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egs/sprakbanken_swe/s5/local/train_irstlm.sh 2.12 KB
8dcb6dfcb   Yannick Estève   first commit
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  #!/bin/bash
  
  # Copyright 2013  Mirsk Digital ApS (Author: Andreas Kirkedal)
  # Apache 2.0
  
  # This script takes data prepared in a corpus-dependent way
  # in data/local/, and converts it into the "canonical" form,
  # in various subdirectories of data/, e.g. data/lang, data/lang_test_ug,
  # data/train_si284, data/train_si84, etc.
  
  # Don't bother doing train_si84 separately (although we have the file lists
  # in data/local/) because it's just the first 7138 utterances in train_si284.
  # We'll create train_si84 after doing the feature extraction.
  
  . ./path.sh || exit 1;
  
  if [ -z $IRSTLM ] ; then
    export IRSTLM=$KALDI_ROOT/tools/irstlm/
  fi
  export PATH=${PATH}:$IRSTLM/bin
  if ! command -v ngt >/dev/null 2>&1 ; then
    echo "$0: Error: the IRSTLM is not available or compiled" >&2
    echo "$0: Error: We used to install it by default, but." >&2
    echo "$0: Error: this is no longer the case." >&2
    echo "$0: Error: To install it, go to $KALDI_ROOT/tools" >&2
    echo "$0: Error: and run extras/install_irstlm.sh" >&2
    exit 1
  fi
  
  echo "Preparing train and test data"
  srcdir=$4
  lmdir=$5
  tmpdir=data/local/lm_tmp
  lang_tmp=data/local/lang_tmp
  lexicon=$1
  ngram=$2
  lm_suffix=$3
  mkdir -p $lmdir
  mkdir -p $tmpdir
  
  
  #grep -P -v '^[\s?|\.|\!]*$' $lexicon | grep -v '^ *$' | \
  #awk '{if(NF>=4){ printf("%s
  ",$0); }}' > $lmdir/text.filt
  
  # Envelop LM training data in context cues
  add-start-end.sh < $lexicon | awk '{if(NF>=3){ printf("%s
  ",$0); }}' > $lmdir/lm_input
  wait
  
  # Next, for each type of language model, create the corresponding FST
  # and the corresponding lang_test_* directory.
  
  echo "Preparing language models for test"
  
  # Create Ngram table
  ngt -i=$lmdir/lm_input -n=$ngram -o=$lmdir/train${ngram}.ngt -b=yes
  wait
  # Estimate trigram and quadrigram models in ARPA format
  tlm -tr=$lmdir/train${ngram}.ngt -n=$ngram -lm=wb -o=$lmdir/train${ngram}.arpa
  wait
  
  
  
  test=data/lang_test_${lm_suffix}
  
  mkdir -p $test
  cp -r $srcdir/* $test
  
  cat $lmdir/train${ngram}.arpa | \
    arpa2fst --disambig-symbol=#0 \
             --read-symbol-table=$test/words.txt - $test/G.fst
  
  utils/validate_lang.pl $test || exit 1;
  
  echo "Succeeded in formatting data."
  exit 0;
  #rm -rf $tmpdir
  #rm -f $ccs