#!/bin/bash
  
  # Multilingual setup for SGMMs.
  # Caution: this is just a stub, intended to show some others what to do, it
  # is not functional yet.
  
  # We treat the WSJ setup as the "other language"-- in fact it's the same language,
  # of course, but we treat the phones there as a distinct set.
  # The only important thing is that the WSJ data has the same sample rate as the
  # RM data.
  
  # add the prefix to all the words and phones:
  
  mkdir -p data_ml exp_ml # ml stands for "multilingual"
  
  utils/add_lang_prefix.sh data/lang rm: data_ml/lang_rm
  
  utils/add_lang_prefix.sh ../../wsj/s5/data/lang wsj: data_ml/lang_wsj
  
  # add the prefix to all the words, utterance-ids, and speaker-ids.
  utils/add_data_prefix.sh data/train rm: data_ml/train_rm
  
  utils/add_data_prefix.sh ../../wsj/s5/data/train_si284 wsj: data_ml/train_si284_wsj
  
  
  # Merge the "lang" directories.  This will change the phones.txt and words.txt,
  # to incorporate all the symbols in the original setups.
  utils/merge_lang.sh data_ml/lang_rm data_ml/lang_wsj data_ml/lang_rm_wsj
  
  utils/combine_data.sh data_ml/train_rm data_ml/train_si284_wsj data_ml/train
  
  # the call to utils/convert_models.sh below will
  # convert the RM LDA+MLLT system to use the new "lang" directory.
  # This script converts the models in the directory to use the new integer values
  # for the phones, as in data/lang_rm_wsj.
  # Everything else will be copied.  The only thing changed in the models is
  # the transition-ids.  We'll need a program call like
  #  gmm-convert <phone-map-file> <model-in> <model-out>
  # where each line of phone-map-file has two lines, (phone-in phone-out).
  # This will just affect the transition model, by mapping all the phone-ids.
  # We'll also need a program
  #  convert-tree <phone-map-file> <tree-in> <tree-out>
  
  utils/convert_models.sh exp/tri2b data_ml/lang_rm exp_ml/tri2b_rm data_ml/lang_rm_wsj
  
  utils/convert_models.sh ../../wsj/exp/tri4b data_ml/lang_wsj exp_ml/tri4b_wsj data_ml/lang
  
  # Re-do the alignment of the RM tri2b setup with the converted models
  # (this avoids the hassle of converting the alignment.)
  steps/align_si.sh --nj 8 --cmd "$train_cmd"  data_ml/train_rm data_ml/lang exp_ml/tri2b_rm \
      exp_ml/tri2b_rm_ali || exit 1;
  
  # Now, starting from those alignments train an RM system with the same LDA+MLLT
  # matrix as the WSJ system.  The training script takes this from the alignment directory,
  # so it's sufficient to put it there:
  cp exp_ml/tri4b_wsj/final.mat exp_ml/tri2b_rm_ali/final.mat
  
  steps/train_sat.sh 1800 9000 data/train data/lang exp_ml/tri2b_rm_ali exp_ml/tri3b_rm_ali || exit 1;
  
  # Train an LDA+MLLT+SAT system for RM that uses the same LDA+MLLT transforms as for WSJ.
  steps/train_sat.sh 1800 9000 data_ml/train_rm data_ml/lang exp_ml/tri2b_rm_ali exp_ml/tri3b_rm || exit 1;
  
  # Now merge the RM and WSJ models.  This will create trees and transition-models
  # that handle the two (disjoint) sets of phones that the RM and WSJ models
  # contain.  We'll need a program "merge-tree" and a program "gmm-merge".  The
  # "merge-tree" program will need, for each tree, a record of which sets of
  # phones it was supposed to handle, since this is not recorded in the tree
  # itself-- we can get this from the transition models which do record this.
  # probably the "merge-tree" program will have usage:
  # merge-tree <tree1> <phone-set-1> <tree2> <phone-set-2> ... <tree-out>
  # where the phone-set-n's will probably be filenames that contain lists of
  # the phones.
  # The "gmm-merge" program will have the usage:
  # gmm-merge <model1> <model2> ... <model-out>
  
  steps/merge_models.sh data_ml/tri3b_rm data_ml/tri4b_wsj data_ml/tri4b
  
  steps/align_fmllr.sh --nj 32 --cmd "$train_cmd" data_ml/train data_ml/lang exp_ml/tri4b \
    exp_ml/tri4b_ali || exit 1;
  
  
  steps/train_ubm.sh --silence-weight 0.5 --cmd "$train_cmd" 600 \
     data_ml/train data_ml/lang exp_ml/tri4b_ali exp_ml/ubm5a || exit 1;
  
  # Use slightly larger SGMM parameters than the WSJ setup.
  steps/train_sgmm2.sh --cmd "$train_cmd" \
    15000 30000 data_ml/train data_ml/lang exp_ml/tri4b_ali \
      exp_ml/ubm5a/final.ubm exp_ml/sgmm2_5a || exit 1;
  
  
  # This convert_models.sh script will also have the effect of subsetting
  # the model, because some of the phones are undefined in the destination.
  # We should make sure that the programs "gmm-convert" and "convert-tree"
  # accept a phone map that does not map all of the phones we have-- it would
  # delete those phones.  The --reduce option to the script would be passed
  # into those programs, and confirm to them that that's "really" what we want
  # to do.
  utils/convert_models.sh --reduce true exp_ml/sgmm2_5a data_ml/lang exp/sgmm2_5c_ml data/lang
  
  (
    utils/mkgraph.sh data/lang_test_tgpr exp/sgmm2_5c_ml exp/sgmm2_5c_ml/graph_tgpr
    steps/decode_sgmm2.sh --nj 10 --cmd "$decode_cmd" --transform-dir exp/tri4b/decode_tgpr_dev93 \
      exp/sgmm2_5c_ml/graph_tgpr data/test_dev93 exp/sgmm2_5c_ml/decode_tgpr_dev93
    steps/decode_sgmm2.sh --nj 8 --cmd "$decode_cmd" --transform-dir exp/tri4b/decode_tgpr_eval92 \
      exp/sgmm2_5c_ml/graph_tgpr data/test_eval92 exp/sgmm2_5c_ml/decode_tgpr_eval92
  
    utils/mkgraph.sh data/lang_test_bd_tgpr exp/sgmm2_5c_ml exp/sgmm2_5c_ml/graph_bd_tgpr || exit 1;
    steps/decode_sgmm2.sh --nj 10 --cmd "$decode_cmd" --transform-dir exp/tri4b/decode_bd_tgpr_dev93 \
      exp/sgmm2_5c_ml/graph_bd_tgpr data/test_dev93 exp/sgmm2_5c_ml/decode_bd_tgpr_dev93
    steps/decode_sgmm2.sh --nj 8 --cmd "$decode_cmd" --transform-dir exp/tri4b/decode_bd_tgpr_eval92 \
      exp/sgmm2_5c_ml/graph_bd_tgpr data/test_eval92 exp/sgmm2_5c_ml/decode_bd_tgpr_eval92
  ) &