Adding fMPE scripts; changes to fMPE code.

git-svn-id: https://svn.code.sf.net/p/kaldi/code/trunk@772 5e6a8d80-dfce-4ca6-a32a-6e07a63d50c8

COPYING

 
+ Update to legal notice, made Feb. 2012.  We would like to clarify that we
+ are using a convention where multiple names in the Apache copyright headers, 
+ for example
+
+  // Copyright 2009-2012  Yanmin Qian  Arnab Ghoshal
+
+ does not necessarily signify joint ownership of copyright of that file, except
+ in cases where all those names were present in the original release made in
+ March 2011-- you can use the version history to work this out, if this matters
+ to you.  Instead, we intend that those contributors who later modified the file, 
+ agree to release their changes under the Apache license, but do not claim to 
+ jointly own the copyright of the original material (which would require an agreement 
+ with the original contributors).  The conventional way of signifying 
+ this is to duplicate the Apache headers at the top of each file each time
+ a change is made by a different author, but this would quickly become impractical.
+
+ The original legal notice is below.  Note: we are continuing to modify it by
+ adding the names of new contributors.
+
+---
                           Legal Notices
 
 Each of the files comprising Kaldi v1.0 have been separately licensed by
@@ -18,6 +38,7 @@ Individual Contributors (in alphabetical order)
       Arnab Ghoshal
       Go Vivace Inc.
       Mirko Hannemann
+      Navdeep Jaitly
       Microsoft Corporation
       Petr Motlicek
       Ariya Rastrow

egs/README.txt

@@ -26,4 +26,7 @@ Recipes in progress:
     sampling rate).
     This directory is a work in progress.
   
+
  gp: GlobalPhone.  This is a multilingual speech corpus.
+
+ timit: TIMIT, which is an old corpus of carefully read speech.  

egs/gp/s1/run.sh

@@ -28,7 +28,7 @@ exit 1;
 # shorten to WAV to take out the empty files and those with compression errors. 
 # So set WORKDIR to someplace with enough disk space. That is where MFCCs will 
 # get created, as well as the FST versions of LMs.
-WORKDIR=/path/with/disk/space
+WORKDIR=/mnt/matylda6/jhu09/qpovey/temp_gp
 cp -r conf local utils steps install.sh path.sh $WORKDIR
 cd $WORKDIR
 # INSTALLING REQUIRED TOOLS:
@@ -39,7 +39,7 @@ cd $WORKDIR
   { echo "shorten and/or sox not found on PATH. Installing..."; 
     install.sh }
 
-local/gp_data_prep.sh --config-dir=$PWD/conf --corpus-dir=/path/to/GlobalPhone --lm-dir=/path/to/lms --work-dir=$WORKDIR
+local/gp_data_prep.sh --config-dir=$PWD/conf --corpus-dir=/mnt/matylda2/data/GLOBALPHONE --lm-dir=/path/to/lms --work-dir=$WORKDIR
 # On Eddie: local/gp_data_prep.sh --config-dir=$PWD/conf --corpus-dir=$PWD/corpus --lm-dir=$PWD/corpus/language_models --work-dir=$PWD
 
