#!/bin/bash
  # Copyright 2019  QCRI (Author: Ahmed Ali)
  # Apache 2.0
  
  set -e -o pipefail
  
  # To create G.fst from ARPA language model
  . ./path.sh || die "path.sh expected";
  
  local/train_lms_srilm.sh --train-text data/train/text data/ data/srilm
  
  # for basic decoding, let's use only a trigram LM
  [ -d data/lang_test/ ] && rm -rf data/lang_test
  cp -R data/lang data/lang_test
  lm=data/srilm/3gram.me.gz
  utils/format_lm.sh data/lang_test $lm data/local/dict/lexicon.txt data/lang_test
  
  # for decoding using bigger, we build 4-gram using the same transcription text
  [ -d data/lang_big ] && rm -rf data/lang_big
  cp -R data/lang data/lang_big
  lm=data/srilm/4gram.me.gz
  utils/format_lm.sh data/lang_big $lm data/local/dict/lexicon.txt data/lang_big
  
  utils/build_const_arpa_lm.sh $lm data/lang_big data/lang_big
  exit 0;