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// gmmbin/gmm-boost-silence.cc
// Copyright 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 "hmm/transition-model.h"
#include "gmm/am-diag-gmm.h"
int main(int argc, char *argv[]) {
try {
using namespace kaldi;
typedef kaldi::int32 int32;
const char *usage =
"Modify GMM-based model to boost (by a certain factor) all
"
"probabilities associated with the specified phones (could be
"
"all silence phones, or just the ones used for optional silence).
"
"Note: this is done by modifying the GMM weights. If the silence
"
"model shares a GMM with other models, then it will modify the GMM
"
"weights for all models that may correspond to silence.
"
"
"
"Usage: gmm-boost-silence [options] <silence-phones-list> <model-in> <model-out>
"
"e.g.: gmm-boost-silence --boost=1.5 1:2:3 1.mdl 1_boostsil.mdl
";
bool binary_write = true;
BaseFloat boost = 1.5;
ParseOptions po(usage);
po.Register("binary", &binary_write, "Write output in binary mode");
po.Register("boost", &boost, "Factor by which to boost silence probs");
po.Read(argc, argv);
if (po.NumArgs() != 3) {
po.PrintUsage();
exit(1);
}
std::string
silence_phones_string = po.GetArg(1),
model_rxfilename = po.GetArg(2),
model_wxfilename = po.GetArg(3);
std::vector<int32> silence_phones;
if (silence_phones_string != "") {
SplitStringToIntegers(silence_phones_string, ":", false, &silence_phones);
std::sort(silence_phones.begin(), silence_phones.end());
KALDI_ASSERT(IsSortedAndUniq(silence_phones) && "Silence phones non-unique.");
} else {
KALDI_WARN << "gmm-boost-silence: no silence phones specified, doing nothing.";
}
AmDiagGmm am_gmm;
TransitionModel trans_model;
{
bool binary_read;
Input ki(model_rxfilename, &binary_read);
trans_model.Read(ki.Stream(), binary_read);
am_gmm.Read(ki.Stream(), binary_read);
}
{ // Do the modification to the am_gmm object.
std::vector<int32> pdfs;
bool ans = GetPdfsForPhones(trans_model, silence_phones, &pdfs);
if (!ans) {
KALDI_WARN << "The pdfs for the silence phones may be shared by other phones "
<< "(note: this probably does not matter.)";
}
for (size_t i = 0; i < pdfs.size(); i++) {
int32 pdf = pdfs[i];
DiagGmm &gmm = am_gmm.GetPdf(pdf);
Vector<BaseFloat> weights(gmm.weights());
weights.Scale(boost);
gmm.SetWeights(weights);
gmm.ComputeGconsts();
}
KALDI_LOG << "Boosted weights for " << pdfs.size()
<< " pdfs, by factor of " << boost;
}
{
Output ko(model_wxfilename, binary_write);
trans_model.Write(ko.Stream(), binary_write);
am_gmm.Write(ko.Stream(), binary_write);
}
KALDI_LOG << "Wrote model to " << model_wxfilename;
} catch(const std::exception &e) {
std::cerr << e.what() << '
';
return -1;
}
}
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