#!/bin/bash
  
  
  # To be run from one directory above this script.
  
  
  lexicon=data/local/dict/lexicon.txt 
  [ ! -f $lexicon ] && echo "$0: No such file $lexicon" && exit 1;
  
  # check if sri is installed or no
  sri_installed=false
  which ngram-count  &>/dev/null
  if [[ $? == 0 ]]; then 
  sri_installed=true
  fi
  
  # This script takes no arguments.  It assumes you have already run
  # previus steps successfully
  # It takes as input the files
  #data/local/train.*/text
  #data/local/dict/lexicon.txt
  
  
  export LC_ALL=C # You'll get errors about things being not sorted, if you
  # have a different locale.
  export PATH=$PATH:./../../../tools/kaldi_lm
  ( # First make sure the kaldi_lm toolkit is installed.
   cd $KALDI_ROOT/tools || exit 1;
   if [ -d kaldi_lm ]; then
     echo Not installing the kaldi_lm toolkit since it is already there.
   else
     echo Downloading and installing the kaldi_lm tools
     if [ ! -f kaldi_lm.tar.gz ]; then
       wget http://www.danielpovey.com/files/kaldi/kaldi_lm.tar.gz || exit 1;
     fi
     tar -xvzf kaldi_lm.tar.gz || exit 1;
     cd kaldi_lm
     make || exit 1;
     echo Done making the kaldi_lm tools
   fi
  ) || exit 1;
  
  
  dir=data/local/lm
   mkdir -p $dir
   text=data/local/train/text
   [ ! -f $text ] && echo "$0: No such file $text" && exit 1;
   
   cleantext=$dir/text.no_oov
  
   cat $text | awk -v lex=$lexicon 'BEGIN{while((getline<lex) >0){ seen[$1]=1; } } 
     {for(n=1; n<=NF;n++) {  if (seen[$n]) { printf("%s ", $n); } else {printf("<UNK> ",$n);} } printf("
  ");}' \
     > $cleantext || exit 1;
  
  
   cat $cleantext | awk '{for(n=2;n<=NF;n++) print $n; }' | sort | uniq -c | \
      sort -nr > $dir/word.counts || exit 1;
  
  
  # Get counts from acoustic training transcripts, and add  one-count
  # for each word in the lexicon (but not silence, we don't want it
  # in the LM-- we'll add it optionally later).
   cat $cleantext | awk '{for(n=2;n<=NF;n++) print $n; }' | \
     cat - <(grep -w -v '!SIL' $lexicon | awk '{print $1}') | \
      sort | uniq -c | sort -nr > $dir/unigram.counts || exit 1;
  
  # note: we probably won't really make use of <UNK> as there aren't any OOVs
   cat $dir/unigram.counts  | awk '{print $2}' | get_word_map.pl "<s>" "</s>" "<UNK>" > $dir/word_map \
      || exit 1;
  
  # note: ignore 1st field of train.txt, it's the utterance-id.
   cat $cleantext | awk -v wmap=$dir/word_map 'BEGIN{while((getline<wmap)>0)map[$1]=$2;}
     { for(n=2;n<=NF;n++) { printf map[$n]; if(n<NF){ printf " "; } else { print ""; }}}' | gzip -c >$dir/train.gz \
      || exit 1;
   
   train_lm.sh --arpa --lmtype 3gram-mincount $dir || exit 1;
  
  # LM is small enough that we don't need to prune it (only about 0.7M N-grams).
  # Perplexity over 128254.000000 words is 90.446690
  
  # note: output is
  # data/local/lm/3gram-mincount/lm_unpruned.gz 
  
  
  # From here is some commands to do a baseline with SRILM (assuming
  # you have it installed).
  
  if $sri_installed; then 
  
   heldout_sent=10000 # Don't change this if you want result to be comparable with
      # kaldi_lm results
   sdir=$dir/srilm # in case we want to use SRILM to double-check perplexities.
   mkdir -p $sdir
   cat $cleantext | awk '{for(n=2;n<=NF;n++){ printf $n; if(n<NF) printf " "; else print ""; }}' | \
     head -$heldout_sent > $sdir/heldout
   cat $cleantext | awk '{for(n=2;n<=NF;n++){ printf $n; if(n<NF) printf " "; else print ""; }}' | \
     tail -n +$heldout_sent > $sdir/train
  
   cat $dir/word_map | awk '{print $1}' | cat - <(echo "<s>"; echo "</s>" ) > $sdir/wordlist
  
  
   ngram-count -text $sdir/train -order 3 -limit-vocab -vocab $sdir/wordlist -unk \
     -map-unk "<UNK>" -kndiscount -interpolate -lm $sdir/srilm.o3g.kn.gz
   ngram -lm $sdir/srilm.o3g.kn.gz -ppl $sdir/heldout 
  # 0 zeroprobs, logprob= -250954 ppl= 90.5091 ppl1= 132.482
  
  # Note: perplexity SRILM gives to Kaldi-LM model is same as kaldi-lm reports above.
  # Difference in WSJ must have been due to different treatment of <UNK>.
   ngram -lm $dir/3gram-mincount/lm_unpruned.gz  -ppl $sdir/heldout 
  # 0 zeroprobs, logprob= -250913 ppl= 90.4439 ppl1= 132.379
  fi
  
  
  echo train lm succeeded
  
  exit 0