 local/gp_format_data.sh --hmm-proto=conf/topo.proto --work-dir=$PWD

egs/rm/s3/RESULTS

@@ -5,38 +5,38 @@ for x in exp/*/decode*; do [ -d $x ] && grep WER $x/wer_* | scripts/best_wer.sh;
 # monophone; delta+accel
 exp/mono/decode/wer_4:%WER 9.830049 [ 1232 / 12533, 143 ins, 289 del, 800 sub ]
 # First triphone pass; delta+accel
-exp/tri1/decode/wer_6:%WER 3.694247 [ 463 / 12533, 69 ins, 100 del, 294 sub ]
+exp/tri1/decode/wer_6:%WER 3.893721 [ 488 / 12533, 69 ins, 96 del, 323 sub ]
 # Second triphone pass; delta+accel
-exp/tri2a/decode/wer_7:%WER 3.638395 [ 456 / 12533, 61 ins, 107 del, 288 sub ]
+exp/tri2a/decode/wer_7:%WER 3.486795 [ 437 / 12533, 65 ins, 91 del, 281 sub ]
 # [as tri2a, but] LDA+MLLT
-exp/tri2b/decode/wer_7:%WER 3.534668 [ 443 / 12533, 74 ins, 88 del, 281 sub ]
+exp/tri2b/decode/wer_6:%WER 3.359132 [ 421 / 12533, 73 ins, 71 del, 277 sub ]
 # LDA + exponential transform (note: this is with speaker adaptation)
-exp/tri2c/decode/wer_5:%WER 2.848480 [ 357 / 12533, 62 ins, 61 del, 234 sub ]
+exp/tri2c/decode/wer_5:%WER 2.905492 [ 364 / 12528, 68 ins, 59 del, 237 sub ]
 # LDA+MLLT+MMI.
-exp/tri3a/decode/wer_7:%WER 3.502753 [ 439 / 12533, 75 ins, 83 del, 281 sub ]
+exp/tri3a/decode/wer_7:%WER 3.084052 [ 386 / 12516, 54 ins, 67 del, 265 sub ]
 # LDA+MLLT+boosted MMI [note: errors are not identical, although WER is same]
-exp/tri3b/decode/wer_7:%WER 3.454879 [ 433 / 12533, 75 ins, 80 del, 278 sub ]
+exp/tri3b/decode/wer_5:%WER 3.155960 [ 395 / 12516, 74 ins, 50 del, 271 sub ]
 # LDA+MLLT+MCE
-exp/tri3c/decode/wer_7:%WER 3.183595 [ 399 / 12533, 62 ins, 79 del, 258 sub ]
+exp/tri3c/decode/wer_6:%WER 3.047953 [ 382 / 12533, 56 ins, 69 del, 257 sub ]
 # LDA+MLLT+SAT
-exp/tri3d/decode/wer_6:%WER 2.553259 [ 320 / 12533, 43 ins, 63 del, 214 sub ]
+exp/tri3d/decode/wer_7:%WER 2.234102 [ 280 / 12533, 35 ins, 62 del, 183 sub ]
 # LDA+MLLT+SAT+MMI
-exp/tri4a/decode/wer_6:%WER 2.473470 [ 310 / 12533, 43 ins, 62 del, 205 sub ]
+exp/tri4a/decode/wer_6:%WER 2.146334 [ 269 / 12533, 37 ins, 43 del, 189 sub ]
 # LDA+MLLT+SAT, extra phase of builting on top of 3d (no help)
-exp/tri4d/decode/wer_5:%WER 2.800606 [ 351 / 12533, 47 ins, 68 del, 236 sub ]
+exp/tri4d/decode/wer_5:%WER 2.457512 [ 308 / 12533, 50 ins, 54 del, 204 sub ]
 # LDA+MLLT + SGMM with speaker vectors
-exp/sgmm3d/decode/wer_4:%WER 2.186228 [ 274 / 12533, 41 ins, 42 del, 191 sub ]
+exp/sgmm3d/decode/wer_6:%WER 2.305912 [ 289 / 12533, 53 ins, 52 del, 184 sub ]
 # LDA+ET + SGMM with speaker vectors.
-exp/sgmm3e/decode/wer_5:%WER 2.242081 [ 281 / 12533, 44 ins, 47 del, 190 sub ]
+exp/sgmm3e/decode/wer_4:%WER 2.042608 [ 256 / 12533, 39 ins, 38 del, 179 sub ]
 # LDA+MLLT+SAT + SGMM with speaker vectors.
-exp/sgmm4f/decode/wer_5:%WER 2.226123 [ 279 / 12533, 56 ins, 49 del, 174 sub ]
+exp/sgmm4f/decode/wer_7:%WER 1.970797 [ 247 / 12533, 36 ins, 56 del, 155 sub ]
 # + FMLLR on top of it all.
-exp/sgmm4f/decode_fmllr/wer_6:%WER 2.202186 [ 276 / 12533, 39 ins, 59 del, 178 sub ]
+exp/sgmm4f/decode_fmllr/wer_5:%WER 1.954839 [ 245 / 12533, 40 ins, 47 del, 158 sub ]
 
 # System combination via lattices: combine tri1 and tri2a
 exp/combine_1_2a/decode/wer_6:%WER 3.518711 [ 441 / 12533, 62 ins, 97 del, 282 sub ]
 # System combination via lattices: combine sgmm4f and tri3d.
-exp/combine_sgmm4f_tri3d/decode/wer_5:%WER 2.082502 [ 261 / 12533, 36 ins, 48 del, 177 sub ]
+exp/combine_sgmm4f_tri3d/decode/wer_5:%WER 1.763345 [ 221 / 12533, 32 ins, 42 del, 147 sub ]
 # System combination via lattices: combine sgmm4f and tri4a.
-exp/combine_sgmm4f_tri4a/decode/wer_5:%WER 2.082502 [ 261 / 12533, 37 ins, 49 del, 175 sub ]
+exp/combine_sgmm4f_tri4a/decode/wer_6:%WER 1.715471 [ 215 / 12533, 31 ins, 39 del, 145 sub ]
 

egs/rm/s3/steps/train_lda_etc_mmi.sh

 #!/bin/bash
-# Copyright 2010-2011 Microsoft Corporation
+# Copyright 2010-2012 Microsoft Corporation  Daniel Povey
 
 # Licensed under the Apache License, Version 2.0 (the "License");
 # you may not use this file except in compliance with the License.
@@ -27,13 +27,24 @@
 #  ali, final.mdl, final.mat
 
 boost=0 # boosting constant, for boosted MMI. 
-tau=100 # Tau value.
-
-if [ $1 == "--boost" ]; then # e.g. "--boost 0.05"
-   shift;
-   boost=$1;
-   shift;
-fi
+tau=200 # Tau value.
+merge=true # if true, cancel num and den counts as described in 
+    # the boosted MMI paper. 
+
+for x in `seq 4`; do
+  if [ $1 == "--boost" ]; then # e.g. "--boost 0.05"
+    boost=$2;
+    shift 2;
+  fi
+  if [ $1 == "--smooth-to-model" ]; then 
+    shift;
+    smooth_to_model=true
+  fi
+  if [ $1 == "--tau" ]; then # e.g. "--tau 200
+    tau=$2
+    shift 2;
+  fi
+done
 
 if [ $# != 4 ]; then
    echo "Usage: steps/train_lda_etc_mmi.sh <data-dir> <lang-dir> <ali-dir> <exp-dir>"
@@ -99,7 +110,7 @@ scripts/mkgraph.sh $dir/lang $alidir $dir/dengraph || exit 1;
 
 echo "Making denominator lattices"
 
-
+ if false; then ##temp
 rm $dir/.error 2>/dev/null
 for n in 0 1 2 3; do
    gmm-latgen-simple --beam=$beam --lattice-beam=$latticebeam --acoustic-scale=$acwt \
@@ -113,45 +124,33 @@ if [ -f $dir/.error ]; then
    echo "Error creating denominator lattices"
    exit 1;
 fi
+ fi ##temp
 
