lattice-rescore-mapped.cc File Reference

#include "base/kaldi-common.h"
#include "util/common-utils.h"
#include "util/stl-utils.h"
#include "hmm/transition-model.h"
#include "fstext/fstext-lib.h"
#include "lat/kaldi-lattice.h"
#include "lat/lattice-functions.h"

Include dependency graph for lattice-rescore-mapped.cc:

Go to the source code of this file.

Namespaces
	kaldi
	This code computes Goodness of Pronunciation (GOP) and extracts phone-level pronunciation feature for mispronunciations detection tasks, the reference:

Functions
void	LatticeAcousticRescore (const TransitionModel &trans_model, const Matrix< BaseFloat > &log_likes, const std::vector< int32 > &state_times, Lattice *lat)
int	main (int argc, char *argv[])

Function Documentation

main()

int main	(	int	argc,
		char *	argv[]
	)

Definition at line 74 of file lattice-rescore-mapped.cc.

References fst::AcousticLatticeScale(), fst::ConvertLattice(), SequentialTableReader< Holder >::Done(), SequentialTableReader< Holder >::FreeCurrent(), ParseOptions::GetArg(), RandomAccessTableReader< Holder >::HasKey(), KALDI_ERR, KALDI_LOG, KALDI_WARN, SequentialTableReader< Holder >::Key(), kaldi::LatticeAcousticRescore(), kaldi::LatticeStateTimes(), SequentialTableReader< Holder >::Next(), ParseOptions::NumArgs(), MatrixBase< Real >::NumRows(), ParseOptions::PrintUsage(), ParseOptions::Read(), TransitionModel::Read(), ParseOptions::Register(), fst::ScaleLattice(), Input::Stream(), RandomAccessTableReader< Holder >::Value(), SequentialTableReader< Holder >::Value(), and TableWriter< Holder >::Write().

                                 {
  try {
    using namespace kaldi;
    typedef kaldi::int32 int32;
    typedef kaldi::int64 int64;
    using fst::SymbolTable;
    using fst::VectorFst;
    using fst::StdArc;

    const char *usage =
        "Replace the acoustic scores on a lattice using log-likelihoods read in\n"
        "as a matrix for each utterance, indexed (frame, pdf-id).  This does the same\n"
        "as (e.g.) gmm-rescore-lattice, but from a matrix.  The \"mapped\" means that\n"
        "the transition-model is used to map transition-ids to pdf-ids.  (c.f.\n"
        "latgen-faster-mapped).  Note: <transition-model-in> can be any type of\n"
        "model file, e.g. GMM-based or neural-net based; only the transition model is read.\n"
        "\n"
        "Usage: lattice-rescore-mapped [options] <transition-model-in> <lattice-rspecifier> "
        "<loglikes-rspecifier> <lattice-wspecifier>\n"
        " e.g.: nnet-logprob [args] .. | lattice-rescore-mapped final.mdl ark:1.lats ark:- ark:2.lats\n";

    kaldi::BaseFloat old_acoustic_scale = 0.0;
    kaldi::ParseOptions po(usage);
    po.Register("old-acoustic-scale", &old_acoustic_scale,
                "Add in the scores in the input lattices with this scale, rather "
                "than discarding them.");
    po.Read(argc, argv);

    if (po.NumArgs() != 4) {
      po.PrintUsage();
      exit(1);
    }

    std::string model_filename = po.GetArg(1),
        lats_rspecifier = po.GetArg(2),
        loglike_rspecifier = po.GetArg(3),
        lats_wspecifier = po.GetArg(4);

    TransitionModel trans_model;
    {
      bool binary;
      Input ki(model_filename, &binary);
      trans_model.Read(ki.Stream(), binary);
      // Ignore what follows it in the model.
    }

    RandomAccessBaseFloatMatrixReader loglike_reader(loglike_rspecifier);
    // Read as regular lattice
    SequentialLatticeReader lattice_reader(lats_rspecifier);
    // Write as compact lattice.
    CompactLatticeWriter compact_lattice_writer(lats_wspecifier);

    int32 num_done = 0, num_err = 0;
    int64 num_frames = 0;
    for (; !lattice_reader.Done(); lattice_reader.Next()) {
      std::string key = lattice_reader.Key();
      if (!loglike_reader.HasKey(key)) {
        KALDI_WARN << "No log-likes found for utterance " << key << ". Skipping";
        num_err++;
        continue;
      }

      Lattice lat = lattice_reader.Value();
      lattice_reader.FreeCurrent();
      if (old_acoustic_scale != 1.0)
        fst::ScaleLattice(fst::AcousticLatticeScale(old_acoustic_scale), &lat);

      kaldi::uint64 props = lat.Properties(fst::kFstProperties, false);
      if (!(props & fst::kTopSorted)) {
        if (fst::TopSort(&lat) == false)
          KALDI_ERR << "Cycles detected in lattice.";
      }

      std::vector<int32> state_times;
      int32 max_time = kaldi::LatticeStateTimes(lat, &state_times);
      const Matrix<BaseFloat> &log_likes = loglike_reader.Value(key);
      if (log_likes.NumRows() != max_time) {
        KALDI_WARN << "Skipping utterance " << key << " since number of time "
                   << "frames in lattice ("<< max_time << ") differ from "
                   << "number of frames in log-likelihoods (" << log_likes.NumRows() << ").";
        num_err++;
        continue;
      }

      kaldi::LatticeAcousticRescore(trans_model, log_likes, state_times,
                                    &lat);
      CompactLattice clat_out;
      ConvertLattice(lat, &clat_out);
      compact_lattice_writer.Write(key, clat_out);
      num_done++;
      num_frames += log_likes.NumRows();
    }

    KALDI_LOG << "Done " << num_done << " lattices, " << num_err
              << " with errors, #frames is " << num_frames;
    return (num_done != 0 ? 0 : 1);
  } catch(const std::exception &e) {
    std::cerr << e.what();
    return -1;
  }
}