -c $dir/gselect$n.gz|" \
+          --rand-prune=$randprune $dir/$x.mdl \
+         "${featspart[$n]}" ark,s,cs:- ark:$dir/tmp$n.vecs && \
+          mv $dir/tmp$n.vecs $dir/cur$n.vecs ) 2>$dir/spkvecs.$x.$n.log \
+           || touch $dir/.error &
+        spkvecs_opt[$n]="--spk-vecs=ark:$dir/cur$n.vecs"
+     done
+     wait;
+     [ -f $dir/.error ] && echo error computing speaker vectors && exit 1    
+   fi  
+
+   if [ $x -eq 0 ]; then
+     flags=vwcS
+   elif [ $[$x%2] -eq 1 -a $x -gt 4 ]; then # even iters after 4 (i.e. starting from 6)...
+     flags=vNwcS
+   else
+     flags=vMwcS
+   fi
+
+   for n in 1 2 3; do
+     sgmm-acc-stats-ali ${spkvecs_opt[$n]} --utt2spk=ark:$dir/train$n.utt2spk \
+       --update-flags=$flags "--gselect=ark,s,cs:gunzip -c $dir/gselect$n.gz|" \
+       --rand-prune=$randprune --binary=true $dir/$x.mdl "${featspart[$n]}" \
+      "ark:gunzip -c $dir/cur$n.ali.gz|" $dir/$x.$n.acc 2> $dir/acc.$x.$n.log \
+        || touch $dir/.error &
+   done
+   wait;
+   [ -f $dir/.error ] && echo error accumulating stats on iter $x && exit 1  
+   if [ $x == $phn_dim_iter ]; then 
+     phn_dim_opt=--increase-phn-dim=$phn_dim
+   else
+     phn_dim_opt=
+   fi
+   sgmm-est $phn_dim_opt --update-flags=$flags --split-substates=$numsubstates \
+       --write-occs=$dir/$[$x+1].occs  $dir/$x.mdl \
+      "sgmm-sum-accs - $dir/$x.?.acc|" $dir/$[$x+1].mdl  2> $dir/update.$x.log || exit 1;
+   rm $dir/$x.mdl $dir/$x.?.acc $dir/$x.occs 2>/dev/null
+   if [ $x -lt $maxiterinc ]; then 
+     numsubstates=$[$numsubstates+$incsubstates]
+   fi
+   x=$[$x+1];
+done
+
+( cd $dir; rm final.mdl final.occs 2>/dev/null; ln -s $x.mdl final.mdl; ln -s $x.occs final.occs )
+
+# Create "alignment model"
+flags=MwcS
+for n in 1 2 3; do
+ ( ali-to-post "ark:gunzip -c $dir/cur$n.ali.gz|" ark:- | \
+   sgmm-post-to-gpost ${spkvecs_opt[$n]} --utt2spk=ark:$dir/train$n.utt2spk \
+                "--gselect=ark,s,cs:gunzip -c $dir/gselect$n.gz|" \
+                 $dir/$x.mdl "${featspart[$n]}" ark,s,cs:- ark:- | \
+   sgmm-acc-stats-gpost --update-flags=$flags  $dir/$x.mdl "${featspart[$n]}" \
+            ark,s,cs:- $dir/$x.$n.aliacc ) 2> $dir/acc_ali.$x.$n.log || touch $dir/.error &
+done
+wait;
+[ -f $dir/.error ] && echo error accumulating stats for alignment model && exit 1  
+
+sgmm-est --update-flags=$flags --remove-speaker-space=true $dir/$x.mdl \
+    "sgmm-sum-accs - $dir/$x.?.aliacc|" $dir/$x.alimdl 2>$dir/update_ali.$x.log || exit 1;
+rm $dir/$x.?.aliacc
+
+( cd $dir; rm final.alimdl 2>/dev/null; ln -s $x.alimdl final.alimdl; )
+
+

egs/wsj/s1/steps/train_sgmm3f.sh

+#!/bin/bash
+# Copyright 2010-2011 Microsoft Corporation  Arnab Ghoshal
+
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+#  http://www.apache.org/licenses/LICENSE-2.0
+#
+# THIS CODE IS PROVIDED *AS IS* BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY
+# KIND, EITHER EXPRESS OR IMPLIED, INCLUDING WITHOUT LIMITATION ANY IMPLIED
+# WARRANTIES OR CONDITIONS OF TITLE, FITNESS FOR A PARTICULAR PURPOSE,
+# MERCHANTABLITY OR NON-INFRINGEMENT.
+# See the Apache 2 License for the specific language governing permissions and
+# limitations under the License.
