#!/bin/bash
  #
  # Copyright 2012-2015  Johns Hopkins University (Author: Daniel Povey)
  # Apache 2.0
  
  # Version of align_fmllr_lats.sh that uses "basis fMLLR", so it is suitable for
  # situations where there is very little data per speaker (e.g. when there is a
  # one-to-one mapping between utterances and speakers).  Intended for use where
  # the model was trained with basis-fMLLR (i.e.  when you trained the model with
  # train_sat_basis.sh where you normally would have trained with train_sat.sh),
  # or when it was trained with SAT but you ran get_fmllr_basis.sh on the
  # source-model directory.
  
  # Begin configuration section.
  stage=0
  nj=4
  cmd=run.pl
  # Begin configuration.
  scale_opts="--transition-scale=1.0 --self-loop-scale=0.1"
  acoustic_scale=0.1
  beam=10
  retry_beam=40
  final_beam=20  # For the lattice-generation phase there is no retry-beam.  This
                 # is a limitation of gmm-latgen-faster.  We just use an
                 # intermediate beam.  We'll lose a little data and it will be
                 # slightly slower.  (however, the min-active of 200 that
                 # gmm-latgen-faster defaults to may help.)
  boost_silence=1.0 # factor by which to boost silence during alignment.
  basis_fmllr_opts="--fmllr-min-count=22  --num-iters=10 --size-scale=0.2 --step-size-iters=3"
  
  generate_ali_from_lats=false # If true, alingments generated from lattices.
  # End configuration options.
  
  echo "$0 $@"  # Print the command line for logging
  
  [ -f path.sh ] && . ./path.sh # source the path.
  . parse_options.sh || exit 1;
  
  if [ $# != 4 ]; then
     echo "usage: steps/align_fmllr_lats.sh <data-dir> <lang-dir> <src-dir> <align-dir>"
     echo "e.g.:  steps/align_fmllr_lats.sh data/train data/lang exp/tri1 exp/tri1_lats"
     echo "main options (for others, see top of script file)"
     echo "  --config <config-file>                           # config containing options"
     echo "  --nj <nj>                                        # number of parallel jobs"
     echo "  --cmd (utils/run.pl|utils/queue.pl <queue opts>) # how to run jobs."
     exit 1;
  fi
  
  data=$1
  lang=$2
  srcdir=$3
  dir=$4
  
  if [ ! -f $srcdir/fmllr.basis ]; then
    echo "$0: expected $srcdir/fmllr.basis to exist.   Run get_fmllr_basis.sh on $srcdir."
  fi
  
  for f in $data/feats.scp $lang/phones.txt $srcdir/final.mdl; do
    [ ! -f $f ] && echo "$0: expected file $f to exist" && exit 1
  done
  
  
  oov=`cat $lang/oov.int` || exit 1;
  silphonelist=`cat $lang/phones/silence.csl` || exit 1;
  sdata=$data/split$nj
  
  mkdir -p $dir/log
  echo $nj > $dir/num_jobs
  [[ -d $sdata && $data/feats.scp -ot $sdata ]] || split_data.sh $data $nj || exit 1;
  
  utils/lang/check_phones_compatible.sh $lang/phones.txt $srcdir/phones.txt || exit 1;
  cp $lang/phones.txt $dir || exit 1;
  
  cp $srcdir/{tree,final.mdl} $dir || exit 1;
  cp $srcdir/final.alimdl $dir 2>/dev/null
  cp $srcdir/final.occs $dir;
  splice_opts=`cat $srcdir/splice_opts 2>/dev/null` # frame-splicing options.
  cp $srcdir/splice_opts $dir 2>/dev/null # frame-splicing options.
  cmvn_opts=`cat $srcdir/cmvn_opts 2>/dev/null`
  cp $srcdir/cmvn_opts $dir 2>/dev/null # cmn/cmvn option.
  delta_opts=`cat $srcdir/delta_opts 2>/dev/null`
  cp $srcdir/delta_opts $dir 2>/dev/null
  
  if [ -f $srcdir/final.mat ]; then feat_type=lda; else feat_type=delta; fi
  echo "$0: feature type is $feat_type"
  
  case $feat_type in
    delta) sifeats="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) sifeats="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 $srcdir/final.mat ark:- ark:- |"
      cp $srcdir/final.mat $dir
      cp $srcdir/full.mat $dir 2>/dev/null
     ;;
    *) echo "Invalid feature type $feat_type" && exit 1;
  esac
  
  ## Set up model and alignment model.
  mdl=$srcdir/final.mdl
  if [ -f $srcdir/final.alimdl ]; then
    alimdl=$srcdir/final.alimdl
  else
    alimdl=$srcdir/final.mdl
  fi
  [ ! -f $mdl ] && echo "$0: no such model $mdl" && exit 1;
  alimdl_cmd="gmm-boost-silence --boost=$boost_silence `cat $lang/phones/optional_silence.csl` $alimdl - |"
  mdl_cmd="gmm-boost-silence --boost=$boost_silence `cat $lang/phones/optional_silence.csl` $mdl - |"
  
