// gmmbin/gmm-align.cc
  
  // Copyright 2009-2012  Microsoft Corporation
  //           2012-2014 Johns Hopkins University (Author: Daniel Povey)
  
  // See ../../COPYING for clarification regarding multiple authors
  //
  // Licensed under the Apache License, Version 2.0 (the "License");
  // you may not use this file except in compliance with the License.
  // You may obtain a copy of the License at
  //
  //  http://www.apache.org/licenses/LICENSE-2.0
  //
  // THIS CODE IS PROVIDED *AS IS* BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY
  // KIND, EITHER EXPRESS OR IMPLIED, INCLUDING WITHOUT LIMITATION ANY IMPLIED
  // WARRANTIES OR CONDITIONS OF TITLE, FITNESS FOR A PARTICULAR PURPOSE,
  // MERCHANTABLITY OR NON-INFRINGEMENT.
  // See the Apache 2 License for the specific language governing permissions and
  // limitations under the License.
  
  #include "base/kaldi-common.h"
  #include "util/common-utils.h"
  #include "gmm/am-diag-gmm.h"
  #include "hmm/transition-model.h"
  #include "fstext/fstext-utils.h"
  #include "decoder/decoder-wrappers.h"
  #include "decoder/training-graph-compiler.h"
  #include "gmm/decodable-am-diag-gmm.h"
  #include "lat/kaldi-lattice.h" // for {Compact}LatticeArc
  
  
  int main(int argc, char *argv[]) {
    try {
      using namespace kaldi;
      typedef kaldi::int32 int32;
      using fst::SymbolTable;
      using fst::VectorFst;
      using fst::StdArc;
  
      const char *usage =
          "Align features given [GMM-based] models.
  "
          "Usage:   gmm-align [options] tree-in model-in lexicon-fst-in feature-rspecifier "
          "transcriptions-rspecifier alignments-wspecifier
  "
          "e.g.: 
  "
          " gmm-align tree 1.mdl lex.fst scp:train.scp "
          "'ark:sym2int.pl -f 2- words.txt text|' ark:1.ali
  ";
      ParseOptions po(usage);
      AlignConfig align_config;
      BaseFloat acoustic_scale = 1.0;
      std::string disambig_rxfilename;
      TrainingGraphCompilerOptions gopts;
  
      align_config.Register(&po);
      po.Register("acoustic-scale", &acoustic_scale, "Scaling factor for acoustic likelihoods");
      po.Register("read-disambig-syms", &disambig_rxfilename, "File containing "
                  "list of disambiguation symbols in phone symbol table");
  
      gopts.Register(&po);
      po.Read(argc, argv);
  
      if (po.NumArgs() != 6) {
        po.PrintUsage();
        exit(1);
      }
  
      std::string tree_in_filename = po.GetArg(1);
      std::string model_in_filename = po.GetArg(2);
      std::string lex_in_filename = po.GetArg(3);
      std::string feature_rspecifier = po.GetArg(4);
      std::string transcript_rspecifier = po.GetArg(5);
      std::string alignment_wspecifier = po.GetArg(6);
  
      ContextDependency ctx_dep;
      ReadKaldiObject(tree_in_filename, &ctx_dep);
  
      TransitionModel trans_model;
      AmDiagGmm am_gmm;
      {
        bool binary;
        Input ki(model_in_filename, &binary);
        trans_model.Read(ki.Stream(), binary);
        am_gmm.Read(ki.Stream(), binary);
      }
  
      // ownership will be taken by gc.
      VectorFst<StdArc> *lex_fst = fst::ReadFstKaldi(lex_in_filename);
  
      std::vector<int32> disambig_syms;    
      if (disambig_rxfilename != "")
        if (!ReadIntegerVectorSimple(disambig_rxfilename, &disambig_syms))
          KALDI_ERR << "fstcomposecontext: Could not read disambiguation symbols from "
                    << disambig_rxfilename;
      
      TrainingGraphCompiler gc(trans_model, ctx_dep, lex_fst, disambig_syms,
                               gopts);
  
      lex_fst = NULL;  // we gave ownership to gc.
      
      SequentialBaseFloatMatrixReader feature_reader(feature_rspecifier);
      RandomAccessInt32VectorReader transcript_reader(transcript_rspecifier);
      Int32VectorWriter alignment_writer(alignment_wspecifier);
      
      int32 num_done = 0, num_err = 0, num_retry = 0;
      double tot_like = 0.0;
      kaldi::int64 frame_count = 0;
      for (; !feature_reader.Done(); feature_reader.Next()) {
        std::string utt = feature_reader.Key();
        if (!transcript_reader.HasKey(utt)) {
          KALDI_WARN << "No transcript found for utterance " << utt;
          num_err++;
          continue;
        }
  
        const Matrix<BaseFloat> &features = feature_reader.Value();
        const std::vector<int32> &transcript = transcript_reader.Value(utt);
  
        VectorFst<StdArc> decode_fst;
        if (!gc.CompileGraphFromText(transcript, &decode_fst)) {
          KALDI_WARN << "Problem creating decoding graph for utterance "
                     << utt <<" [serious error]";
          num_err++;
          continue;
        }
        if (features.NumRows() == 0) {
          KALDI_WARN << "Zero-length features for utterance: " << utt;
          num_err++;
          continue;
        }
  
        DecodableAmDiagGmmScaled gmm_decodable(am_gmm, trans_model, features,
                                               acoustic_scale);
  
        
        AlignUtteranceWrapper(align_config, utt,
                              acoustic_scale, &decode_fst, &gmm_decodable,
                              &alignment_writer, NULL,
                              &num_done, &num_err, &num_retry,
                              &tot_like, &frame_count);
      }
      KALDI_LOG << "Overall log-likelihood per frame is " << (tot_like/frame_count)
                << " over " << frame_count<< " frames.";
      KALDI_LOG << "Retried " << num_retry << " out of "
                << (num_done + num_err) << " utterances.";
      KALDI_LOG << "Done " << num_done << ", errors on " << num_err;
      return (num_done != 0 ? 0 : 1);
    } catch(const std::exception &e) {
      std::cerr << e.what();
      return -1;
    }
  }