apply-cmvn-sliding.cc
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// featbin/apply-cmvn-sliding.cc
// Copyright 2013 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 "matrix/kaldi-matrix.h"
#include "feat/feature-functions.h"
int main(int argc, char *argv[]) {
try {
using namespace kaldi;
using kaldi::int32;
const char *usage =
"Apply sliding-window cepstral mean (and optionally variance)\n"
"normalization per utterance. If center == true, window is centered\n"
"on frame being normalized; otherwise it precedes it in time.\n"
"Useful for speaker-id; see also apply-cmvn-online\n"
"\n"
"Usage: apply-cmvn-sliding [options] <feats-rspecifier> <feats-wspecifier>\n";
ParseOptions po(usage);
SlidingWindowCmnOptions opts;
opts.Register(&po);
po.Read(argc, argv);
if (po.NumArgs() != 2) {
po.PrintUsage();
exit(1);
}
int32 num_done = 0, num_err = 0;
std::string feat_rspecifier = po.GetArg(1);
std::string feat_wspecifier = po.GetArg(2);
SequentialBaseFloatMatrixReader feat_reader(feat_rspecifier);
BaseFloatMatrixWriter feat_writer(feat_wspecifier);
for (;!feat_reader.Done(); feat_reader.Next()) {
std::string utt = feat_reader.Key();
Matrix<BaseFloat> feat(feat_reader.Value());
if (feat.NumRows() == 0) {
KALDI_WARN << "Empty feature matrix for utterance " << utt;
num_err++;
continue;
}
Matrix<BaseFloat> cmvn_feat(feat.NumRows(),
feat.NumCols(), kUndefined);
SlidingWindowCmn(opts, feat, &cmvn_feat);
feat_writer.Write(utt, cmvn_feat);
num_done++;
}
KALDI_LOG << "Applied sliding-window cepstral mean "
<< (opts.normalize_variance ? "and variance " : "")
<< "normalization to " << num_done << " utterances, "
<< num_err << " had errors.";
return (num_done != 0 ? 0 : 1);
} catch(const std::exception &e) {
std::cerr << e.what();
return -1;
}
}