// gmmbin/gmm-align.cc // Copyright 2009-2012 Microsoft Corporation // 2012-2014 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/am-diag-gmm.h" #include "hmm/transition-model.h" #include "fstext/fstext-utils.h" #include "decoder/decoder-wrappers.h" #include "decoder/training-graph-compiler.h" #include "gmm/decodable-am-diag-gmm.h" #include "lat/kaldi-lattice.h" // for {Compact}LatticeArc int main(int argc, char *argv[]) { try { using namespace kaldi; typedef kaldi::int32 int32; using fst::SymbolTable; using fst::VectorFst; using fst::StdArc; const char *usage = "Align features given [GMM-based] models.\n" "Usage: gmm-align [options] tree-in model-in lexicon-fst-in feature-rspecifier " "transcriptions-rspecifier alignments-wspecifier\n" "e.g.: \n" " gmm-align tree 1.mdl lex.fst scp:train.scp " "'ark:sym2int.pl -f 2- words.txt text|' ark:1.ali\n"; ParseOptions po(usage); AlignConfig align_config; BaseFloat acoustic_scale = 1.0; std::string disambig_rxfilename; TrainingGraphCompilerOptions gopts; align_config.Register(&po); po.Register("acoustic-scale", &acoustic_scale, "Scaling factor for acoustic likelihoods"); po.Register("read-disambig-syms", &disambig_rxfilename, "File containing " "list of disambiguation symbols in phone symbol table"); gopts.Register(&po); po.Read(argc, argv); if (po.NumArgs() != 6) { po.PrintUsage(); exit(1); } std::string tree_in_filename = po.GetArg(1); std::string model_in_filename = po.GetArg(2); std::string lex_in_filename = po.GetArg(3); std::string feature_rspecifier = po.GetArg(4); std::string transcript_rspecifier = po.GetArg(5); std::string alignment_wspecifier = po.GetArg(6); ContextDependency ctx_dep; ReadKaldiObject(tree_in_filename, &ctx_dep); TransitionModel trans_model; AmDiagGmm am_gmm; { bool binary; Input ki(model_in_filename, &binary); trans_model.Read(ki.Stream(), binary); am_gmm.Read(ki.Stream(), binary); } // ownership will be taken by gc. VectorFst *lex_fst = fst::ReadFstKaldi(lex_in_filename); std::vector disambig_syms; if (disambig_rxfilename != "") if (!ReadIntegerVectorSimple(disambig_rxfilename, &disambig_syms)) KALDI_ERR << "fstcomposecontext: Could not read disambiguation symbols from " << disambig_rxfilename; TrainingGraphCompiler gc(trans_model, ctx_dep, lex_fst, disambig_syms, gopts); lex_fst = NULL; // we gave ownership to gc. SequentialBaseFloatMatrixReader feature_reader(feature_rspecifier); RandomAccessInt32VectorReader transcript_reader(transcript_rspecifier); Int32VectorWriter alignment_writer(alignment_wspecifier); int32 num_done = 0, num_err = 0, num_retry = 0; double tot_like = 0.0; kaldi::int64 frame_count = 0; for (; !feature_reader.Done(); feature_reader.Next()) { std::string utt = feature_reader.Key(); if (!transcript_reader.HasKey(utt)) { KALDI_WARN << "No transcript found for utterance " << utt; num_err++; continue; } const Matrix &features = feature_reader.Value(); const std::vector &transcript = transcript_reader.Value(utt); VectorFst decode_fst; if (!gc.CompileGraphFromText(transcript, &decode_fst)) { KALDI_WARN << "Problem creating decoding graph for utterance " << utt <<" [serious error]"; num_err++; continue; } if (features.NumRows() == 0) { KALDI_WARN << "Zero-length features for utterance: " << utt; num_err++; continue; } DecodableAmDiagGmmScaled gmm_decodable(am_gmm, trans_model, features, acoustic_scale); AlignUtteranceWrapper(align_config, utt, acoustic_scale, &decode_fst, &gmm_decodable, &alignment_writer, NULL, &num_done, &num_err, &num_retry, &tot_like, &frame_count); } KALDI_LOG << "Overall log-likelihood per frame is " << (tot_like/frame_count) << " over " << frame_count<< " frames."; KALDI_LOG << "Retried " << num_retry << " out of " << (num_done + num_err) << " utterances."; KALDI_LOG << "Done " << num_done << ", errors on " << num_err; return (num_done != 0 ? 0 : 1); } catch(const std::exception &e) { std::cerr << e.what(); return -1; } }