// gmmbin/gmm-latgen-map.cc // Copyright 2012 Neha Agrawal, Cisco Systems; // Johns Hopkins University (author: Daniel Povey) // 2014 Guoguo Chen // 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 #include #include "base/kaldi-common.h" #include "util/common-utils.h" #include "gmm/am-diag-gmm.h" #include "gmm/mle-am-diag-gmm.h" #include "hmm/transition-model.h" #include "transform/fmllr-diag-gmm.h" #include "fstext/fstext-lib.h" #include "decoder/decoder-wrappers.h" #include "gmm/decodable-am-diag-gmm.h" #include "base/timer.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::Fst; using fst::StdArc; const char *usage = "Decode features using GMM-based model. Note: the input\n" " will typically be piped in from gmm-est-map.\n" "Note: is only needed for the transition-model, which isn't\n" "included in .\n" "\n" "Usage: gmm-latgen-map [options] " " " " [ [ ] ]\n"; ParseOptions po(usage); bool binary = true; bool allow_partial = true; BaseFloat acoustic_scale = 0.1; std::string word_syms_filename, utt2spk_rspecifier; LatticeFasterDecoderConfig decoder_opts; decoder_opts.Register(&po); po.Register("utt2spk", &utt2spk_rspecifier, "rspecifier for utterance to " "speaker map"); po.Register("binary", &binary, "Write output in binary mode"); 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() < 5 || po.NumArgs() > 7) { po.PrintUsage(); exit(1); } std::string model_in_filename = po.GetArg(1), gmms_rspecifier = po.GetArg(2), fst_in_filename = po.GetArg(3), feature_rspecifier = po.GetArg(4), lattice_wspecifier = po.GetArg(5), words_wspecifier = po.GetOptArg(6), alignment_wspecifier = po.GetOptArg(7); TransitionModel trans_model; { bool binary_read; Input is(model_in_filename, &binary_read); trans_model.Read(is.Stream(), binary_read); } RandomAccessMapAmDiagGmmReaderMapped gmms_reader(gmms_rspecifier, utt2spk_rspecifier); Int32VectorWriter words_writer(words_wspecifier); Int32VectorWriter alignment_writer(alignment_wspecifier); bool determinize = decoder_opts.determinize_lattice; if (!determinize) KALDI_WARN << "determinize is set to FASLE ..."; CompactLatticeWriter compact_lattice_writer; LatticeWriter lattice_writer; if (lattice_wspecifier != "") { if (! (determinize ? compact_lattice_writer.Open(lattice_wspecifier) : lattice_writer.Open(lattice_wspecifier))) KALDI_ERR << "Could not open table for writing lattices: " << lattice_wspecifier; } fst::SymbolTable *word_syms = NULL; if (word_syms_filename != "") { word_syms = fst::SymbolTable::ReadText(word_syms_filename); if (!word_syms) { KALDI_ERR << "Could not read symbol table from file " << word_syms_filename; } } BaseFloat tot_like = 0.0; kaldi::int64 frame_count = 0; int num_success = 0, num_fail = 0; Timer timer; if (ClassifyRspecifier(fst_in_filename, NULL, NULL) == kNoRspecifier) { // Input FST is just one FST, not a table of FSTs. Fst *decode_fst = fst::ReadFstKaldiGeneric(fst_in_filename); SequentialBaseFloatMatrixReader feature_reader(feature_rspecifier); for (; !feature_reader.Done(); feature_reader.Next()) { string utt = feature_reader.Key(); if (!gmms_reader.HasKey(utt)) { KALDI_WARN << "Utterance " << utt << " has no corresponding MAP model skipping this utterance."; num_fail++; continue; } AmDiagGmm am_gmm; am_gmm.CopyFromAmDiagGmm(gmms_reader.Value(utt)); Matrix features(feature_reader.Value()); feature_reader.FreeCurrent(); if (features.NumRows() == 0) { KALDI_WARN << "Zero-length utterance: " << utt; num_fail++; continue; } LatticeFasterDecoder decoder(*decode_fst, decoder_opts); kaldi::DecodableAmDiagGmmScaled gmm_decodable(am_gmm, trans_model, features, acoustic_scale); double like; if (DecodeUtteranceLatticeFaster( decoder, gmm_decodable, trans_model, word_syms, utt, acoustic_scale, determinize, allow_partial, &alignment_writer, &words_writer, &compact_lattice_writer, &lattice_writer, &like)) { tot_like += like; frame_count += features.NumRows(); num_success++; } else num_fail++; } // end looping over all utterances } else { RandomAccessTableReader fst_reader(fst_in_filename); SequentialBaseFloatMatrixReader feature_reader(feature_rspecifier); for (; !feature_reader.Done(); feature_reader.Next()) { string utt = feature_reader.Key(); if (!fst_reader.HasKey(utt)) { KALDI_WARN << "Utterance " << utt << " has no corresponding FST" << "skipping this utterance."; num_fail++; continue; } if (!gmms_reader.HasKey(utt)) { KALDI_WARN << "Utterance " << utt << " has no corresponding MAP model skipping this utterance."; num_fail++; continue; } AmDiagGmm am_gmm; am_gmm.CopyFromAmDiagGmm(gmms_reader.Value(utt)); Matrix features(feature_reader.Value()); feature_reader.FreeCurrent(); if (features.NumRows() == 0) { KALDI_WARN << "Zero-length utterance: " << utt; num_fail++; continue; } LatticeFasterDecoder decoder(fst_reader.Value(utt), decoder_opts); kaldi::DecodableAmDiagGmmScaled gmm_decodable(am_gmm, trans_model, features, acoustic_scale); double like; if (DecodeUtteranceLatticeFaster( decoder, gmm_decodable, trans_model, word_syms, utt, acoustic_scale, determinize, allow_partial, &alignment_writer, &words_writer, &compact_lattice_writer, &lattice_writer, &like)) { tot_like += like; frame_count += features.NumRows(); num_success++; } else num_fail++; } // end looping over all utterances } KALDI_LOG << "Average log-likelihood per frame is " << (tot_like / frame_count) << " over " << frame_count << " frames."; double elapsed = timer.Elapsed(); KALDI_LOG << "Time taken [excluding initialization] " << 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; delete word_syms; return (num_success != 0 ? 0 : 1); } catch(const std::exception& e) { std::cerr << e.what(); return -1; } }