#!/bin/bash
  
  train_cmd="utils/run.pl"
  decode_cmd="utils/run.pl"
  
  if [ ! -d waves_yesno ]; then
    wget http://www.openslr.org/resources/1/waves_yesno.tar.gz || exit 1;
    # was:
    # wget http://sourceforge.net/projects/kaldi/files/waves_yesno.tar.gz || exit 1;
    tar -xvzf waves_yesno.tar.gz || exit 1;
  fi
  
  train_yesno=train_yesno
  test_base_name=test_yesno
  
  rm -rf data exp mfcc
  
  # Data preparation
  
  local/prepare_data.sh waves_yesno
  local/prepare_dict.sh
  utils/prepare_lang.sh --position-dependent-phones false data/local/dict "<SIL>" data/local/lang data/lang
  local/prepare_lm.sh
  
  # Feature extraction
  for x in train_yesno test_yesno; do 
   steps/make_mfcc.sh --nj 1 data/$x exp/make_mfcc/$x mfcc
   steps/compute_cmvn_stats.sh data/$x exp/make_mfcc/$x mfcc
   utils/fix_data_dir.sh data/$x
  done
  
  # Mono training
  steps/train_mono.sh --nj 1 --cmd "$train_cmd" \
    --totgauss 400 \
    data/train_yesno data/lang exp/mono0a 
    
  # Graph compilation  
  utils/mkgraph.sh data/lang_test_tg exp/mono0a exp/mono0a/graph_tgpr
  
  # Decoding
  steps/decode.sh --nj 1 --cmd "$decode_cmd" \
      exp/mono0a/graph_tgpr data/test_yesno exp/mono0a/decode_test_yesno
  
  for x in exp/*/decode*; do [ -d $x ] && grep WER $x/wer_* | utils/best_wer.sh; done