sgmm2-acc-stats-gpost.cc File Reference

#include "base/kaldi-common.h"
#include "util/common-utils.h"
#include "sgmm2/am-sgmm2.h"
#include "hmm/transition-model.h"
#include "sgmm2/estimate-am-sgmm2.h"

Include dependency graph for sgmm2-acc-stats-gpost.cc:

Go to the source code of this file.

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

Function Documentation

main()

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

Definition at line 29 of file sgmm2-acc-stats-gpost.cc.

References TransitionModel::Accumulate(), MleAmSgmm2Accs::AccumulateFromPosteriors(), Sgmm2PerSpkDerivedVars::Clear(), MleAmSgmm2Accs::CommitStatsForSpk(), AmSgmm2::ComputePerFrameVars(), AmSgmm2::ComputePerSpkDerivedVars(), SequentialTableReader< Holder >::Done(), Sgmm2PerSpkDerivedVars::Empty(), ParseOptions::GetArg(), RandomAccessTableReader< Holder >::HasKey(), RandomAccessTableReaderMapped< Holder >::HasKey(), rnnlm::i, TransitionModel::InitStats(), RandomAccessTableReaderMapped< Holder >::IsOpen(), rnnlm::j, KALDI_LOG, KALDI_WARN, SequentialTableReader< Holder >::Key(), SequentialTableReader< Holder >::Next(), ParseOptions::NumArgs(), MatrixBase< Real >::NumRows(), ParseOptions::PrintUsage(), ParseOptions::Read(), TransitionModel::Read(), AmSgmm2::Read(), ParseOptions::Register(), MleAmSgmm2Accs::ResizeAccumulators(), MatrixBase< Real >::Row(), Sgmm2PerSpkDerivedVars::SetSpeakerVector(), Output::Stream(), Input::Stream(), kaldi::StringToSgmmUpdateFlags(), TransitionModel::TransitionIdToPdf(), RandomAccessTableReader< Holder >::Value(), SequentialTableReader< Holder >::Value(), RandomAccessTableReaderMapped< Holder >::Value(), MleAmSgmm2Accs::Write(), and VectorBase< Real >::Write().

                                 {
  using namespace kaldi;
  try {
    const char *usage =
        "Accumulate stats for SGMM training, given Gaussian-level posteriors\n"
        "Usage: sgmm2-acc-stats-gpost [options] <model-in> <feature-rspecifier> "
        "<gpost-rspecifier> <stats-out>\n"
        "e.g.: sgmm2-acc-stats-gpost 1.mdl 1.ali scp:train.scp ark, s, cs:- 1.acc\n";

    ParseOptions po(usage);
    bool binary = true;
    std::string spkvecs_rspecifier, utt2spk_rspecifier;
    std::string update_flags_str = "vMNwcSt";
    BaseFloat rand_prune = 1.0e-05;

    po.Register("binary", &binary, "Write output in binary mode");
    po.Register("spk-vecs", &spkvecs_rspecifier, "Speaker vectors (rspecifier)");
    po.Register("utt2spk", &utt2spk_rspecifier,
                "rspecifier for utterance to speaker map");
    po.Register("rand-prune", &rand_prune, "Pruning threshold for posteriors");
    po.Register("update-flags", &update_flags_str, "Which SGMM parameters to update: subset of vMNwcS.");
    po.Read(argc, argv);

    kaldi::SgmmUpdateFlagsType acc_flags = StringToSgmmUpdateFlags(update_flags_str);

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

    std::string model_filename = po.GetArg(1),
        feature_rspecifier = po.GetArg(2),
        gpost_rspecifier = po.GetArg(3),
        accs_wxfilename = po.GetArg(4);

    using namespace kaldi;
    typedef kaldi::int32 int32;

    // Initialize the readers before the model, as this can avoid
    // crashes on systems with low virtual memory.
    SequentialBaseFloatMatrixReader feature_reader(feature_rspecifier);
    RandomAccessSgmm2GauPostReader gpost_reader(gpost_rspecifier);
    RandomAccessBaseFloatVectorReaderMapped spkvecs_reader(spkvecs_rspecifier,
                                                           utt2spk_rspecifier);
    RandomAccessTokenReader utt2spk_map(utt2spk_rspecifier);
    
