Blame view
src/gmmbin/gmm-est-rescale.cc
3.62 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 |
// gmmbin/gmm-est-rescale.cc // Copyright 2012 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/indirect-diff-diag-gmm.h" #include "tree/context-dep.h" #include "hmm/transition-model.h" int main(int argc, char *argv[]) { using namespace kaldi; typedef kaldi::int32 int32; try { const char *usage = "Do \"re-scaling\" re-estimation of GMM-based model " " (this update changes the model as features change, but preserves " " the difference between the model and the features, to keep " " the effect of any prior discriminative training). Used in fMPE. " " Does not update the transitions or weights. " "Usage: gmm-est-rescale [options] <model-in> <old-stats-in> <new-stats-in> <model-out> " "e.g.: gmm-est-rescale 1.mdl old.acc new.acc 2.mdl "; bool binary_write = true; MleDiagGmmOptions opts; // Not passed to command-line-- just a mechanism to // ensure our options have the same default values as those ones. BaseFloat min_variance = opts.min_variance; BaseFloat min_gaussian_occupancy = opts.min_gaussian_occupancy; ParseOptions po(usage); po.Register("binary", &binary_write, "Write output in binary mode"); po.Register("min-variance", &min_variance, "Variance floor (absolute variance)."); po.Register("min-gaussian-occupancy", &min_gaussian_occupancy, "Minimum occupancy to update a Gaussian."); po.Read(argc, argv); if (po.NumArgs() != 4) { po.PrintUsage(); exit(1); } std::string model_rxfilename = po.GetArg(1), old_stats_rxfilename = po.GetArg(2), new_stats_rxfilename = po.GetArg(3), model_wxfilename = po.GetArg(4); AmDiagGmm am_gmm; TransitionModel trans_model; { bool binary_read; Input ki(model_rxfilename, &binary_read); trans_model.Read(ki.Stream(), binary_read); am_gmm.Read(ki.Stream(), binary_read); } AccumAmDiagGmm old_gmm_accs, new_gmm_accs; { Vector<double> transition_accs; bool binary; Input ki(old_stats_rxfilename, &binary); transition_accs.Read(ki.Stream(), binary); old_gmm_accs.Read(ki.Stream(), binary, true); } { Vector<double> transition_accs; bool binary; Input ki(new_stats_rxfilename, &binary); transition_accs.Read(ki.Stream(), binary); new_gmm_accs.Read(ki.Stream(), binary, true); } DoRescalingUpdate(old_gmm_accs, new_gmm_accs, min_variance, min_gaussian_occupancy, &am_gmm); { Output ko(model_wxfilename, binary_write); trans_model.Write(ko.Stream(), binary_write); am_gmm.Write(ko.Stream(), binary_write); } KALDI_LOG << "Rescaled model and wrote to " << model_wxfilename; return 0; } catch(const std::exception &e) { std::cerr << e.what() << ' '; return -1; } } |