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src/gmmbin/gmm-transform-means.cc
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// gmmbin/gmm-transform-means.cc
// Copyright 2009-2011 Microsoft Corporation
// 2012 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 "tree/context-dep.h"
#include "hmm/transition-model.h"
#include "transform/mllt.h"
int main(int argc, char *argv[]) {
try {
using namespace kaldi;
typedef kaldi::int32 int32;
const char *usage =
"Transform GMM means with linear or affine transform
"
"Usage: gmm-transform-means <transform-matrix> <model-in> <model-out>
"
"e.g.: gmm-transform-means 2.mat 2.mdl 3.mdl
";
bool binary = true; // write in binary if true.
ParseOptions po(usage);
po.Register("binary", &binary, "Write output in binary mode");
po.Read(argc, argv);
if (po.NumArgs() != 3) {
po.PrintUsage();
exit(1);
}
std::string mat_rxfilename = po.GetArg(1),
model_in_rxfilename = po.GetArg(2),
model_out_wxfilename = po.GetArg(3);
Matrix<BaseFloat> mat;
ReadKaldiObject(mat_rxfilename, &mat);
AmDiagGmm am_gmm;
TransitionModel trans_model;
{
bool binary_read;
Input ki(model_in_rxfilename, &binary_read);
trans_model.Read(ki.Stream(), binary_read);
am_gmm.Read(ki.Stream(), binary_read);
}
int32 dim = am_gmm.Dim();
if (mat.NumRows() != dim)
KALDI_ERR << "Transform matrix has " << mat.NumRows() << " rows but "
"model has dimension " << am_gmm.Dim();
if (mat.NumCols() != dim
&& mat.NumCols() != dim+1)
KALDI_ERR << "Transform matrix has " << mat.NumCols() << " columns but "
"model has dimension " << am_gmm.Dim() << " (neither a linear nor an "
"affine transform";
for (int32 i = 0; i < am_gmm.NumPdfs(); i++) {
DiagGmm &gmm = am_gmm.GetPdf(i);
Matrix<BaseFloat> means;
gmm.GetMeans(&means);
Matrix<BaseFloat> new_means(means.NumRows(), means.NumCols());
if (mat.NumCols() == dim) { // linear case
// Right-multiply means by mat^T (equivalent to left-multiplying each
// row by mat).
new_means.AddMatMat(1.0, means, kNoTrans, mat, kTrans, 0.0);
} else { // affine case
Matrix<BaseFloat> means_ext(means.NumRows(), means.NumCols()+1);
means_ext.Set(1.0); // set all elems to 1.0
SubMatrix<BaseFloat> means_part(means_ext, 0, means.NumRows(),
0, means.NumCols());
means_part.CopyFromMat(means); // copy old part...
new_means.AddMatMat(1.0, means_ext, kNoTrans, mat, kTrans, 0.0);
}
gmm.SetMeans(new_means);
gmm.ComputeGconsts();
}
{
Output ko(model_out_wxfilename, binary);
trans_model.Write(ko.Stream(), binary);
am_gmm.Write(ko.Stream(), binary);
}
KALDI_LOG << "Written model to " << model_out_wxfilename;
return 0;
} catch(const std::exception &e) {
std::cerr << e.what() << '
';
return -1;
}
}
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