acc-tree-stats.cc File Reference

#include "base/kaldi-common.h"
#include "util/common-utils.h"
#include "tree/context-dep.h"
#include "tree/build-tree-utils.h"
#include "hmm/transition-model.h"
#include "hmm/tree-accu.h"

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Functions
int	main (int argc, char *argv[])
	Accumulate tree statistics for decision tree training. More...

Function Documentation

main()

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

Accumulate tree statistics for decision tree training.

The program reads in a feature archive, and the corresponding alignments, and generates the sufficient statistics for the decision tree creation. Context width and central phone position are used to identify the contexts.Transition model is used as an input to identify the PDF's and the phones.

Definition at line 34 of file acc-tree-stats.cc.

References kaldi::AccumulateTreeStats(), kaldi::DeleteBuildTreeStats(), SequentialTableReader< Holder >::Done(), ParseOptions::GetArg(), ParseOptions::GetOptArg(), RandomAccessTableReader< Holder >::HasKey(), KALDI_LOG, KALDI_WARN, SequentialTableReader< Holder >::Key(), SequentialTableReader< Holder >::Next(), ParseOptions::NumArgs(), MatrixBase< Real >::NumRows(), ParseOptions::PrintUsage(), ParseOptions::Read(), TransitionModel::Read(), AccumulateTreeStatsOptions::Register(), ParseOptions::Register(), Output::Stream(), Input::Stream(), RandomAccessTableReader< Holder >::Value(), SequentialTableReader< Holder >::Value(), and kaldi::WriteBuildTreeStats().

                                 {
  using namespace kaldi;
  typedef kaldi::int32 int32;
  try {
    const char *usage =
        "Accumulate statistics for phonetic-context tree building.\n"
        "Usage:  acc-tree-stats [options] <model-in> <features-rspecifier> <alignments-rspecifier> <tree-accs-out>\n"
        "e.g.: \n"
        " acc-tree-stats 1.mdl scp:train.scp ark:1.ali 1.tacc\n";

    bool binary = true;
    AccumulateTreeStatsOptions opts;
    ParseOptions po(usage);
    po.Register("binary", &binary, "Write output in binary mode");
    opts.Register(&po);

    po.Read(argc, argv);

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

    std::string model_filename = po.GetArg(1),
        feature_rspecifier = po.GetArg(2),
        alignment_rspecifier = po.GetArg(3),
        accs_out_wxfilename = po.GetOptArg(4);


    AccumulateTreeStatsInfo acc_tree_stats_info(opts);

    TransitionModel trans_model;
    {
      bool binary;
      Input ki(model_filename, &binary);
      trans_model.Read(ki.Stream(), binary);
      // There is more in this file but we don't need it.
    }

    SequentialBaseFloatMatrixReader feature_reader(feature_rspecifier);
    RandomAccessInt32VectorReader alignment_reader(alignment_rspecifier);

    std::map<EventType, GaussClusterable*> tree_stats;

    int num_done = 0, num_no_alignment = 0, num_other_error = 0;

    for (; !feature_reader.Done(); feature_reader.Next()) {
      std::string key = feature_reader.Key();
      if (!alignment_reader.HasKey(key)) {
        num_no_alignment++;
      } else {
        const Matrix<BaseFloat> &mat = feature_reader.Value();
        const std::vector<int32> &alignment = alignment_reader.Value(key);

        if (alignment.size() != mat.NumRows()) {
          KALDI_WARN << "Alignments has wrong size "<< (alignment.size())<<" vs. "<< (mat.NumRows());
          num_other_error++;
          continue;
        }

        AccumulateTreeStats(trans_model,
                            acc_tree_stats_info,
                            alignment,
                            mat,
                            &tree_stats);
        num_done++;
        if (num_done % 1000 == 0)
          KALDI_LOG << "Processed " << num_done << " utterances.";
      }
    }

    BuildTreeStatsType stats;  // vectorized form.

    for (std::map<EventType, GaussClusterable*>::const_iterator iter = tree_stats.begin();
         iter != tree_stats.end();
         ++iter) {
      stats.push_back(std::make_pair(iter->first, iter->second));
    }
    tree_stats.clear();

    {
      Output ko(accs_out_wxfilename, binary);
      WriteBuildTreeStats(ko.Stream(), binary, stats);
    }
    KALDI_LOG << "Accumulated stats for " << num_done << " files, "
              << num_no_alignment << " failed due to no alignment, "
              << num_other_error << " failed for other reasons.";
    KALDI_LOG << "Number of separate stats (context-dependent states) is "
              << stats.size();
    DeleteBuildTreeStats(&stats);
    if (num_done != 0) return 0;
    else return 1;
  } catch(const std::exception &e) {
    std::cerr << e.what();
    return -1;
  }
}