Yannick Estève / ONTRAC-Kaldi

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egs/aspire/s5/local/nnet3/decode_online.sh 3.87 KB
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8dcb6dfcb   Yannick Estève   first commit 
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  #!/bin/bash
  
  # Copyright Johns Hopkins University (Author: Daniel Povey, Vijayaditya Peddinti) 2016.  Apache 2.0.
  # This script does online decoding, unlike local/nnet3/decode.sh which does 2-pass decoding with
  # uniform segments.
  
  set -e
  
  # general opts
  iter=
  stage=0
  decode_num_jobs=30
  num_jobs=30
  affix=
  
  # segmentation opts
  window=10
  overlap=5
  
  # ivector+decode opts
  # tuned based on the ASpIRE nnet2 online system
  max_count=75
  max_state_duration=40
  silence_weight=0.00001
  
  pass2_decode_opts="--min-active 1000"
  lattice_beam=8
  extra_left_context=0 # change for (B)LSTM
  extra_right_context=0 # change for BLSTM
  frames_per_chunk=50 # change for (B)LSTM
  acwt=0.1 # important to change this when using chain models
  post_decode_acwt=1.0 # important to change this when using chain models
  extra_left_context_initial=0
  
  score_opts="--min-lmwt 6 --max-lmwt 13"
  
  . ./cmd.sh
  [ -f ./path.sh ] && . ./path.sh
  . utils/parse_options.sh || exit 1;
  
  if [ $# -ne 4 ]; then
    echo "Usage: $0 [options] <data-dir> <lang-dir> <graph-dir> <model-dir>"
    echo " Options:"
    echo "    --stage (0|1|2)   # start scoring script from part-way through."
    echo "e.g.:"
    echo "$0 dev_aspire data/lang exp/tri5a/graph_pp exp/nnet3/tdnn"
    exit 1;
  fi
  
  data_set=$1 #select from {dev_aspire, test_aspire, eval_aspire}
  lang=$2 # data/lang
  graph=$3 #exp/tri5a/graph_pp
  dir=$4 # exp/nnet3/tdnn
  
  model_affix=`basename $dir`
  affix=_${affix}${iter:+_iter${iter}}
  
  segmented_data_set=${data_set}_uniformsegmented
  if [ $stage -le 1 ]; then
    local/generate_uniformly_segmented_data_dir.sh  \
      --overlap $overlap --window $window $data_set $segmented_data_set
  fi
  
  if [[ "$data_set" =~ "test_aspire" ]]; then
    out_file=single_dev_test${affix}_$model_affix.ctm
    act_data_set=test_aspire
  elif [[ "$data_set" =~ "eval_aspire" ]]; then
    out_file=single_eval${affix}_$model_affix.ctm
    act_data_set=eval_aspire
  elif [[ "$data_set" =~  "dev_aspire" ]]; then
    # we will just decode the directory without oracle segments file
    # as we would like to operate in the actual evaluation condition
    out_file=single_dev${affix}_${model_affix}.ctm
    act_data_set=dev_aspire
  else
    echo "$0: Unknown data-set $data_set"
    exit 1
  fi
  
  if [ $stage -le 2 ]; then
    # If this setup used PLP features, we'd have to give the option --feature-type plp
    # to the script below.
    steps/online/nnet3/prepare_online_decoding.sh \
      --mfcc-config conf/mfcc_hires.conf \
      --max-count $max_count \
        $lang exp/nnet3/extractor "$dir" ${dir}_online
  fi
  
  decode_dir=${dir}_online/decode_${segmented_data_set}${affix}_pp
  if [ $stage -le 3 ]; then
    echo "Generating lattices, with --acwt $acwt and --post-decode-acwt $post_decode_acwt "
        # the following options have not yet been implemented
        # --frames-per-chunk "$frames_per_chunk"
        #--extra-left-context $extra_left_context  \
        #--extra-right-context $extra_right_context  \
    steps/online/nnet3/decode.sh --nj $decode_num_jobs --cmd "$decode_cmd" \
        --config conf/decode.config $pass2_decode_opts \
        --acwt $acwt --post-decode-acwt $post_decode_acwt \
        --extra-left-context-initial $extra_left_context_initial \
        --silence-weight $silence_weight \
        --per-utt true \
        --skip-scoring true ${iter:+--iter $iter} --lattice-beam $lattice_beam \
       $graph data/${segmented_data_set}_hires ${decode_dir}_tg || \
       { echo "$0: Error decoding" && exit 1; }
  fi
  
  if [ $stage -le 4 ]; then
    echo "Rescoring lattices"
    steps/lmrescore_const_arpa.sh --cmd "$decode_cmd" \
      --skip-scoring true \
      ${lang}_pp_test{,_fg} data/${segmented_data_set}_hires \
      ${decode_dir}_{tg,fg};
  fi
  
  decode_dir=${decode_dir}_fg
  if [ $stage -le 5 ]; then
    local/score_aspire.sh --cmd "$decode_cmd" \
      $score_opts \
      --word-ins-penalties "0.0,0.25,0.5,0.75,1.0" \
      --ctm-beam 6 \
      ${iter:+--iter $iter} \
      --decode-mbr true \
      --tune-hyper true \
      $lang $decode_dir $act_data_set $segmented_data_set $out_file
  fi