 # No need to create "numerator" alignments/lattices: we just use the 
 # alignments in $alidir.
 
-echo "Note: ignore absolute offsets in the objective function values"
-echo "This is caused by not having LM, lexicon or transition-probs in numerator"
-
 x=0;
 while [ $x -lt $num_iters ]; do
-  echo "Iteration $x: getting denominator stats."
-  # Get denominator stats...
-  if [ $x -eq 0 ]; then
-    ( lattice-to-post --acoustic-scale=$acwt "ark:gunzip -c $dir/lat?.gz|" ark:- | \
-      gmm-acc-stats $dir/$x.mdl "$feats" ark:- $dir/den_acc.$x.acc ) \
-     2>$dir/acc_den.$x.log || exit 1;
-  else # Need to recompute acoustic likelihoods...
-   ( gmm-rescore-lattice $dir/$x.mdl "ark:gunzip -c $dir/lat?.gz|" "$feats" ark:- | \
-      lattice-to-post --acoustic-scale=$acwt ark:- ark:- | \
-      gmm-acc-stats $dir/$x.mdl "$feats" ark:- $dir/den_acc.$x.acc ) \
-     2>$dir/acc_den.$x.log || exit 1;
-  fi
-  echo "Iteration $x: getting numerator stats."
-  # Get numerator stats...
-  gmm-acc-stats-ali $dir/$x.mdl "$feats" ark:$alidir/ali $dir/num_acc.$x.acc \
-   2>$dir/acc_num.$x.log || exit 1;
-
-  ( gmm-est-gaussians-ebw $dir/$x.mdl "gmm-ismooth-stats --tau=$tau $dir/num_acc.$x.acc $dir/num_acc.$x.acc -|" \
-         $dir/den_acc.$x.acc - | \
+  echo "Iteration $x: getting  stats."
+  ( gmm-rescore-lattice $dir/$x.mdl "ark:gunzip -c $dir/lat?.gz|" "$feats" ark:- | \
+   lattice-to-post --acoustic-scale=$acwt ark:- ark:- | \
+   sum-post --merge=$merge --scale1=-1 \
+    ark:- "ark,s,cs:ali-to-post ark:$alidir/ali ark:- |" ark:- | \
+   gmm-acc-stats2 $dir/$x.mdl "$feats" ark:- $dir/num_acc.$x.acc $dir/den_acc.$x.acc ) \
+     2>$dir/acc.$x.log || exit 1;
+
+  # This tau is only used for smoothing "to the model".
+  ( gmm-est-gaussians-ebw --tau=$tau $dir/$x.mdl $dir/num_acc.$x.acc $dir/den_acc.$x.acc - | \
    gmm-est-weights-ebw - $dir/num_acc.$x.acc $dir/den_acc.$x.acc $dir/$[$x+1].mdl ) \
     2>$dir/update.$x.log || exit 1;
 
-  den=`grep Overall $dir/acc_den.$x.log  | grep lattice-to-post | awk '{print $7}'`
-  num=`grep Overall $dir/acc_num.$x.log  | grep gmm-acc-stats-ali | awk '{print $11}'`
-  diff=`perl -e "print ($num * $acwt - $den);"`
-  impr=`grep Overall $dir/update.$x.log | head -1 | awk '{print $10;}'`
-  impr=`perl -e "print ($impr * $acwt);"` # auxf impr normalized by multiplying by
-  # kappa, so it's comparable to an objective-function change.
-  echo On iter $x, objf was $diff, auxf improvement was $impr | tee $dir/objf.$x.log
-
+  objf=`grep Overall $dir/acc.$x.log  | grep gmm-acc-stats2 | awk '{print $10}'`
+  nf=`grep Overall $dir/acc.$x.log  | grep gmm-acc-stats2 | awk '{print $12}'`
+  impr=`grep Overall $dir/log/update.$x.log | head -1 | awk '{print $10*$12;}'`
+  impr=`perl -e "print ($impr/$nf);"` # renormalize by "real" #frames, to correct
+    # for the canceling of stats.
+  echo On iter $x, objf was $objf, auxf improvement from MMI was $impr | tee $dir/objf.$x.log
+  rm $dir/*.acc
   x=$[$x+1]
 done
 

egs/timit/s1/conf/mfcc.conf

+--use-energy=false   # only non-default option.

egs/timit/s1/conf/topo.proto

+<Topology> 
+<TopologyEntry> 
+<ForPhones>
+NONSILENCEPHONES
+</ForPhones> 
+<State> 0 <PdfClass> 0 <Transition> 0 0.75 <Transition> 1 0.25 </State> 
+<State> 1 <PdfClass> 1 <Transition> 1 0.75 <Transition> 2 0.25 </State> 
+<State> 2 <PdfClass> 2 <Transition> 2 0.75 <Transition> 3 0.25 </State> 
+<State> 3 </State>
+</TopologyEntry> 
+<TopologyEntry> 
+<ForPhones>
+SILENCEPHONES
+</ForPhones> 
+<State> 0 <PdfClass> 0 <Transition> 0 0.25 <Transition> 1 0.25 <Transition> 2 0.25 <Transition> 3 0.25 </State> 
+<State> 1 <PdfClass> 1 <Transition> 1 0.25 <Transition> 2 0.25 <Transition> 3 0.25 <Transition> 4 0.25 </State> 
+<State> 2 <PdfClass> 2 <Transition> 1 0.25 <Transition> 2 0.25 <Transition> 3 0.25 <Transition> 4 0.25 </State> 
+<State> 3 <PdfClass> 3 <Transition> 1 0.25 <Transition> 2 0.25 <Transition> 3 0.25 <Transition> 4 0.25 </State> 
+<State> 4 <PdfClass> 4 <Transition> 4 0.25 <Transition> 5 0.75 </State> 
+<State> 5 </State>
+</TopologyEntry> 
+</Topology> 

egs/timit/s1/steps/train_mono.sh

@@ -103,4 +103,3 @@ done
 
 # example of showing the alignments:
 # show-alignments data/lang/phones.txt $dir/30.mdl ark:$dir/cur.ali | head -4
-

egs/timit/s3/run.sh

 . path.sh
-local/timit_data_prep.sh /ais/gobi2/speech/TIMIT
-local/timit_train_lms.sh data/local
-local/timit_format_data.sh
+#local/timit_data_prep.sh /ais/gobi2/speech/TIMIT
+local/timit_data_prep.sh /mnt/matylda2/data/TIMIT || exit 1;
+local/timit_train_lms.sh data/local || exit 1;
+local/timit_format_data.sh || exit 1;
 
