#!/bin/bash
  
  # Copyright 2012   Carnegie Mellon University (Author: Yajie Miao)
  #                  Johns Hopkins University (Author: Daniel Povey)
  
  # Decoding script that computes basis for basis-fMLLR (see decode_fmllr_basis.sh).
  # This can be on top of delta+delta-delta, or LDA+MLLT features.
  
  stage=0
  # Parameters in alignment of training data
  scale_opts="--transition-scale=1.0 --acoustic-scale=0.1 --self-loop-scale=0.1"
  per_utt=true # If true, then treat each utterance as a separate speaker for purposes of
    # basis training... this is recommended if the number of actual speakers in your
    # training set is less than (feature-dim) * (feature-dim+1).
  align_beam=10
  retry_beam=40
  silence_weight=0.01
  cmd=run.pl
  # End configuration section
  
  echo "$0 $@"  # Print the command line for logging
  
  [ -f ./path.sh ] && . ./path.sh; # source the path.
  . parse_options.sh || exit 1;
  
  if [ $# != 3 ]; then
     echo "Usage: steps/get_fmllr_basis.sh [options] <data-dir> <lang-dir> <exp-dir>"
     echo " e.g.: steps/decode_basis_fmllr.sh data/train_si84 data/lang exp/tri3b/"
     echo "Note: we currently assume that this is the same data you trained the model with."
     echo "main options (for others, see top of script file)"
     echo "  --config <config-file>                   # config containing options"
     echo "  --cmd <cmd>                              # Command to run in parallel with"
     exit 1;
  fi
  
  data=$1
  lang=$2
  dir=$3
  
  nj=`cat $dir/num_jobs` || exit 1;
  sdata=$data/split$nj;
  [[ -d $sdata && $data/feats.scp -ot $sdata ]] || split_data.sh $data $nj || exit 1;
  
  splice_opts=`cat $dir/splice_opts 2>/dev/null` # frame-splicing options.
  
  silphonelist=`cat $lang/phones/silence.csl` || exit 1;
  
  for f in $data/feats.scp $dir/final.alimdl $dir/final.mdl $dir/ali.1.gz; do
    [ ! -f $f ] && echo "$0: no such file $f" && exit 1;
  done
  
  
  # Set up the unadapted features "$sifeats".
  if [ -f $dir/final.mat ]; then feat_type=lda; else feat_type=delta; fi
  echo "$0: feature type is $feat_type";
  case $feat_type in
    delta) sifeats="ark,s,cs:apply-cmvn --norm-vars=false --utt2spk=ark:$sdata/JOB/utt2spk scp:$sdata/JOB/cmvn.scp scp:$sdata/JOB/feats.scp ark:- | add-deltas ark:- ark:- |";;
    lda) sifeats="ark,s,cs:apply-cmvn --norm-vars=false --utt2spk=ark:$sdata/JOB/utt2spk scp:$sdata/JOB/cmvn.scp scp:$sdata/JOB/feats.scp ark:- | splice-feats $splice_opts ark:- ark:- | transform-feats $dir/final.mat ark:- ark:- |";;
    *) echo "Invalid feature type $feat_type" && exit 1;
  esac
  
    # Set up the adapted features "$feats" for training set.
  if [ -f $srcdir/trans.1 ]; then 
    feats="$sifeats transform-feats --utt2spk=ark:$sdata/JOB/utt2spk ark:$sdata/trans.JOB ark:- ark:- |";
  else
    feats="$sifeats";
  fi
  
  
  if $per_utt; then
    spk2utt_opt=  # treat each utterance as separate speaker when computing basis.
    echo "Doing per-utterance adaptation for purposes of computing the basis."
  else
    echo "Doing per-speaker adaptation for purposes of computing the basis."
    [ `cat $sdata/spk2utt | wc -l` -lt $[41*40] ] && \
      echo "Warning: number of speakers is small, might be better to use --per-utt=true."
    spk2utt_opt="--spk2utt=ark:$sdata/JOB/spk2utt"
  fi
  
  # Note: we get Gaussian level alignments with the "final.mdl" and the
  # speaker adapted features. 
  $cmd JOB=1:$nj $dir/log/basis_acc.JOB.log \
    ali-to-post "ark:gunzip -c $dir/ali.JOB.gz|" ark:- \| \
    weight-silence-post $silence_weight $silphonelist $dir/final.mdl ark:- ark:- \| \
    gmm-post-to-gpost $dir/final.mdl "$feats" ark:- ark:- \| \
    gmm-basis-fmllr-accs-gpost $spk2utt_opt \
      $dir/final.mdl "$sifeats" ark,s,cs:- $dir/basis.acc.JOB || exit 1; 
  
  # Compute the basis matrices.
  $cmd $dir/log/basis_training.log \
    gmm-basis-fmllr-training $dir/final.mdl $dir/fmllr.basis $dir/basis.acc.* || exit 1;
  rm $dir/basis.acc.* 2>/dev/null
  
  exit 0;