// gmmbin/gmm-align-compiled.cc // Copyright 2009-2013 Microsoft Corporation // 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 "hmm/hmm-utils.h" #include "fstext/fstext-lib.h" #include "decoder/decoder-wrappers.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-compiled [options] " " [scores-wspecifier]\n" "e.g.: \n" " gmm-align-compiled 1.mdl ark:graphs.fsts scp:train.scp ark:1.ali\n" "or:\n" " compile-train-graphs tree 1.mdl lex.fst 'ark:sym2int.pl -f 2- words.txt text|' \\\n" " ark:- | gmm-align-compiled 1.mdl ark:- scp:train.scp t, ark:1.ali\n"; ParseOptions po(usage); AlignConfig align_config; BaseFloat acoustic_scale = 1.0; BaseFloat transition_scale = 1.0; BaseFloat self_loop_scale = 1.0; std::string per_frame_acwt_wspecifier; align_config.Register(&po); po.Register("transition-scale", &transition_scale, "Transition-probability scale [relative to acoustics]"); po.Register("acoustic-scale", &acoustic_scale, "Scaling factor for acoustic likelihoods"); po.Register("self-loop-scale", &self_loop_scale, "Scale of self-loop versus non-self-loop log probs [relative to acoustics]"); po.Register("write-per-frame-acoustic-loglikes", &per_frame_acwt_wspecifier, "Wspecifier for table of vectors containing the acoustic log-likelihoods " "per frame for each utterance. E.g. ark:foo/per_frame_logprobs.1.ark"); po.Read(argc, argv); if (po.NumArgs() < 4 || po.NumArgs() > 5) { po.PrintUsage(); exit(1); } std::string model_in_filename = po.GetArg(1), fst_rspecifier = po.GetArg(2), feature_rspecifier = po.GetArg(3), alignment_wspecifier = po.GetArg(4), scores_wspecifier = po.GetOptArg(5); 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); } SequentialTableReader fst_reader(fst_rspecifier); RandomAccessBaseFloatMatrixReader feature_reader(feature_rspecifier); Int32VectorWriter alignment_writer(alignment_wspecifier); BaseFloatWriter scores_writer(scores_wspecifier); BaseFloatVectorWriter per_frame_acwt_writer(per_frame_acwt_wspecifier); int num_done = 0, num_err = 0, num_retry = 0; double tot_like = 0.0; kaldi::int64 frame_count = 0; for (; !fst_reader.Done(); fst_reader.Next()) { std::string utt = fst_reader.Key(); if (!feature_reader.HasKey(utt)) { num_err++; KALDI_WARN << "No features for utterance " << utt; } else { const Matrix &features = feature_reader.Value(utt); VectorFst decode_fst(fst_reader.Value()); fst_reader.FreeCurrent(); // this stops copy-on-write of the fst // by deleting the fst inside the reader, since we're about to mutate // the fst by adding transition probs. if (features.NumRows() == 0) { KALDI_WARN << "Zero-length utterance: " << utt; num_err++; continue; } { // Add transition-probs to the FST. std::vector disambig_syms; // empty. AddTransitionProbs(trans_model, disambig_syms, transition_scale, self_loop_scale, &decode_fst); } DecodableAmDiagGmmScaled gmm_decodable(am_gmm, trans_model, features, acoustic_scale); KALDI_LOG << utt; AlignUtteranceWrapper(align_config, utt, acoustic_scale, &decode_fst, &gmm_decodable, &alignment_writer, &scores_writer, &num_done, &num_err, &num_retry, &tot_like, &frame_count, &per_frame_acwt_writer); } } 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; } }