#!/bin/bash
  
  # Kaldi ASR baseline for the CHiME-4 Challenge (1ch track: single channel track)
  #
  # Copyright 2016 University of Sheffield (Jon Barker, Ricard Marxer)
  #                Inria (Emmanuel Vincent)
  #                Mitsubishi Electric Research Labs (Shinji Watanabe)
  #           2017 JHU CLSP (Szu-Jui Chen)
  #           2017 JHU CLSP (Aswin Shanmugam Subramanian)
  #  Apache 2.0  (http://www.apache.org/licenses/LICENSE-2.0)
  
  . ./path.sh
  . ./cmd.sh
  
  #####Baseline settings#####
  # Usage: 
  # Execute './run.sh' to get the models.
  # We provide BLSTM masking based enhancement --enhancement single_blstmmask
  #
  # We stopped to support the old CHiME-3/4 baseline. If you want to reproduce the old results
  # Please use the old version of Kaldi, e.g., git checkout 9e8ff73648917836d0870c8f6fdd2ff4bdde384f
  
  # Config:
  stage=0 # resume training with --stage N
  enhancement=single_blstmmask #### or your method
  # if the following options are true, they wouldn't train a model again and will only do decoding
  gmm_decode_only=false
  tdnn_decode_only=false
  # make it true when you want to add enhanced data into training set. But please note that when changing enhancement method,
  # you may need to retrain from run_gmm.sh and avoid using decode-only options above
  add_enhanced_data=true
  
  . utils/parse_options.sh || exit 1;
  
  # 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
  
  #####check data and model paths################
  # Set a main root directory of the CHiME4 data
  # If you use scripts distributed in the CHiME4 package,
  chime4_data=`pwd`/../..
  # Otherwise, please specify it, e.g.,
  # chime4_data=/db/laputa1/data/processed/public/CHiME4
  # chime3_data=/data2/archive/speech-db/original/public/CHiME3
  
  case $(hostname -f) in
    *.clsp.jhu.edu) 
        chime4_data=/export/corpora4/CHiME4/CHiME3 # JHU,
        chime3_data=/export/corpora5/CHiME3 
        ;;
  esac 
  
  if [ ! -d $chime4_data ]; then
    echo "$chime4_data does not exist. Please specify chime4 data root correctly" && exit 1;
  fi
  if [ ! -d $chime3_data ]; then
    echo "$chime3_data does not exist. Please specify chime4 data root correctly" && exit 1;
  fi
  
  #####main program start################
  # You can execute run_init.sh only "once"
  # This creates 3-gram LM, FSTs, and basic task files
  if [ $stage -le 0 ]; then
    local/run_init.sh $chime4_data
  fi
  
  if [[ "$enhancement" == *isolated_1ch_track* ]]; then
    enhancement_data=$chime4_data/data/audio/16kHz/isolated_1ch_track
  else
    enhancement_data=`pwd`/enhan/$enhancement
  fi
  
  if [ $stage -le 1 ]; then
    local/run_blstm_gev.sh --cmd "$train_cmd" --nj 20 --track 1 $chime4_data $chime3_data $enhancement_data 0 
  fi
  
  # Compute PESQ, STOI, eSTOI, and SDR scores
  if [ $stage -le 2 ]; then
    if [ ! -f local/bss_eval_sources.m ] || [ ! -f local/stoi.m ] || [ ! -f local/estoi.m ] || [ ! -f local/PESQ ]; then
      # download and install speech enhancement evaluation tools
      local/download_se_eval_tool.sh
    fi
    chime4_rir_data=local/nn-gev/data/audio/16kHz/isolated_ext
    if [ ! -d $chime4_rir_data ]; then
      echo "$chime4_rir_dir does not exist. Please run 'blstm_gev' enhancement method first;" && exit 1;
    fi
    local/compute_pesq.sh $enhancement $enhancement_data $chime4_rir_data $PWD
    local/compute_stoi_estoi_sdr.sh $enhancement $enhancement_data $chime4_rir_data
    local/compute_pesq.sh NOISY_1ch $chime4_data/data/audio/16kHz/isolated_1ch_track/ $chime4_rir_data $PWD
    local/compute_stoi_estoi_sdr.sh NOISY_1ch $chime4_data/data/audio/16kHz/isolated_1ch_track/ $chime4_rir_data
    local/write_se_results.sh $enhancement
    local/write_se_results.sh NOISY_1ch
  fi
  
  # GMM based ASR experiment
  # Please set a directory of your speech enhancement method.
  # The directory structure and audio files must follow the attached baseline enhancement directory
  if [ $stage -le 3 ]; then
    local/run_gmm.sh --add-enhanced-data $add_enhanced_data \
      --decode-only $gmm_decode_only $enhancement $enhancement_data $chime4_data
  fi
  
  # TDNN based ASR experiment
  # Since it takes time to evaluate TDNN, we make the GMM and TDNN scripts separately.
  # You may execute it after you would have promising results using GMM-based ASR experiments
  if [ $stage -le 4 ]; then
    local/chain/run_tdnn.sh --decode-only $tdnn_decode_only $enhancement
  fi
  
  # LM-rescoring experiment with 5-gram and RNN LMs
  # It takes a few days to train a RNNLM.
  if [ $stage -le 5 ]; then
    local/run_lmrescore_tdnn.sh $chime4_data $enhancement
  fi
  
  # LM-rescoring experiment with LSTM LMs
  if [ $stage -le 6 ]; then
    local/rnnlm/run_lstm.sh $enhancement
  fi
  
  echo "Done."