// bin/latgen-faster-mapped.cc // Copyright 2009-2012 Microsoft Corporation, Karel Vesely // 2013 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 "base/kaldi-common.h" #include "util/common-utils.h" #include "tree/context-dep.h" #include "hmm/transition-model.h" #include "fstext/fstext-lib.h" #include "decoder/decoder-wrappers.h" #include "decoder/decodable-matrix.h" #include "base/timer.h" 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 = "Generate lattices, reading log-likelihoods as matrices\n" " (model is needed only for the integer mappings in its transition-model)\n" "Usage: latgen-faster-mapped [options] trans-model-in (fst-in|fsts-rspecifier) loglikes-rspecifier" " lattice-wspecifier [ words-wspecifier [alignments-wspecifier] ]\n"; ParseOptions po(usage); Timer timer; bool allow_partial = false; BaseFloat acoustic_scale = 0.1; LatticeFasterDecoderConfig config; std::string word_syms_filename; config.Register(&po); 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, "If true, produce output even if end 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_str = po.GetArg(2), feature_rspecifier = po.GetArg(3), lattice_wspecifier = po.GetArg(4), words_wspecifier = po.GetOptArg(5), alignment_wspecifier = po.GetOptArg(6); TransitionModel trans_model; ReadKaldiObject(model_in_filename, &trans_model); bool determinize = config.determinize_lattice; CompactLatticeWriter compact_lattice_writer; LatticeWriter lattice_writer; if (! (determinize ? compact_lattice_writer.Open(lattice_wspecifier) : lattice_writer.Open(lattice_wspecifier))) KALDI_ERR << "Could not open table for writing lattices: " << lattice_wspecifier; Int32VectorWriter words_writer(words_wspecifier); Int32VectorWriter alignment_writer(alignment_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; double tot_like = 0.0; kaldi::int64 frame_count = 0; int num_success = 0, num_fail = 0; if (ClassifyRspecifier(fst_in_str, NULL, NULL) == kNoRspecifier) { SequentialBaseFloatMatrixReader loglike_reader(feature_rspecifier); // Input FST is just one FST, not a table of FSTs. Fst *decode_fst = fst::ReadFstKaldiGeneric(fst_in_str); timer.Reset(); { LatticeFasterDecoder decoder(*decode_fst, config); for (; !loglike_reader.Done(); loglike_reader.Next()) { std::string utt = loglike_reader.Key(); Matrix loglikes (loglike_reader.Value()); loglike_reader.FreeCurrent(); if (loglikes.NumRows() == 0) { KALDI_WARN << "Zero-length utterance: " << utt; num_fail++; continue; } DecodableMatrixScaledMapped decodable(trans_model, loglikes, acoustic_scale); double like; if (DecodeUtteranceLatticeFaster( decoder, 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 += loglikes.NumRows(); num_success++; } else num_fail++; } } delete decode_fst; // delete this only after decoder goes out of scope. } else { // We have different FSTs for different utterances. SequentialTableReader fst_reader(fst_in_str); RandomAccessBaseFloatMatrixReader loglike_reader(feature_rspecifier); for (; !fst_reader.Done(); fst_reader.Next()) { std::string utt = fst_reader.Key(); if (!loglike_reader.HasKey(utt)) { KALDI_WARN << "Not decoding utterance " << utt << " because no loglikes available."; num_fail++; continue; } const Matrix &loglikes = loglike_reader.Value(utt); if (loglikes.NumRows() == 0) { KALDI_WARN << "Zero-length utterance: " << utt; num_fail++; continue; } LatticeFasterDecoder decoder(fst_reader.Value(), config); DecodableMatrixScaledMapped decodable(trans_model, loglikes, acoustic_scale); double like; if (DecodeUtteranceLatticeFaster( decoder, 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 += loglikes.NumRows(); num_success++; } else num_fail++; } } 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; if (num_success != 0) return 0; else return 1; } catch(const std::exception &e) { std::cerr << e.what(); return -1; } }