+
+# sgmm3f is descended from sgmm3c (gender-dependent UBM) and sgmm3e
+# (exponential-transform features).
+
+if [ -f path.sh ]; then . path.sh; fi
+
+dir=exp/sgmm3f
+srcdir=exp/tri2k
+mat=$srcdir/lda.mat
+ubm=exp/ubm3f/final.ubm # about 800 UBM comps (400 each for male and female).
+preselectmap=exp/ubm3f/preselect.map
+srcmodel=$srcdir/final.mdl
+srcalimodel=$srcdir/final.alimdl
+ldamat=$srcdir/lda.mat
+defaultmat=$srcdir/default.mat
+et=$srcdir/final.et
+scale_opts="--transition-scale=1.0 --acoustic-scale=0.1 --self-loop-scale=0.1"
+
+numiters=35 # Total number of iterations.
+realign_iters="5 15 25"; # realign a bit earlier than we did in tri2a, 
+    # since SGMM system quite different
+    # from normal triphone system.
+spkvec_iters="5 8 12 17 22 32"
+maxiterinc=20 # By this iter, we have all the substates.
+numleaves=6000 # was 4.2k for GMM system: increasing it for SGMM system.
+numsubstates=6000 # initial #-substates
+totsubstates=35000 # a little less than #Gauss for baseline GMM system (40k)
+incsubstates=$[($totsubstates-$numsubstates)/$maxiterinc] # per-iter increment for #substates
+phn_dim=50
+phn_dim_iter=3 # iter to increase phn dim.
+
+silphonelist=`cat data/silphones.csl`
+randprune=0.1
+
+mkdir -p $dir
+cp data/train.scp $dir
+cp data/train.tra $dir
+scripts/filter_scp.pl $dir/train.scp data/train.utt2spk > $dir/train.utt2spk
+scripts/utt2spk_to_spk2utt.pl $dir/train.utt2spk > $dir/train.spk2utt
+
+
+scripts/compose_maps.pl $dir/train.utt2spk data/spk2gender.map | \
+ scripts/compose_maps.pl - $preselectmap | \
+ scripts/split_scp.pl --utt2spk=$dir/train.utt2spk - $dir/preselect.{1,2,3}
+ gzip -f $dir/preselect.{1,2,3}
+
+
+# done creating preselect file.
+
+scripts/split_scp.pl --utt2spk=$dir/train.utt2spk $dir/train{,1,2,3}.scp
+scripts/split_scp.pl --utt2spk=$dir/train.utt2spk $dir/train{,1,2,3}.tra
+scripts/split_scp.pl --utt2spk=$dir/train.utt2spk $dir/train{,1,2,3}.utt2spk
+
+for n in 1 2 3 ""; do # The "" handles the un-split one.  Creating spk2utt files..
+  scripts/utt2spk_to_spk2utt.pl $dir/train$n.utt2spk > $dir/train$n.spk2utt
+done
+
+
+# also see featspart below, used for sub-parts of the features;
+# try to keep them in sync.
+
+feats="ark,s,cs:splice-feats --print-args=false scp:$dir/train.scp ark:- | transform-feats $ldamat ark:- ark:- | transform-feats --utt2spk=ark:$dir/train.utt2spk \"ark:cat $dir/?.trans|\" ark:- ark:- |"
+for n in 1 2 3; do
+  featspart[$n]="ark,s,cs:splice-feats --print-args=false scp:$dir/train${n}.scp ark:- | transform-feats $ldamat ark:- ark:- | transform-feats --utt2spk=ark:$dir/train$n.utt2spk ark:$dir/$n.trans ark: ark:- |"
+  defaultfeatspart[$n]="ark,s,cs:splice-feats --print-args=false scp:$dir/train${n}.scp ark:- | transform-feats $defaultmat ark:- ark:- |"
+  ldafeatspart[$n]="ark,s,cs:splice-feats --print-args=false scp:$dir/train${n}.scp ark:- | transform-feats $ldamat ark:- ark:- |"
+done
+
+if [ ! -f $ubm ]; then
+  echo "No UBM in $ubm";
+  exit 1
+fi
+
+echo "Creating training graphs for model from $srcdir"
+rm -f $dir/.error
+for n in 1 2 3; do
+  compile-train-graphs $srcdir/tree $srcmodel  data/L.fst ark:$dir/train${n}.tra \
+     "ark:|gzip -c > $dir/srcgraphs${n}.fsts.gz" \
+     2>$dir/compile_src_graphs.${n}.log || touch $dir/.error &
+done
+wait
+[ -f $dir/.error ] &&  echo source-dir compile-graphs error && exit 1
+
+
+# Align all training data using old alignment model.