  
  ## because gmm-latgen-faster doesn't support adding the transition-probs to the
  ## graph itself, we need to bake them into the compiled graphs.  This means we can't reuse previously compiled graphs,
  ## because the other scripts write them without transition probs.
  if [ $stage -le 0 ]; then
    echo "$0: compiling training graphs"
    tra="ark:utils/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 $scale_opts $dir/tree $dir/final.mdl  $lang/L.fst "$tra" \
      "ark:|gzip -c >$dir/fsts.JOB.gz" || exit 1;
  fi
  
  
  if [ $stage -le 1 ]; then
    # Note: we need to set --transition-scale=0.0 --self-loop-scale=0.0 because,
    # as explained above, we compiled the transition probs into the training
    # graphs.
    echo "$0: aligning data in $data using $alimdl and speaker-independent features."
    $cmd JOB=1:$nj $dir/log/align_pass1.JOB.log \
      gmm-align-compiled --transition-scale=0.0 --self-loop-scale=0.0 --acoustic-scale=$acoustic_scale \
          --beam=$beam --retry-beam=$retry_beam "$alimdl_cmd" \
      "ark:gunzip -c $dir/fsts.JOB.gz|" "$sifeats" "ark:|gzip -c >$dir/pre_ali.JOB.gz" || exit 1;
  fi
  
  if [ $stage -le 2 ]; then
    echo "$0: computing fMLLR transforms"
    if [ "$alimdl" != "$mdl" ]; then
      $cmd JOB=1:$nj $dir/log/fmllr.JOB.log \
        ali-to-post "ark:gunzip -c $dir/pre_ali.JOB.gz|" ark:- \| \
        weight-silence-post 0.0 $silphonelist $alimdl ark:- ark:- \| \
        gmm-post-to-gpost $alimdl "$sifeats" ark:- ark:- \| \
        gmm-est-basis-fmllr-gpost $basis_fmllr_opts \
        --spk2utt=ark:$sdata/JOB/spk2utt $mdl $srcdir/fmllr.basis "$sifeats" \
        ark,s,cs:- ark:$dir/trans.JOB || exit 1;
    else
      $cmd JOB=1:$nj $dir/log/fmllr.JOB.log \
        ali-to-post "ark:gunzip -c $dir/pre_ali.JOB.gz|" ark:- \| \
        weight-silence-post 0.0 $silphonelist $alimdl ark:- ark:- \| \
        gmm-est-basis-fmllr $basis_fmllr_opts \
        --spk2utt=ark:$sdata/JOB/spk2utt $mdl $srcdir/fmllr.basis "$sifeats" \
        ark,s,cs:- ark:$dir/trans.JOB || exit 1;
    fi
  fi
  
  feats="$sifeats transform-feats --utt2spk=ark:$sdata/JOB/utt2spk ark:$dir/trans.JOB ark:- ark:- |"
  
  if [ $stage -le 3 ]; then
    # Warning: gmm-latgen-faster doesn't support a retry-beam so you may get more
    # alignment errors (however, it does have a default min-active=200 so this
    # will tend to reduce alignment errors).
    # --allow_partial=false makes sure we reach the end of the decoding graph.
    # --word-determinize=false makes sure we retain the alternative pronunciations of
    #   words (including alternatives regarding optional silences).
    #  --lattice-beam=$beam keeps all the alternatives that were within the beam,
    #    it means we do no pruning of the lattice (lattices from a training transcription
    #    will be small anyway).
    echo "$0: generating lattices containing alternate pronunciations."
    $cmd JOB=1:$nj $dir/log/generate_lattices.JOB.log \
      gmm-latgen-faster --acoustic-scale=$acoustic_scale --beam=$final_beam \
          --lattice-beam=$final_beam --allow-partial=false --word-determinize=false \
        "$mdl_cmd" "ark:gunzip -c $dir/fsts.JOB.gz|" "$feats" \
        "ark:|gzip -c >$dir/lat.JOB.gz" || exit 1;
  fi
  
  if [ $stage -le 4 ] && $generate_ali_from_lats; then
    # If generate_alignments is true, ali.*.gz is generated in lats dir
    $cmd JOB=1:$nj $dir/log/generate_alignments.JOB.log \
      lattice-best-path --acoustic-scale=$acoustic_scale "ark:gunzip -c $dir/lat.JOB.gz |" \
      ark:/dev/null "ark:|gzip -c >$dir/ali.JOB.gz" || exit 1;
  fi
  
  rm $dir/pre_ali.*.gz 2>/dev/null || true
  
  echo "$0: done generating lattices from training transcripts."
  
  utils/summarize_warnings.pl $dir/log
  
  exit 0;