Blame view
src/sgmm2bin/sgmm2-rescore-lattice.cc
6.14 KB
8dcb6dfcb first commit |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 132 133 134 135 136 137 138 139 140 141 142 143 144 145 146 147 148 149 150 151 152 153 154 155 156 157 158 159 160 161 162 163 164 165 166 167 168 169 |
// sgmm2bin/sgmm2-rescore-lattice.cc // Copyright 2009-2012 Saarland University (Author: Arnab Ghoshal) // Johns Hopkins University (Author: Daniel Povey) // Cisco Systems (Author: Neha Agrawal) // 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 "util/stl-utils.h" #include "sgmm2/am-sgmm2.h" #include "hmm/transition-model.h" #include "fstext/fstext-lib.h" #include "lat/kaldi-lattice.h" #include "lat/lattice-functions.h" #include "sgmm2/decodable-am-sgmm2.h" int main(int argc, char *argv[]) { 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 a new model. " "Usage: sgmm2-rescore-lattice [options] <model-in> <lattice-rspecifier> " "<feature-rspecifier> <lattice-wspecifier> " " e.g.: sgmm2-rescore-lattice 1.mdl ark:1.lats scp:trn.scp ark:2.lats "; kaldi::BaseFloat old_acoustic_scale = 0.0; bool speedup = false; BaseFloat log_prune = 5.0; std::string gselect_rspecifier, spkvecs_rspecifier, utt2spk_rspecifier; kaldi::ParseOptions po(usage); po.Register("old-acoustic-scale", &old_acoustic_scale, "Add the current acoustic scores with some scale."); po.Register("log-prune", &log_prune, "Pruning beam used to reduce number of exp() evaluations."); po.Register("spk-vecs", &spkvecs_rspecifier, "Speaker vectors (rspecifier)"); po.Register("utt2spk", &utt2spk_rspecifier, "rspecifier for utterance to speaker map"); po.Register("gselect", &gselect_rspecifier, "Precomputed Gaussian indices (rspecifier)"); po.Register("speedup", &speedup, "If true, enable a faster version of the computation that " "saves times when there is only one pdf-id on a single frame " "by only sometimes (randomly) computing the probabilities, and " "then scaling them up to preserve corpus-level diagnostics."); po.Read(argc, argv); if (po.NumArgs() != 4) { po.PrintUsage(); exit(1); } if (gselect_rspecifier == "") KALDI_ERR << "--gselect-rspecifier option is required."; std::string model_filename = po.GetArg(1), lats_rspecifier = po.GetArg(2), feature_rspecifier = po.GetArg(3), lats_wspecifier = po.GetArg(4); 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); } RandomAccessInt32VectorVectorReader gselect_reader(gselect_rspecifier); RandomAccessBaseFloatVectorReaderMapped spkvecs_reader(spkvecs_rspecifier, utt2spk_rspecifier); RandomAccessBaseFloatMatrixReader feature_reader(feature_rspecifier); // Read as compact lattice SequentialCompactLatticeReader compact_lattice_reader(lats_rspecifier); // Write as compact lattice. CompactLatticeWriter compact_lattice_writer(lats_wspecifier); int32 num_done = 0, num_err = 0; for (; !compact_lattice_reader.Done(); compact_lattice_reader.Next()) { std::string utt = compact_lattice_reader.Key(); if (!feature_reader.HasKey(utt)) { KALDI_WARN << "No feature found for utterance " << utt; num_err++; continue; } CompactLattice clat = compact_lattice_reader.Value(); compact_lattice_reader.FreeCurrent(); if (old_acoustic_scale != 1.0) fst::ScaleLattice(fst::AcousticLatticeScale(old_acoustic_scale), &clat); const Matrix<BaseFloat> &feats = feature_reader.Value(utt); // Get speaker vectors Sgmm2PerSpkDerivedVars spk_vars; 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" if (!gselect_reader.HasKey(utt) || gselect_reader.Value(utt).size() != feats.NumRows()) { KALDI_WARN << "No Gaussian-selection info available for utterance " << utt << " (or wrong size)"; num_err++; continue; } const std::vector<std::vector<int32> > &gselect = gselect_reader.Value(utt); DecodableAmSgmm2 sgmm2_decodable(am_sgmm, trans_model, feats, gselect, log_prune, &spk_vars); if (!speedup) { if (kaldi::RescoreCompactLattice(&sgmm2_decodable, &clat)) { compact_lattice_writer.Write(utt, clat); num_done++; } else num_err++; } else { BaseFloat speedup_factor = 100.0; if (kaldi::RescoreCompactLatticeSpeedup(trans_model, speedup_factor, &sgmm2_decodable, &clat)) { compact_lattice_writer.Write(utt, clat); num_done++; } else num_err++; } } KALDI_LOG << "Done " << num_done << " lattices, errors on " << num_err; return (num_done != 0 ? 0 : 1); } catch(const std::exception &e) { std::cerr << e.what(); return -1; } } |