// gmmbin/gmm-decode-simple.cc // Copyright 2009-2011 Microsoft Corporation // 2013 Johns Hopkins University // 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 "tree/context-dep.h" #include "hmm/transition-model.h" #include "fstext/fstext-lib.h" #include "decoder/simple-decoder.h" #include "gmm/decodable-am-diag-gmm.h" #include "fstext/lattice-utils.h" #include "lat/kaldi-lattice.h" #include "base/timer.h" int main(int argc, char *argv[]) { try { using namespace kaldi; typedef kaldi::int32 int32; using fst::SymbolTable; using fst::VectorFst; using fst::Fst; using fst::StdArc; using fst::ReadFstKaldiGeneric; const char *usage = "Decode features using GMM-based model.\n" "Viterbi decoding, Only produces linear sequence; any lattice\n" "produced is linear\n" "\n" "Usage: gmm-decode-simple [options] " " [] " "[]"; ParseOptions po(usage); Timer timer; bool allow_partial = true; BaseFloat acoustic_scale = 0.1; std::string word_syms_filename; BaseFloat beam = 16.0; po.Register("beam", &beam, "Decoding log-likelihood beam"); po.Register("acoustic-scale", &acoustic_scale, "Scaling factor for acoustic likelihoods"); po.Register("word-symbol-table", &word_syms_filename, "Symbol table for words [for debug output]"); po.Register("allow-partial", &allow_partial, "Produce output even when final state was not reached"); po.Read(argc, argv); if (po.NumArgs() < 4 || po.NumArgs() > 6) { po.PrintUsage(); exit(1); } std::string model_in_filename = po.GetArg(1), fst_in_filename = po.GetArg(2), feature_rspecifier = po.GetArg(3), words_wspecifier = po.GetArg(4), alignment_wspecifier = po.GetOptArg(5), lattice_wspecifier = po.GetOptArg(6); 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); } Fst *decode_fst = ReadFstKaldiGeneric(fst_in_filename); Int32VectorWriter words_writer(words_wspecifier); Int32VectorWriter alignment_writer(alignment_wspecifier); CompactLatticeWriter clat_writer(lattice_wspecifier); fst::SymbolTable *word_syms = NULL; if (word_syms_filename != "") if (!(word_syms = fst::SymbolTable::ReadText(word_syms_filename))) KALDI_ERR << "Could not read symbol table from file " << word_syms_filename; SequentialBaseFloatMatrixReader feature_reader(feature_rspecifier); BaseFloat tot_like = 0.0; kaldi::int64 frame_count = 0; int num_success = 0, num_fail = 0; SimpleDecoder decoder(*decode_fst, beam); for (; !feature_reader.Done(); feature_reader.Next()) { std::string utt = feature_reader.Key(); Matrix features (feature_reader.Value()); feature_reader.FreeCurrent(); if (features.NumRows() == 0) { KALDI_WARN << "Zero-length utterance: " << utt; num_fail++; continue; } DecodableAmDiagGmmScaled gmm_decodable(am_gmm, trans_model, features, acoustic_scale); decoder.Decode(&gmm_decodable); VectorFst decoded; // linear FST. if ( (allow_partial || decoder.ReachedFinal()) && decoder.GetBestPath(&decoded) ) { if (!decoder.ReachedFinal()) KALDI_WARN << "Decoder did not reach end-state, " << "outputting partial traceback since --allow-partial=true"; num_success++; std::vector alignment; std::vector words; LatticeWeight weight; frame_count += features.NumRows(); GetLinearSymbolSequence(decoded, &alignment, &words, &weight); words_writer.Write(utt, words); if (alignment_wspecifier != "") alignment_writer.Write(utt, alignment); if (lattice_wspecifier != "") { // We'll write the lattice without acoustic scaling. if (acoustic_scale != 0.0) fst::ScaleLattice(fst::AcousticLatticeScale(1.0 / acoustic_scale), &decoded); fst::VectorFst clat; ConvertLattice(decoded, &clat, true); clat_writer.Write(utt, clat); } if (word_syms != NULL) { std::cerr << utt << ' '; for (size_t i = 0; i < words.size(); i++) { std::string s = word_syms->Find(words[i]); if (s == "") KALDI_ERR << "Word-id " << words[i] <<" not in symbol table."; std::cerr << s << ' '; } std::cerr << '\n'; } BaseFloat like = -ConvertToCost(weight); tot_like += like; KALDI_LOG << "Log-like per frame for utterance " << utt << " is " << (like / features.NumRows()) << " over " << features.NumRows() << " frames."; } else { num_fail++; KALDI_WARN << "Did not successfully decode utterance " << utt << ", len = " << features.NumRows(); } } double elapsed = timer.Elapsed(); KALDI_LOG << "Time taken "<< elapsed << "s: real-time factor assuming 100 frames/sec is " << (elapsed*100.0/frame_count); KALDI_LOG << "Done " << num_success << " utterances, failed for " << num_fail; KALDI_LOG << "Overall log-likelihood per frame is " << (tot_like/frame_count) << " over " << frame_count<<" frames."; delete word_syms; delete decode_fst; if (num_success != 0) return 0; else return 1; } catch(const std::exception &e) { std::cerr << e.what(); return -1; } }