    AmSgmm2 am_sgmm;
    TransitionModel trans_model;
    {
      bool binary;
      Input ki(model_filename, &binary);
      trans_model.Read(ki.Stream(), binary);
      am_sgmm.Read(ki.Stream(), binary);
    }

    Vector<double> transition_accs;
    trans_model.InitStats(&transition_accs);
    MleAmSgmm2Accs sgmm_accs(rand_prune);
    sgmm_accs.ResizeAccumulators(am_sgmm, acc_flags, (spkvecs_rspecifier != ""));

    double tot_t = 0.0;
    kaldi::Sgmm2PerFrameDerivedVars per_frame_vars;
    
    int32 num_done = 0, num_err = 0;
    std::string cur_spk;
    Sgmm2PerSpkDerivedVars spk_vars;
    
    for (; !feature_reader.Done(); feature_reader.Next()) {
      std::string utt = feature_reader.Key();
      std::string spk = utt;

      if (!utt2spk_rspecifier.empty()) {
        if (!utt2spk_map.HasKey(utt)) {
          KALDI_WARN << "utt2spk map does not have value for " << utt
                     << ", ignoring this utterance.";
          continue;
        } else { spk = utt2spk_map.Value(utt); }
      }

      if (spk != cur_spk && cur_spk != "")
        sgmm_accs.CommitStatsForSpk(am_sgmm, spk_vars);
      
      if (spk != cur_spk || spk_vars.Empty()) {
        spk_vars.Clear();
        if (spkvecs_reader.IsOpen()) {
          if (spkvecs_reader.HasKey(utt)) {
            spk_vars.SetSpeakerVector(spkvecs_reader.Value(utt));
            am_sgmm.ComputePerSpkDerivedVars(&spk_vars);
          } else {
            KALDI_WARN << "Cannot find speaker vector for " << utt;
            num_err++;
            continue;
          }
        } // else spk_vars is "empty"
      }

      cur_spk = spk;      
      
      const Matrix<BaseFloat> &mat = feature_reader.Value();
      if (!gpost_reader.HasKey(utt) ||
          gpost_reader.Value(utt).size() != mat.NumRows()) {
        KALDI_WARN << "No Gaussian-posterior information for utterance "
                   << utt << " (or wrong size).";
        num_err++;
        continue;
      }
      const Sgmm2GauPost &gpost = gpost_reader.Value(utt);
      
      num_done++;
      BaseFloat tot_weight = 0.0;

      for (size_t i = 0; i < gpost.size(); i++) {
        const std::vector<int32> &gselect = gpost[i].gselect;
        am_sgmm.ComputePerFrameVars(mat.Row(i), gselect, spk_vars,
                                    &per_frame_vars);

        for (size_t j = 0; j < gpost[i].tids.size(); j++) {
          int32 tid = gpost[i].tids[j],  // transition identifier.
              pdf_id = trans_model.TransitionIdToPdf(tid);
          
          BaseFloat weight = gpost[i].posteriors[j].Sum();
          trans_model.Accumulate(weight, tid, &transition_accs);
          sgmm_accs.AccumulateFromPosteriors(am_sgmm, per_frame_vars,
                                             gpost[i].posteriors[j],
                                             pdf_id, &spk_vars);
          tot_weight += weight;
        }
      }

      tot_t += tot_weight;
      if (num_done % 50 == 0)
        KALDI_LOG << "Processed " << num_done << " utterances";      
    }
    sgmm_accs.CommitStatsForSpk(am_sgmm, spk_vars); // for last speaker
    
    KALDI_LOG << "Overall number of frames is " << tot_t;
    KALDI_LOG << "Done " << num_done << " files, "
              << num_err << " with errors.";

    {
      Output ko(accs_wxfilename, binary);
      transition_accs.Write(ko.Stream(), binary);
      sgmm_accs.Write(ko.Stream(), binary);
    }
    KALDI_LOG << "Written accs.";
    return (num_done != 0 ? 0 : 1);
  } catch(const std::exception &e) {
    std::cerr << e.what();
    return -1;
  }
}