#!/bin/bash
  
  # Copyright 2016 University of Sheffield (Jon Barker, Ricard Marxer)
  #                Inria (Emmanuel Vincent)
  #                Mitsubishi Electric Research Labs (Shinji Watanabe)
  #  Apache 2.0  (http://www.apache.org/licenses/LICENSE-2.0)
  
  # Config:
  nj=30
  stage=0 # resume training with --stage=N
  eval_flag=true # make it true when the evaluation data are released
  
  . utils/parse_options.sh || exit 1;
  
  # This script is made from the kaldi recipe of the 2nd CHiME Challenge Track 2
  # made by Chao Weng
  
  . ./path.sh
  . ./cmd.sh ## You'll want to change cmd.sh to something that will work on your system.
             ## This relates to the queue.
  
  if [ $# -ne 1 ]; then
    printf "
  USAGE: %s <Chime4 root directory>
  
  " `basename $0`
    echo "Please specifies a CHiME4 root directory"
    echo "If you use scripts distributed in the CHiME4 package,"
    echo "It would be `pwd`/../.."
    exit 1;
  fi
  
  # This is a shell script, but it's recommended that you run the commands one by
  # one by copying and pasting into the shell.
  
  # clean data
  chime4_data=$1
  wsj0_data=$chime4_data/data/WSJ0 # directory of WSJ0 in Chime4. You can also specify your WSJ0 corpus directory
  
  # Set bash to 'debug' mode, it will exit on :
  # -e 'error', -u 'undefined variable', -o ... 'error in pipeline', -x 'print commands',
  set -e
  set -u
  set -o pipefail
  
  if [ $stage -le 0 ]; then
    # process for clean speech and making LMs etc. from original WSJ0
    # note that training on clean data means original WSJ0 data only (no booth data)
    local/clean_wsj0_data_prep.sh $wsj0_data
    local/wsj_prepare_dict.sh
    utils/prepare_lang.sh data/local/dict "<SPOKEN_NOISE>" data/local/lang_tmp data/lang
    local/clean_chime4_format_data.sh
  fi
  
  echo "`basename $0` Done."