gmm-latgen-map.cc
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// 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 <string>
#include <vector>
#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"
"<gmms-rspecifier> will typically be piped in from gmm-est-map.\n"
"Note: <model-in> is only needed for the transition-model, which isn't\n"
"included in <gmms-rspecifier>.\n"
"\n"
"Usage: gmm-latgen-map [options] <model-in> "
"<gmms-rspecifier> <fsts-rxfilename|fsts-rspecifier> <features-rspecifier> "
"<lattice-wspecifier> [ <words-wspecifier> [ <alignments-wspecifier> ] ]\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<StdArc> *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<BaseFloat> 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::VectorFstHolder> 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<BaseFloat> 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;
}
}