gmm-init-mono.cc
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// gmmbin/gmm-init-mono.cc
// Copyright 2009-2011 Microsoft Corporation
// 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/hmm-topology.h"
#include "hmm/transition-model.h"
#include "tree/context-dep.h"
namespace kaldi {
// This function reads a file like:
// 1 2 3
// 4 5
// 6 7 8
// where each line is a list of integer id's of phones (that should have their pdfs shared).
void ReadSharedPhonesList(std::string rxfilename, std::vector<std::vector<int32> > *list_out) {
list_out->clear();
Input input(rxfilename);
std::istream &is = input.Stream();
std::string line;
while (std::getline(is, line)) {
list_out->push_back(std::vector<int32>());
if (!SplitStringToIntegers(line, " \t\r", true, &(list_out->back())))
KALDI_ERR << "Bad line in shared phones list: " << line << " (reading "
<< PrintableRxfilename(rxfilename) << ")";
std::sort(list_out->rbegin()->begin(), list_out->rbegin()->end());
if (!IsSortedAndUniq(*(list_out->rbegin())))
KALDI_ERR << "Bad line in shared phones list (repeated phone): " << line
<< " (reading " << PrintableRxfilename(rxfilename) << ")";
}
}
} // end namespace kaldi
int main(int argc, char *argv[]) {
try {
using namespace kaldi;
using kaldi::int32;
const char *usage =
"Initialize monophone GMM.\n"
"Usage: gmm-init-mono <topology-in> <dim> <model-out> <tree-out> \n"
"e.g.: \n"
" gmm-init-mono topo 39 mono.mdl mono.tree\n";
bool binary = true;
std::string train_feats;
std::string shared_phones_rxfilename;
BaseFloat perturb_factor = 0.0;
ParseOptions po(usage);
po.Register("binary", &binary, "Write output in binary mode");
po.Register("train-feats", &train_feats,
"rspecifier for training features [used to set mean and variance]");
po.Register("shared-phones", &shared_phones_rxfilename,
"rxfilename containing, on each line, a list of phones whose pdfs should be shared.");
po.Register("perturb-factor", &perturb_factor,
"Perturb the means using this fraction of standard deviation.");
po.Read(argc, argv);
if (po.NumArgs() != 4) {
po.PrintUsage();
exit(1);
}
std::string topo_filename = po.GetArg(1);
int dim = atoi(po.GetArg(2).c_str());
KALDI_ASSERT(dim> 0 && dim < 10000);
std::string model_filename = po.GetArg(3);
std::string tree_filename = po.GetArg(4);
Vector<BaseFloat> glob_inv_var(dim);
glob_inv_var.Set(1.0);
Vector<BaseFloat> glob_mean(dim);
glob_mean.Set(1.0);
if (train_feats != "") {
double count = 0.0;
Vector<double> var_stats(dim);
Vector<double> mean_stats(dim);
SequentialDoubleMatrixReader feat_reader(train_feats);
for (; !feat_reader.Done(); feat_reader.Next()) {
const Matrix<double> &mat = feat_reader.Value();
for (int32 i = 0; i < mat.NumRows(); i++) {
count += 1.0;
var_stats.AddVec2(1.0, mat.Row(i));
mean_stats.AddVec(1.0, mat.Row(i));
}
}
if (count == 0) { KALDI_ERR << "no features were seen."; }
var_stats.Scale(1.0/count);
mean_stats.Scale(1.0/count);
var_stats.AddVec2(-1.0, mean_stats);
if (var_stats.Min() <= 0.0)
KALDI_ERR << "bad variance";
var_stats.InvertElements();
glob_inv_var.CopyFromVec(var_stats);
glob_mean.CopyFromVec(mean_stats);
}
HmmTopology topo;
bool binary_in;
Input ki(topo_filename, &binary_in);
topo.Read(ki.Stream(), binary_in);
const std::vector<int32> &phones = topo.GetPhones();
std::vector<int32> phone2num_pdf_classes (1+phones.back());
for (size_t i = 0; i < phones.size(); i++)
phone2num_pdf_classes[phones[i]] = topo.NumPdfClasses(phones[i]);
// Now the tree [not really a tree at this point]:
ContextDependency *ctx_dep = NULL;
if (shared_phones_rxfilename == "") { // No sharing of phones: standard approach.
ctx_dep = MonophoneContextDependency(phones, phone2num_pdf_classes);
} else {
std::vector<std::vector<int32> > shared_phones;
ReadSharedPhonesList(shared_phones_rxfilename, &shared_phones);
// ReadSharedPhonesList crashes on error.
ctx_dep = MonophoneContextDependencyShared(shared_phones, phone2num_pdf_classes);
}
int32 num_pdfs = ctx_dep->NumPdfs();
AmDiagGmm am_gmm;
DiagGmm gmm;
gmm.Resize(1, dim);
{ // Initialize the gmm.
Matrix<BaseFloat> inv_var(1, dim);
inv_var.Row(0).CopyFromVec(glob_inv_var);
Matrix<BaseFloat> mu(1, dim);
mu.Row(0).CopyFromVec(glob_mean);
Vector<BaseFloat> weights(1);
weights.Set(1.0);
gmm.SetInvVarsAndMeans(inv_var, mu);
gmm.SetWeights(weights);
gmm.ComputeGconsts();
}
for (int i = 0; i < num_pdfs; i++)
am_gmm.AddPdf(gmm);
if (perturb_factor != 0.0) {
for (int i = 0; i < num_pdfs; i++)
am_gmm.GetPdf(i).Perturb(perturb_factor);
}
// Now the transition model:
TransitionModel trans_model(*ctx_dep, topo);
{
Output ko(model_filename, binary);
trans_model.Write(ko.Stream(), binary);
am_gmm.Write(ko.Stream(), binary);
}
// Now write the tree.
ctx_dep->Write(Output(tree_filename, binary).Stream(),
binary);
delete ctx_dep;
return 0;
} catch(const std::exception &e) {
std::cerr << e.what();
return -1;
}
}