 # mfccdir should be some place with a largish disk where you
 # want to store MFCC features. 
@@ -9,13 +10,13 @@ mfccdir=mfccs
 
 steps/make_mfcc.sh data/train exp/make_mfcc/train $mfccdir 4
 for test in train test dev ; do
-  steps/make_mfcc.sh data/$test exp/make_mfcc/$test $mfccdir 4
+  steps/make_mfcc.sh data/$test exp/make_mfcc/$test $mfccdir 4 || exit 1;
 done
 
 # train monophone system.
-steps/train_mono.sh data/train data/lang exp/mono
+steps/train_mono.sh data/train data/lang exp/mono || exit 1;
 
-scripts/mkgraph.sh --mono data/lang_test exp/mono exp/mono/graph
+scripts/mkgraph.sh --mono data/lang_test exp/mono exp/mono/graph || exit 1;
 echo "Decoding test datasets."
 for test in dev test ; do
   steps/decode_deltas.sh exp/mono data/$test data/lang exp/mono/decode_$test &
@@ -25,8 +26,7 @@ scripts/average_wer.sh exp/mono/decode_*/wer > exp/mono/wer
 
 # Get alignments from monophone system.
 echo "Creating training alignments to use to train other systems such as ANN-HMM."
-steps/align_deltas.sh data/train data/lang exp/mono exp/mono_ali
+steps/align_deltas.sh data/train data/lang exp/mono exp/mono_ali || exit 1;
 echo "Creating dev alignments to use to train other systems such as ANN-HMM."
-steps/align_deltas.sh data/dev data/lang exp/mono exp/mono_ali_dev
-
+steps/align_deltas.sh data/dev data/lang exp/mono exp/mono_ali_dev || exit 1;
 

egs/wsj/s3/RESULTS

@@ -22,12 +22,15 @@ exp/tri2b/decode_tgpr_dev93_fromlats/wer_15:%WER 16.71 [ 1376 / 8234, 267 ins, 1
 exp/tri2b/decode_tgpr_dev93_tg/wer_16:%WER 16.26 [ 1339 / 8234, 267 ins, 141 del, 931 sub ]
 exp/tri2b/decode_tgpr_dev93_tg_biglm/wer_16:%WER 16.42 [ 1352 / 8234, 269 ins, 142 del, 941 sub ]
 
-exp/tri2b/decode_tgpr_eval92/wer_16:%WER 11.54 [ 651 / 5643, 146 ins, 42 del, 463 sub ]
+exp/tri2b/decode_tgpr_eval92/wer_17:%WER 11.45 [ 646 / 5643, 140 ins, 46 del, 460 sub ]
 
 # +MMI
-exp/tri2b_mmi/decode_tgpr_eval92/wer_16:%WER 11.08 [ 625 / 5643, 125 ins, 44 del, 456 sub ]
+exp/tri2b_mmi/decode_tgpr_eval92/wer_14:%WER 10.63 [ 600 / 5643, 124 ins, 45 del, 431 sub ]
 #  +boosting
-exp/tri2b_mmi_b0.1/decode_tgpr_eval92/wer_16:%WER 10.83 [ 611 / 5643, 122 ins, 43 del, 446 sub ]
+exp/tri2b_mmi_b0.1/decode_tgpr_eval92/wer_16:%WER 10.69 [ 603 / 5643, 119 ins, 48 del, 436 sub ]
+# +fMMI
+exp/tri2b_fmmi_b0.1/decode_tgpr_eval92/wer_15:%WER 10.26 [ 579 / 5643, 111 ins, 39 del, 429 sub ]
+
 # +MCE
 exp/tri2b_mce/decode_tgpr_eval92/wer_16:%WER 11.15 [ 629 / 5643, 132 ins, 45 del, 452 sub ]
 
@@ -69,8 +72,17 @@ exp/tri4b/decode_tgpr_dev93/wer_13:%WER 12.53 [ 1032 / 8234, 242 ins, 79 del, 71
 exp/tri4b/decode_tgpr_eval92/wer_16:%WER 8.05 [ 454 / 5643, 119 ins, 23 del, 312 sub ]
 
 # +MMI
-exp/tri4b_mmi/decode_tgpr_dev93/wer_14:%WER 11.53 [ 949 / 8234, 203 ins, 82 del, 664 sub ]
-exp/tri4b_mmi_b0.1/decode_tgpr_dev93/wer_16:%WER 11.45 [ 943 / 8234, 191 ins, 87 del, 665 sub ]
+exp/tri4b_mmi/decode_tgpr_dev93/wer_12:%WER 11.28 [ 929 / 8234, 206 ins, 76 del, 647 sub ]
+#+boosting
+exp/tri4b_mmi_b0.1/decode_tgpr_dev93/wer_16:%WER 11.25 [ 926 / 8234, 176 ins, 94 del, 656 sub ]
+ # increasing beam from 13 to 15 to see effect. 
+ exp/tri4b_mmi_b0.1/decode_tgpr_dev93_b15/wer_14:%WER 10.72 [ 883 / 8234, 172 ins, 84 del, 627 sub ]
+exp/tri4b_mmi_b0.1/decode_tgpr_eval92/wer_14:%WER 7.34 [ 414 / 5643, 105 ins, 20 del, 289 sub ]
+
+#+fMMI
+exp/tri4b_fmmi_b0.1/decode_tgpr_dev93/wer_13:%WER 10.86 [ 894 / 8234, 167 ins, 89 del, 638 sub ]
+exp/tri4b_fmmi_b0.1/decode_tgpr_eval92/wer_12:%WER 7.25 [ 409 / 5643, 111 ins, 14 del, 284 sub ]
+
 
