#!/bin/bash
  
  # Note: this TIDIGITS setup has not been tuned at all and has some obvious
  # deficiencies; this has been created as a starting point for a tutorial.
  # We're just using the "adults" data here, not the data from children.
  
  . ./cmd.sh ## You'll want to change cmd.sh to something that will work on your system.
             ## This relates to the queue.
  
  # This is a shell script, but it's recommended that you run the commands one by
  # one by copying and pasting into the shell.
  
  tidigits=/export/corpora5/LDC/LDC93S10
  #tidigits=/mnt/matylda2/data/TIDIGITS
  
  # The following command prepares the data/{train,dev,test} directories.
  local/tidigits_data_prep.sh $tidigits || exit 1;
  local/tidigits_prepare_lang.sh  || exit 1;
  utils/validate_lang.pl data/lang/ # Note; this actually does report errors,
     # and exits with status 1, but we've checked them and seen that they
     # don't matter (this setup doesn't have any disambiguation symbols,
     # and the script doesn't like that).
  
  # Now make MFCC features.
  # mfccdir should be some place with a largish disk where you
  # want to store MFCC features.
  mfccdir=mfcc
  for x in test train; do
   steps/make_mfcc.sh --cmd "$train_cmd" --nj 20 \
     data/$x exp/make_mfcc/$x $mfccdir || exit 1;
   steps/compute_cmvn_stats.sh data/$x exp/make_mfcc/$x $mfccdir || exit 1;
  done
  
  utils/subset_data_dir.sh data/train 1000 data/train_1k
  
  
  
  # try --boost-silence 1.25 to some of the scripts below (also 1.5, if that helps...
  # effect may not be clear till we test triphone system.  See
  # wsj setup for examples (../../wsj/s5/run.sh)
  
  steps/train_mono.sh  --nj 4 --cmd "$train_cmd" \
    data/train_1k data/lang exp/mono0a
  
   utils/mkgraph.sh data/lang exp/mono0a exp/mono0a/graph && \
   steps/decode.sh --nj 10 --cmd "$decode_cmd" \
        exp/mono0a/graph data/test exp/mono0a/decode
  
  steps/align_si.sh --nj 4 --cmd "$train_cmd" \
     data/train data/lang exp/mono0a exp/mono0a_ali
  
  steps/train_deltas.sh --cmd "$train_cmd" \
      300 3000 data/train data/lang exp/mono0a_ali exp/tri1
  
  
   utils/mkgraph.sh data/lang exp/tri1 exp/tri1/graph
   steps/decode.sh --nj 10 --cmd "$decode_cmd" \
        exp/tri1/graph data/test exp/tri1/decode
  
  # Example of looking at the output.
  # utils/int2sym.pl -f 2- data/lang/words.txt  exp/tri1/decode/scoring/19.tra | sed "s/ $//" | sort | diff - data/test/text
  
  
  # Getting results [see RESULTS file]
  # for x in exp/*/decode*; do [ -d $x ] && grep SER $x/wer_* | utils/best_wer.sh; done
  
  #exp/mono0a/decode/wer_17:%SER 3.67 [ 319 / 8700 ]
  #exp/tri1/decode/wer_19:%SER 2.64 [ 230 / 8700 ]