Blame view
src/gmmbin/gmm-basis-fmllr-training.cc
2.77 KB
8dcb6dfcb
first commit
|
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 |
// gmmbin/gmm-basis-fmllr-training.cc
// Copyright 2012 Carnegie Mellon University (author: Yajie Miao)
// 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>
using std::string;
#include <vector>
using std::vector;
#include "base/kaldi-common.h"
#include "util/common-utils.h"
#include "gmm/am-diag-gmm.h"
#include "hmm/transition-model.h"
#include "transform/fmllr-diag-gmm.h"
#include "transform/basis-fmllr-diag-gmm.h"
int main(int argc, char *argv[]) {
try {
typedef kaldi::int32 int32;
using namespace kaldi;
const char *usage =
"Estimate fMLLR basis representation. Reads a set of gradient scatter
"
"accumulations. Outputs basis matrices.
"
"Usage: gmm-basis-fmllr-training [options] <model-in> <basis-wspecifier> "
"<accs-in1> <accs-in2> ...
";
bool binary_write = true;
ParseOptions po(usage);
po.Register("binary", &binary_write, "Write output in binary mode");
po.Read(argc, argv);
if (po.NumArgs() < 3) {
po.PrintUsage();
exit(1);
}
string
model_rxfilename = po.GetArg(1),
basis_wspecifier = po.GetArg(2);
TransitionModel trans_model;
AmDiagGmm am_gmm;
{
bool binary;
Input ki(model_rxfilename, &binary);
trans_model.Read(ki.Stream(), binary);
am_gmm.Read(ki.Stream(), binary);
}
BasisFmllrAccus basis_accs(am_gmm.Dim());
int num_accs = po.NumArgs() - 2;
for (int i = 3, max = po.NumArgs(); i <= max; ++i) {
std::string accs_in_filename = po.GetArg(i);
bool binary_read;
kaldi::Input ki(accs_in_filename, &binary_read);
basis_accs.Read(ki.Stream(), binary_read, true /* add read values*/);
}
// Estimate the basis matrices
BasisFmllrEstimate basis_est(am_gmm.Dim());
basis_est.EstimateFmllrBasis(am_gmm, basis_accs);
WriteKaldiObject(basis_est, basis_wspecifier, binary_write);
KALDI_LOG << "Summed " << num_accs << " gradient scatter stats";
KALDI_LOG << "Generate " << basis_est.BasisSize() << " bases, written to "
<< basis_wspecifier;
return 0;
} catch(const std::exception& e) {
std::cerr << e.what();
return -1;
}
}
|