 # LDA+MLLT+SAT, SI-284, full retraining starting from 3b [c.f. 4b]
 exp/tri4c/decode_tgpr_dev93/wer_16:%WER 12.10 [ 996 / 8234, 220 ins, 83 del, 693 sub ]

egs/wsj/s3/run.sh

@@ -164,6 +164,18 @@ steps/train_lda_etc_mmi.sh --num-jobs 10 --boost 0.1 --cmd "$train_cmd" \
   data/train_si84 data/lang exp/tri2b_ali_si84 exp/tri2b_denlats_si84 exp/tri2b exp/tri2b_mmi_b0.1
 scripts/decode.sh --cmd "$decode_cmd" steps/decode_lda_mllt.sh exp/tri2b/graph_tgpr data/test_eval92 exp/tri2b_mmi_b0.1/decode_tgpr_eval92
 
+ # The next 3 commands train and test fMMI+MMI (on top of LDA+MLLT).
+ steps/train_dubm_lda_etc.sh --silence-weight 0.5 \
+   --num-jobs 10 --cmd "$train_cmd" 400 data/train_si84 \
+   data/lang exp/tri2b_ali_si84 exp/dubm2b
+ steps/train_lda_etc_mmi_fmmi.sh \
+   --num-jobs 10 --boost 0.1 --cmd "$train_cmd" \
+   data/train_si84 data/lang exp/tri2b_ali_si84 exp/dubm2b exp/tri2b_denlats_si84 \
+   exp/tri2b exp/tri2b_fmmi_b0.1
+ scripts/decode.sh --cmd "$decode_cmd" steps/decode_lda_mllt_fmpe.sh \
+   exp/tri2b/graph_tgpr data/test_eval92 exp/tri2b_fmmi_b0.1/decode_tgpr_eval92
+
+
 steps/train_lda_etc_mce.sh --cmd "$train_cmd" --num-jobs 10 data/train_si84 data/lang \
  exp/tri2b_ali_si84 exp/tri2b_denlats_si84 exp/tri2b exp/tri2b_mce
  scripts/decode.sh --num-jobs 10 --cmd "$decode_cmd" steps/decode_lda_mllt.sh \
@@ -222,7 +234,8 @@ scripts/mkgraph.sh data/lang_test_tgpr exp/tri4b exp/tri4b/graph_tgpr
 scripts/decode.sh --cmd "$decode_cmd" steps/decode_lda_mllt_sat.sh exp/tri4b/graph_tgpr data/test_dev93 exp/tri4b/decode_tgpr_dev93
 scripts/decode.sh --cmd "$decode_cmd" steps/decode_lda_mllt_sat.sh exp/tri4b/graph_tgpr data/test_eval92 exp/tri4b/decode_tgpr_eval92
 
-# Train and test MMI, and boosted MMI, on tri4b.
+# Train and test MMI, and boosted MMI, on tri4b (LDA+MLLT+SAT on
+# all the data).
 # Making num-jobs 40 as want to keep them under 4 hours long (or will fail
 # on regular queue at BUT).
 steps/align_lda_mllt_sat.sh --num-jobs 40 --cmd "$train_cmd" \
@@ -235,6 +248,25 @@ scripts/decode.sh --cmd "$decode_cmd" steps/decode_lda_etc.sh exp/tri4b/graph_tg
 steps/train_lda_etc_mmi.sh --boost 0.1 --num-jobs 40 --cmd "$train_cmd" \
   data/train_si284 data/lang exp/tri4b_ali_si284 exp/tri4b_denlats_si284 exp/tri4b exp/tri4b_mmi_b0.1
 scripts/decode.sh --cmd "$decode_cmd" steps/decode_lda_etc.sh exp/tri4b/graph_tgpr data/test_dev93 exp/tri4b_mmi_b0.1/decode_tgpr_dev93 exp/tri4b/decode_tgpr_dev93
+ scripts/decode.sh --opts "--beam 15" --cmd "$decode_cmd" steps/decode_lda_etc.sh exp/tri4b/graph_tgpr data/test_dev93 exp/tri4b_mmi_b0.1/decode_tgpr_dev93_b15 exp/tri4b/decode_tgpr_dev93
+scripts/decode.sh --cmd "$decode_cmd" steps/decode_lda_etc.sh exp/tri4b/graph_tgpr data/test_eval92 exp/tri4b_mmi_b0.1/decode_tgpr_eval92 exp/tri4b/decode_tgpr_eval92
+
+ # Train fMMI+MMI system on top of 4b.
+ steps/train_dubm_lda_etc.sh --silence-weight 0.5 \
+   --num-jobs 40 --cmd "$train_cmd" 600 data/train_si284 \
+   data/lang exp/tri4b_ali_si284 exp/dubm4b
+ steps/train_lda_etc_mmi_fmmi.sh \
+   --num-jobs 40 --boost 0.1 --cmd "$train_cmd" \
+   data/train_si284 data/lang exp/tri4b_ali_si284 exp/dubm4b exp/tri4b_denlats_si284 \
+   exp/tri4b exp/tri4b_fmmi_b0.1 
+ scripts/decode.sh --cmd "$decode_cmd" steps/decode_lda_etc_fmpe.sh \
+   exp/tri4b/graph_tgpr data/test_eval92 exp/tri4b_fmmi_b0.1/decode_tgpr_eval92 \
+   exp/tri4b/decode_tgpr_eval92
+ scripts/decode.sh --cmd "$decode_cmd" steps/decode_lda_etc_fmpe.sh \
+   exp/tri4b/graph_tgpr data/test_dev93 exp/tri4b_fmmi_b0.1/decode_tgpr_dev93 \
+   exp/tri4b/decode_tgpr_dev93
+
+
 
