// bin/align-equal-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 "tree/context-dep.h" #include "hmm/transition-model.h" #include "fstext/fstext-lib.h" #include "decoder/training-graph-compiler.h" /** @brief Write an equally spaced alignment (for getting training started). */ 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 = "Write an equally spaced alignment (for getting training started)" "Usage: align-equal-compiled \n" "e.g.: \n" " align-equal-compiled 1.fsts scp:train.scp ark:equal.ali\n"; ParseOptions po(usage); bool binary = true; po.Register("binary", &binary, "Write output in binary mode"); po.Read(argc, argv); if (po.NumArgs() != 3) { po.PrintUsage(); exit(1); } std::string fst_rspecifier = po.GetArg(1), feature_rspecifier = po.GetArg(2), alignment_wspecifier = po.GetArg(3); SequentialTableReader fst_reader(fst_rspecifier); RandomAccessBaseFloatMatrixReader feature_reader(feature_rspecifier); Int32VectorWriter alignment_writer(alignment_wspecifier); int32 done = 0, no_feat = 0, error = 0; for (; !fst_reader.Done(); fst_reader.Next()) { std::string key = fst_reader.Key(); if (!feature_reader.HasKey(key)) { KALDI_WARN << "No features for utterance " << key; no_feat++; } else { const Matrix &features = feature_reader.Value(key); 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: " << key; error++; continue; } if (decode_fst.Start() == fst::kNoStateId) { KALDI_WARN << "Empty decoding graph for " << key; error++; continue; } VectorFst path; int32 rand_seed = StringHasher()(key); // StringHasher() produces new anonymous // object of type StringHasher; we then call operator () on it, with "key". if (EqualAlign(decode_fst, features.NumRows(), rand_seed, &path) ) { std::vector aligned_seq, words; StdArc::Weight w; GetLinearSymbolSequence(path, &aligned_seq, &words, &w); KALDI_ASSERT(aligned_seq.size() == features.NumRows()); alignment_writer.Write(key, aligned_seq); done++; } else { KALDI_WARN << "AlignEqual: did not align utterence " << key; error++; } } } if (done != 0 && no_feat == 0 && error == 0) { KALDI_LOG << "Success: done " << done << " utterances."; } else { KALDI_WARN << "Computed " << done << " alignments; " << no_feat << " lacked features, " << error << " had other errors."; } if (done != 0) return 0; else return 1; } catch(const std::exception &e) { std::cerr << e.what(); return -1; } }