gmm-align.cc
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// gmmbin/gmm-align.cc
// Copyright 2009-2012 Microsoft Corporation
// 2012-2014 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 "fstext/fstext-utils.h"
#include "decoder/decoder-wrappers.h"
#include "decoder/training-graph-compiler.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 [options] tree-in model-in lexicon-fst-in feature-rspecifier "
"transcriptions-rspecifier alignments-wspecifier\n"
"e.g.: \n"
" gmm-align tree 1.mdl lex.fst scp:train.scp "
"'ark:sym2int.pl -f 2- words.txt text|' ark:1.ali\n";
ParseOptions po(usage);
AlignConfig align_config;
BaseFloat acoustic_scale = 1.0;
std::string disambig_rxfilename;
TrainingGraphCompilerOptions gopts;
align_config.Register(&po);
po.Register("acoustic-scale", &acoustic_scale, "Scaling factor for acoustic likelihoods");
po.Register("read-disambig-syms", &disambig_rxfilename, "File containing "
"list of disambiguation symbols in phone symbol table");
gopts.Register(&po);
po.Read(argc, argv);
if (po.NumArgs() != 6) {
po.PrintUsage();
exit(1);
}
std::string tree_in_filename = po.GetArg(1);
std::string model_in_filename = po.GetArg(2);
std::string lex_in_filename = po.GetArg(3);
std::string feature_rspecifier = po.GetArg(4);
std::string transcript_rspecifier = po.GetArg(5);
std::string alignment_wspecifier = po.GetArg(6);
ContextDependency ctx_dep;
ReadKaldiObject(tree_in_filename, &ctx_dep);
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);
}
// ownership will be taken by gc.
VectorFst<StdArc> *lex_fst = fst::ReadFstKaldi(lex_in_filename);
std::vector<int32> disambig_syms;
if (disambig_rxfilename != "")
if (!ReadIntegerVectorSimple(disambig_rxfilename, &disambig_syms))
KALDI_ERR << "fstcomposecontext: Could not read disambiguation symbols from "
<< disambig_rxfilename;
TrainingGraphCompiler gc(trans_model, ctx_dep, lex_fst, disambig_syms,
gopts);
lex_fst = NULL; // we gave ownership to gc.
SequentialBaseFloatMatrixReader feature_reader(feature_rspecifier);
RandomAccessInt32VectorReader transcript_reader(transcript_rspecifier);
Int32VectorWriter alignment_writer(alignment_wspecifier);
int32 num_done = 0, num_err = 0, num_retry = 0;
double tot_like = 0.0;
kaldi::int64 frame_count = 0;
for (; !feature_reader.Done(); feature_reader.Next()) {
std::string utt = feature_reader.Key();
if (!transcript_reader.HasKey(utt)) {
KALDI_WARN << "No transcript found for utterance " << utt;
num_err++;
continue;
}
const Matrix<BaseFloat> &features = feature_reader.Value();
const std::vector<int32> &transcript = transcript_reader.Value(utt);
VectorFst<StdArc> decode_fst;
if (!gc.CompileGraphFromText(transcript, &decode_fst)) {
KALDI_WARN << "Problem creating decoding graph for utterance "
<< utt <<" [serious error]";
num_err++;
continue;
}
if (features.NumRows() == 0) {
KALDI_WARN << "Zero-length features for utterance: " << utt;
num_err++;
continue;
}
DecodableAmDiagGmmScaled gmm_decodable(am_gmm, trans_model, features,
acoustic_scale);
AlignUtteranceWrapper(align_config, utt,
acoustic_scale, &decode_fst, &gmm_decodable,
&alignment_writer, NULL,
&num_done, &num_err, &num_retry,
&tot_like, &frame_count);
}
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;
}
}