 # Train UBM, for SGMM system on top of LDA+MLLT.
 steps/train_ubm_lda_etc.sh --num-jobs 10 --cmd "$train_cmd" \
@@ -245,6 +277,7 @@ scripts/mkgraph.sh data/lang_test_tgpr exp/sgmm3c exp/sgmm3c/graph_tgpr
 scripts/decode.sh --cmd "$decode_cmd" steps/decode_sgmm_lda_etc.sh exp/sgmm3c/graph_tgpr \
   data/test_dev93 exp/sgmm3c/decode_tgpr_dev93
 
+
 # Decode using 3 Gaussians (not 15) for gselect in 1st pass, for fast decoding.
 scripts/decode.sh --opts "--first-pass-gselect 3" --cmd "$decode_cmd" \
   steps/decode_sgmm_lda_etc.sh exp/sgmm3c/graph_tgpr data/test_dev93 exp/sgmm3c/decode_tgpr_dev93_gs3

egs/wsj/s3/steps/decode_lda_etc.sh

@@ -62,7 +62,7 @@ fi
 requirements="$mydata/feats.scp $srcdir/final.mdl $srcdir/final.mat $graphdir/HCLG.fst $transdir/$jobid.trans"
 for f in $requirements; do
   if [ ! -f $f ]; then
-     echo "decode_lda_mllt.sh: no such file $f";
+     echo "decode_lda_etc.sh: no such file $f";
      exit 1;
   fi
 done

egs/wsj/s3/steps/decode_lda_etc_fmpe.sh

+#!/bin/bash
+
+# Decoding script for LDA + optionally MLLT + [some speaker-specific transforms]
+# + fMPE.
+# This decoding script takes as an argument a previous decoding directory where it
+# can find some transforms.
+
+if [ -f ./path.sh ]; then . ./path.sh; fi
+
+numjobs=1
+jobid=0
+beam=13.0
+rescore=false
+for x in `seq 3`; do
+  if [ "$1" == "-j" ]; then
+    shift;
+    numjobs=$1;
+    jobid=$2;
+    shift 2;
+  fi
+  if [ "$1" == "--beam" ]; then
+    beam=$2;
+    shift 2;
+  fi
+done
+
+if [ $# != 4 ]; then
+   # Note: transform-dir has to be last because scripts/decode.sh expects decode-dir to be #3 arg.
+   echo "Usage: steps/decode_lda_etc.sh [-j num-jobs job-number] <graph-dir> <data-dir> <decode-dir> <transform-dir>"
+   echo " e.g.: steps/decode_lda_etc.sh -j 8 0 exp/tri4b/graph_tgpr data/test_dev93 exp/tri4b_mmi/decode_tgpr_dev93 exp/tri4b/decode_tgpr_dev93"
+   exit 1;
+fi
+
+
+graphdir=$1
+data=$2
+dir=$3
+transdir=$4
+srcdir=`dirname $dir`; # Assume model directory one level up from decoding directory.
+
+mkdir -p $dir
+
+if [ $numjobs -gt 1 ]; then
+  mydata=$data/split$numjobs/$jobid
+else
+  mydata=$data
+fi
+
+requirements="$mydata/feats.scp $srcdir/final.mdl $srcdir/final.fmpe $srcdir/final.mat $graphdir/HCLG.fst $transdir/$jobid.trans"
+for f in $requirements; do
+  if [ ! -f $f ]; then
+     echo "decode_lda_etc_fmpe.sh: no such file $f";
+     exit 1;
+  fi
+done
+
+
+basefeats="ark:compute-cmvn-stats --spk2utt=ark:$mydata/spk2utt scp:$mydata/feats.scp ark:- | apply-cmvn --norm-vars=false --utt2spk=ark:$mydata/utt2spk ark:- scp:$mydata/feats.scp ark:- | splice-feats ark:- ark:- | transform-feats $srcdir/final.mat ark:- ark:- | transform-feats --utt2spk=ark:$mydata/utt2spk ark:$transdir/$jobid.trans ark:- ark:- |"
+
+# Get the Gaussian-selection info for the fMPE.  
+ngselect=2; # Just the 2 top Gaussians. 
+gmm-gselect --n=$ngselect $srcdir/final.fmpe "$basefeats" \
+  "ark:|gzip -c >$dir/gselect.$jobid.gz" 2>$dir/gselect.$jobid.log
+
+
+# Now set up the fMPE features.
+feats="$basefeats fmpe-apply-transform $srcdir/final.fmpe ark:- 'ark,s,cs:gunzip -c $dir/gselect.$jobid.gz|' ark:- |"
+
+gmm-latgen-faster --max-active=7000 --beam=$beam --lattice-beam=6.0 \
+  --acoustic-scale=0.083333 \
+  --allow-partial=true --word-symbol-table=$graphdir/words.txt \
+  $srcdir/final.mdl $graphdir/HCLG.fst "$feats" "ark:|gzip -c > $dir/lat.$jobid.gz" \
+     2> $dir/decode$jobid.log || exit 1;