+
+echo "Aligning all training data with old alignment model"
+
+rm -f $dir/.error
+for n in 1 2 3; do
+   gmm-align-compiled $scale_opts --beam=8 --retry-beam=40 $srcalimodel \
+       "ark:gunzip -c $dir/srcgraphs${n}.fsts.gz|" "${defaultfeatspart[$n]}" \
+       "ark:|gzip -c >$dir/pre.${n}.ali.gz" \
+           2> $dir/pre_align.${n}.log || touch $dir/.error &
+done
+wait;
+[ -f $dir/.error ] &&  echo align error RE old system && exit 1
+
+echo "Computing ET transforms"
+
+for n in 1 2 3; do
+  ( ali-to-post "ark:gunzip -c $dir/pre.${n}.ali.gz|" ark:- | \
+    weight-silence-post 0.0 $silphonelist $srcalimodel ark:- ark:- | \
+    gmm-post-to-gpost $srcalimodel "${defaultfeatspart[$n]}" ark,o:- ark:- | \
+    gmm-est-et --spk2utt=ark:$dir/train$n.spk2utt --verbose=1 $srcmodel $et \
+    "${ldafeatspart[$n]}" ark,s,cs:- ark:$dir/$n.trans ark,t:$dir/$n.warp ) \
+       2> $dir/et_trans.$n.log || touch $dir/.error &
+done
+wait 
+[ -f $dir/.error ] && echo error aligning data && exit 1
+
+rm $dir/pre.${n}.ali.gz # remove first-pass alignments
+
+cp $srcdir/topo $dir
+
+# Align all training data using old model (and old graphs, since we
+# use the same data-subset as last time). 
+# Note: a small number of utterances don't have graphs at this stage because of differences
+# in how the data splitting is done when we switch to using speaker information.
+
+
+echo "Aligning all training data with old adapted model"
+
+rm -f $dir/.error
+for n in 1 2 3; do
+   gmm-align-compiled $scale_opts --beam=8 --retry-beam=40 $srcmodel \
+       "ark:gunzip -c $dir/srcgraphs${n}.fsts.gz|" "${featspart[$n]}" \
+       "ark:|gzip -c >$dir/0.${n}.ali.gz" \
+        2> $dir/old_align.${n}.log || touch $dir/.error &
+done
+wait;
+[ -f $dir/.error ] &&  echo align error RE old system && exit 1
+rm $dir/srcgraphs*.fsts.gz # These graphs no longer needed.
+
+acc-tree-stats  --ci-phones=$silphonelist $srcmodel "$feats" \
+  "ark:gunzip -c $dir/0.?.ali.gz|" $dir/treeacc 2> $dir/acc.tree.log  || exit 1;
+
+
+# The next few commands are involved with making the questions
+# for tree clustering.  The extra complexity vs. the RM recipe has
+# to do with the desire to ask questions about the "real" phones
+# ignoring things like stress and position-in-word, and ask questions
+# separately about stress and position-in-word.
+
+# Don't include silences as things to be clustered -> --nosil option.
+scripts/make_shared_phones.sh --nosil | scripts/sym2int.pl data/phones.txt > $dir/phone_sets.list
+cluster-phones $dir/treeacc $dir/phone_sets.list $dir/questions.txt 2> $dir/cluster_phones.log || exit 1;
+scripts/int2sym.pl data/phones.txt < $dir/questions.txt > $dir/questions_syms.txt
+scripts/make_extra_questions.sh | cat $dir/questions_syms.txt - > $dir/questions_syms_all.txt
+scripts/sym2int.pl data/phones.txt < $dir/questions_syms_all.txt > $dir/questions_all.txt
+
+compile-questions $dir/topo $dir/questions_all.txt $dir/questions.qst 2>$dir/compile_questions.log || exit 1;
+
+scripts/make_roots.sh > $dir/roots_syms.txt
+scripts/sym2int.pl --ignore-oov data/phones.txt  < $dir/roots_syms.txt > $dir/roots.txt
+
+build-tree --verbose=1 --max-leaves=$numleaves \
+  $dir/treeacc $dir/roots.txt \
+  $dir/questions.qst $dir/topo $dir/tree  2> $dir/train_tree.log || exit 1;
+
+# the sgmm-init program accepts a GMM, so we just create a temporary GMM "0.gmm"
+
+gmm-init-model  --write-occs=$dir/0.occs  \
+    $dir/tree $dir/treeacc $dir/topo $dir/0.gmm 2> $dir/init_gmm.log || exit 1;
+
+sgmm-init --spk-space-dim=40 $dir/topo $dir/tree $ubm $dir/0.mdl 2> $dir/init_sgmm.log || exit 1;
+
+rm $dir/0.gmm
+
+rm $dir/treeacc
+
+for n in 1 2 3; do
+  sgmm-gselect "--preselect=ark:gunzip -c $dir/preselect.${n}.gz|" \
+     $dir/0.mdl "${featspart[$n]}" ark,t:- 2>$dir/gselect$n.log | \
+     gzip -c > $dir/gselect${n}.gz || touch $dir/.error &
+done
+wait
+[ -f $dir/.error ] && echo "Error in gselect phase" && exit 1;
+
+
+# Convert alignments generated from previous model, to use as 
+# initial alignments.