egs/wsj/s3/steps/decode_lda_mllt_fmpe.sh

+#!/bin/bash
+
+# Decoding script that works with a GMM model and the baseline
+# [e.g. MFCC] features plus cepstral mean subtraction plus
+# LDA+MLLT or similar transform, plus fMPE/FMMI.
+# This script just generates lattices for a single broken-up
+# piece of the data.
+
+if [ -f ./path.sh ]; then . ./path.sh; fi
+
+numjobs=1
+jobid=0
+rescore=false
+if [ "$1" == "-j" ]; then
+  shift;
+  numjobs=$1;
+  jobid=$2;
+  shift; shift;
+fi
+
+if [ $# != 3 ]; then
+   echo "Usage: steps/decode_lda_mllt_fmpe.sh [-j num-jobs job-number] <graph-dir> <data-dir> <decode-dir>"
+   echo " e.g.: steps/decode_lda_mllt_fmpe.sh -j 8 0 exp/tri2b/graph_tgpr data/test_dev93 exp/tri2b_fmmi/decode_dev93_tgpr"
+   exit 1;
+fi
+
+
+graphdir=$1
+data=$2
+dir=$3
+srcdir=`dirname $dir`; # Assume model directory one level up from decoding directory.
+
+mkdir -p $dir
+
+if [ $numjobs -gt 1 ]; then
+  mydata=$data/split$numjobs/$jobid
+else
+  mydata=$data
+fi
+
+requirements="$mydata/feats.scp $srcdir/final.mdl $srcdir/final.fmpe $srcdir/final.mat $graphdir/HCLG.fst"
+for f in $requirements; do
+  if [ ! -f $f ]; then
+     echo "decode_lda_mllt_fmpe.sh: no such file $f";
+     exit 1;
+  fi
+done
+
+
+basefeats="ark:compute-cmvn-stats --spk2utt=ark:$mydata/spk2utt scp:$mydata/feats.scp ark:- | apply-cmvn --norm-vars=false --utt2spk=ark:$mydata/utt2spk ark:- scp:$mydata/feats.scp ark:- | splice-feats ark:- ark:- | transform-feats $srcdir/final.mat ark:- ark:- |"
+
+# Get the Gaussian-selection info for the fMPE.  
+ngselect=2; # Just the 2 top Gaussians. 
+gmm-gselect --n=$ngselect $srcdir/final.fmpe "$basefeats" \
+  "ark:|gzip -c >$dir/gselect.$jobid.gz" 2>$dir/gselect.$jobid.log
+
+# Now set up the fMPE features.
+feats="$basefeats fmpe-apply-transform $srcdir/final.fmpe ark:- 'ark,s,cs:gunzip -c $dir/gselect.$jobid.gz|' ark:- |"
+
+gmm-latgen-faster --max-active=7000 --beam=13.0 --lattice-beam=6.0 --acoustic-scale=0.083333 \
+  --allow-partial=true --word-symbol-table=$graphdir/words.txt \
+  $srcdir/final.mdl $graphdir/HCLG.fst "$feats" "ark:|gzip -c > $dir/lat.$jobid.gz" \
+     2> $dir/decode.$jobid.log || exit 1;
+

egs/wsj/s3/steps/train_dubm_lda_etc.sh

+#!/bin/bash
+
+# This trains a diagonal-covariance UBM (i.e. just a global
+# mixture of Gaussians, or GMM).
+
+# Train UBM from a trained HMM/GMM system [with splice+LDA+[MLLT/ET/MLLT+SAT] features]
+# Alignment directory is used for the CMN and transforms.
+# A UBM is just a single mixture of Gaussians (full-covariance, in our case), that's trained
+# on all the data.  This will later be used in Subspace Gaussian Mixture Model (SGMM)
+# training.
+
+nj=4
+cmd=scripts/run.pl
+silweight=
+for x in 1 2; do
+  if [ $1 == "--num-jobs" ]; then
+     shift
+     nj=$1
+     shift
+  fi
+  if [ $1 == "--cmd" ]; then
+     shift
+     cmd=$1
+     shift
+  fi  
+  if [ $1 == "--silence-weight" ]; then
+     shift
+     silweight=$1 # e.g. to weight down silence in training.
+     shift
+  fi  
+done
+
+if [ $# != 5 ]; then
+  echo "Usage: steps/train_ubm_lda_etc.sh <num-comps> <data-dir> <lang-dir> <ali-dir> <exp-dir>"
+  echo " e.g.: steps/train_ubm_lda_etc.sh 400 data/train_si84 data/lang exp/tri2b_ali_si84 exp/ubm3c"
+  exit 1;
+fi
+
+if [ -f path.sh ]; then . path.sh; fi
+
+numcomps=$1
+data=$2
+lang=$3
+alidir=$4
+dir=$5
+silphonelist=`cat $lang/silphones.csl`
+
+mkdir -p $dir/log
+
+if [ ! -d $data/split$nj -o $data/split$nj -ot $data/feats.scp ]; then
+  scripts/split_data.sh $data $nj
+fi
+
+n1=`get_splits.pl $nj | awk '{print $1}'`
+[ -f $alidir/$n1.trans ] && echo "Using speaker transforms from $alidir"
+
+for n in `get_splits.pl $nj`; do
+  featspart[$n]="ark,s,cs:apply-cmvn --norm-vars=false --utt2spk=ark:$data/split$nj/$n/utt2spk ark:$alidir/$n.cmvn scp:$data/split$nj/$n/feats.scp ark:- | splice-feats ark:- ark:- | transform-feats $alidir/final.mat ark:- ark:- |"
+  if [ -f $alidir/$n1.trans ]; then
+    featspart[$n]="${featspart[$n]} transform-feats --utt2spk=ark:$data/split$nj/$n/utt2spk ark:$alidir/$n.trans ark:- ark:- |"
+  fi
+  if [ ! -z "$silweight" ]; then
+    weightspart[$n]="--weights='ark,s,cs:gunzip -c $alidir/$n.ali.gz | ali-to-post ark:- ark:- | weight-silence-post $silweight $silphonelist $alidir/final.mdl ark:- ark:- | post-to-weights ark:- ark:- |'"
+  fi
+done
+
+ngselect=50
+
+intermediate=2000
+if [ $[$numcomps*2] -gt $intermediate ]; then
+  intermediate=$[$numcomps*2];
+fi
+
+echo "Clustering model $alidir/final.mdl to get initial UBM"
+# typically: --intermediate-numcomps=2000 --ubm-numcomps=400
+
+if [ ! -s  $dir/0.dubm ]; then
+ $cmd $dir/log/cluster.log \
+  init-ubm --intermediate-numcomps=$intermediate --ubm-numcomps=$numcomps \
+   --verbose=2 --fullcov-ubm=false $alidir/final.mdl $alidir/final.occs \
+    $dir/0.dubm   || exit 1;
+fi
+rm $dir/.error 2>/dev/null
+# First do Gaussian selection to 50 components, which will be used
+# as the initial screen for all further passes.
+for n in `get_splits.pl $nj`; do
+  $cmd $dir/log/gselect.$n.log \
+    gmm-gselect --n=$ngselect $dir/0.dubm "${featspart[$n]}" \
+      "ark:|gzip -c >$dir/gselect.$n.gz"  &
+done
+wait
+[ -f $dir/.error ] && echo "Error doing GMM selection" && exit 1;
+
+for x in 0 1 2 3; do
+  echo "Pass $x"
+  for n in `get_splits.pl $nj`; do
+    $cmd $dir/log/acc.$x.$n.log \
+      gmm-global-acc-stats ${weightspart[$n]} "--gselect=ark,s,cs:gunzip -c $dir/gselect.$n.gz|" \
+        $dir/$x.dubm "${featspart[$n]}" $dir/$x.$n.acc || touch $dir/.error &
+  done
+  wait
+  [ -f $dir/.error ] && echo "Error accumulating stats for UBM estimation on pass $x" && exit 1;
+  lowcount_opt="--remove-low-count-gaussians=false"
+  [ $x -eq 3 ] && lowcount_opt=   # Only remove low-count Gaussians on last iter-- keeps gselect info valid.
+  $cmd $dir/log/update.$x.log \
+    gmm-global-est $lowcount_opt --verbose=2 $dir/$x.dubm "gmm-global-sum-accs - $dir/$x.*.acc |" \
+      $dir/$[$x+1].dubm || exit 1;
+  rm $dir/$x.*.acc $dir/$x.dubm
+done
+
+rm $dir/gselect.*.gz
+rm $dir/final.dubm 2>/dev/null
+mv $dir/4.dubm $dir/final.dubm || exit 1;
+

egs/wsj/s3/steps/train_lda_etc_mmi.sh

@@ -20,10 +20,8 @@
 # [something] may be MLLT, or ET, or MLLT + SAT.  Any speaker-specific
 # transforms are expected to be located in the alignment directory. 
 # This script never re-estimates any transforms, it just does model 
-# training.  To make this faster, it initializes the model from the
-# old system's model, i.e. for each p.d.f., it takes the best-match pdf
-# from the old system (based on overlap of tree-stats counts), and 
-# uses that GMM to initialize the current GMM.
+# training.  
+
 # Basically we are doing 4 iterations of Extended Baum-Welch (EBW)
 # estimation, as described in Dan Povey's thesis, with a few differences:
 # (i) we have the option of "boosting", as in "Boosted MMI", which increases
@@ -47,7 +45,9 @@
 niters=4
 nj=4
 boost=0.0
-tau=100
+tau=200
+merge=true # if true, cancel num and den counts as described in 
+    # the boosted MMI paper. 
 cmd=scripts/run.pl
 acwt=0.1
 stage=0
@@ -69,6 +69,9 @@ for x in `seq 8`; do
   if [ $1 == "--acwt" ]; then
     shift; acwt=$1; shift
   fi  
+  if [ $1 == "--tau" ]; then
+    shift; tau=$1; shift
+  fi  
   if [ $1 == "--stage" ]; then
     shift; stage=$1; shift
   fi  
@@ -121,58 +124,60 @@ rm $dir/.error 2>/dev/null
 cur_mdl=$srcdir/final.mdl
 x=0
 while [ $x -lt $niters ]; do
-  echo "Iteration $x: getting denominator stats."
-  # Get denominator stats...  For simplicity we rescore the lattice
+  echo "Iteration $x: getting stats."
+  # Get denominator and numerator stats together...    This involves
+  # merging the num and den posteriors, and (if $merge==true), canceling
+  # the +ve and -ve occupancies on each frame. 
+  # For simplicity we rescore the lattice
   # on all iterations, even though it shouldn't be necessary on the zeroth
   # (but we want this script to work even if $srcdir doesn't contain the
-  # model used to generate the lattice).
+  #  model used to generate the lattice).
   if [ $stage -le $x ]; then
     for n in `get_splits.pl $nj`; do  
-      $cmd $dir/log/acc_den.$x.$n.log \
+      $cmd $dir/log/acc.$x.$n.log \
         gmm-rescore-lattice $cur_mdl "${latspart[$n]}" "${featspart[$n]}" ark:- \| \
         lattice-to-post --acoustic-scale=$acwt ark:- ark:- \| \
-        gmm-acc-stats $cur_mdl "${featspart[$n]}" ark:- $dir/den_acc.$x.$n.acc \