+
+for n in 1 2 3; do
+  convert-ali $srcmodel $dir/0.mdl $dir/tree \
+      "ark:gunzip -c $dir/0.$n.ali.gz|" \
+      "ark:|gzip -c > $dir/cur$n.ali.gz" \
+     2>$dir/convert.$n.log || exit 1; # don't parallelize: mostly I/O.
+done
+rm $dir/0.?.ali.gz
+
+# Make training graphs
+echo "Compiling training graphs"
+
+rm -f $dir/.error
+for n in 1 2 3; do
+  compile-train-graphs $dir/tree $dir/0.mdl  data/L.fst ark:$dir/train${n}.tra \
+     "ark:|gzip -c > $dir/graphs${n}.fsts.gz" \
+     2>$dir/compile_graphs.${n}.log || touch $dir/.error &
+done
+wait
+[ -f $dir/.error ] &&  echo compile-graphs error && exit 1
+
+x=0
+while [ $x -lt $numiters ]; do
+   echo "Pass $x"
+   if echo $realign_iters | grep -w $x >/dev/null; then
+     echo "Aligning data"
+     rm -f $dir/.error
+     for n in 1 2 3; do
+       sgmm-align-compiled ${spkvecs_opt[$n]} --utt2spk=ark:$dir/train$n.utt2spk \
+            "--gselect=ark,s,cs:gunzip -c $dir/gselect$n.gz|" \
+           $scale_opts --beam=8 --retry-beam=40 $dir/$x.mdl \
+           "ark:gunzip -c $dir/graphs${n}.fsts.gz|" "${featspart[$n]}" \
+           "ark:|gzip -c >$dir/cur${n}.ali.gz" 2> $dir/align.$x.$n.log \
+             || touch $dir/.error &
+     done
+     wait 
+     [ -f $dir/.error ] && echo error aligning data && exit 1
+   fi
+   if echo $spkvec_iters | grep -w $x >/dev/null; then
+     echo "Computing speaker vectors"
+     for n in 1 2 3; do
+      ( ali-to-post "ark:gunzip -c $dir/cur${n}.ali.gz|" ark:- | \
+        weight-silence-post 0.01 $silphonelist $dir/$x.mdl ark:- ark:- | \
+        sgmm-est-spkvecs --spk2utt=ark:$dir/train$n.spk2utt ${spkvecs_opt[$n]} \
+         "--gselect=ark,s,cs:gunzip -c $dir/gselect$n.gz|" \
+          --rand-prune=$randprune $dir/$x.mdl \
+         "${featspart[$n]}" ark,s,cs:- ark:$dir/tmp$n.vecs && mv $dir/tmp$n.vecs $dir/cur$n.vecs ) 2>$dir/spkvecs.$x.$n.log \
+           || touch $dir/.error &
+        spkvecs_opt[$n]="--spk-vecs=ark:$dir/cur$n.vecs"
+     done
+     wait;
+
+     [ -f $dir/.error ] && echo error computing speaker vectors && exit 1    
+   fi  
+
+   if [ $x -eq 0 ]; then
+     flags=vwcS
+   elif [ $[$x%2] -eq 1 -a $x -gt 4 ]; then # even iters after 4 (i.e. starting from 6)...
+     flags=vNwcS
+   else
+     flags=vMwcS
+   fi
+
+   for n in 1 2 3; do
+     sgmm-acc-stats-ali ${spkvecs_opt[$n]} --utt2spk=ark:$dir/train$n.utt2spk \
+       --update-flags=$flags "--gselect=ark,s,cs:gunzip -c $dir/gselect$n.gz|" \
+       --rand-prune=$randprune --binary=true $dir/$x.mdl "${featspart[$n]}" \
+      "ark:gunzip -c $dir/cur$n.ali.gz|" $dir/$x.$n.acc 2> $dir/acc.$x.$n.log \