ivector-mean.cc
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// ivectorbin/ivector-mean.cc
// Copyright 2013-2014 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"
int main(int argc, char *argv[]) {
using namespace kaldi;
typedef kaldi::int32 int32;
try {
const char *usage =
"With 3 or 4 arguments, averages iVectors over all the\n"
"utterances of each speaker using the spk2utt file.\n"
"Input the spk2utt file and a set of iVectors indexed by\n"
"utterance; output is iVectors indexed by speaker. If 4\n"
"arguments are given, extra argument is a table for the number\n"
"of utterances per speaker (can be useful for PLDA). If 2\n"
"arguments are given, computes the mean of all input files and\n"
"writes out the mean vector.\n"
"\n"
"Usage: ivector-mean <spk2utt-rspecifier> <ivector-rspecifier> "
"<ivector-wspecifier> [<num-utt-wspecifier>]\n"
"or: ivector-mean <ivector-rspecifier> <mean-wxfilename>\n"
"e.g.: ivector-mean data/spk2utt exp/ivectors.ark exp/spk_ivectors.ark exp/spk_num_utts.ark\n"
"or: ivector-mean exp/ivectors.ark exp/mean.vec\n"
"See also: ivector-subtract-global-mean\n";
ParseOptions po(usage);
bool binary_write = false;
po.Register("binary", &binary_write, "If true, write output in binary "
"(only applicable when writing files, not archives/tables.");
po.Read(argc, argv);
if (po.NumArgs() < 2 || po.NumArgs() > 4) {
po.PrintUsage();
exit(1);
}
if (po.NumArgs() == 2) {
// Compute the mean of the input vectors and write it out.
std::string ivector_rspecifier = po.GetArg(1),
mean_wxfilename = po.GetArg(2);
int32 num_done = 0;
SequentialBaseFloatVectorReader ivector_reader(ivector_rspecifier);
Vector<double> sum;
for (; !ivector_reader.Done(); ivector_reader.Next()) {
if (sum.Dim() == 0) sum.Resize(ivector_reader.Value().Dim());
sum.AddVec(1.0, ivector_reader.Value());
num_done++;
}
if (num_done == 0) {
KALDI_ERR << "No iVectors read";
} else {
sum.Scale(1.0 / num_done);
WriteKaldiObject(sum, mean_wxfilename, binary_write);
return 0;
}
} else {
std::string spk2utt_rspecifier = po.GetArg(1),
ivector_rspecifier = po.GetArg(2),
ivector_wspecifier = po.GetArg(3),
num_utts_wspecifier = po.GetOptArg(4);
double spk_sumsq = 0.0;
Vector<double> spk_sum;
int64 num_spk_done = 0, num_spk_err = 0,
num_utt_done = 0, num_utt_err = 0;
RandomAccessBaseFloatVectorReader ivector_reader(ivector_rspecifier);
SequentialTokenVectorReader spk2utt_reader(spk2utt_rspecifier);
BaseFloatVectorWriter ivector_writer(ivector_wspecifier);
Int32Writer num_utts_writer(num_utts_wspecifier);
for (; !spk2utt_reader.Done(); spk2utt_reader.Next()) {
std::string spk = spk2utt_reader.Key();
const std::vector<std::string> &uttlist = spk2utt_reader.Value();
if (uttlist.empty()) {
KALDI_ERR << "Speaker with no utterances.";
}
Vector<BaseFloat> spk_mean;
int32 utt_count = 0;
for (size_t i = 0; i < uttlist.size(); i++) {
std::string utt = uttlist[i];
if (!ivector_reader.HasKey(utt)) {
KALDI_WARN << "No iVector present in input for utterance " << utt;
num_utt_err++;
} else {
if (utt_count == 0) {
spk_mean = ivector_reader.Value(utt);
} else {
spk_mean.AddVec(1.0, ivector_reader.Value(utt));
}
num_utt_done++;
utt_count++;
}
}
if (utt_count == 0) {
KALDI_WARN << "Not producing output for speaker " << spk
<< " since no utterances had iVectors";
num_spk_err++;
} else {
spk_mean.Scale(1.0 / utt_count);
ivector_writer.Write(spk, spk_mean);
if (num_utts_wspecifier != "")
num_utts_writer.Write(spk, utt_count);
num_spk_done++;
spk_sumsq += VecVec(spk_mean, spk_mean);
if (spk_sum.Dim() == 0)
spk_sum.Resize(spk_mean.Dim());
spk_sum.AddVec(1.0, spk_mean);
}
}
KALDI_LOG << "Computed mean of " << num_spk_done << " speakers ("
<< num_spk_err << " with no utterances), consisting of "
<< num_utt_done << " utterances (" << num_utt_err
<< " absent from input).";
if (num_spk_done != 0) {
spk_sumsq /= num_spk_done;
spk_sum.Scale(1.0 / num_spk_done);
double mean_length = spk_sum.Norm(2.0),
spk_length = sqrt(spk_sumsq),
norm_spk_length = spk_length / sqrt(spk_sum.Dim());
KALDI_LOG << "Norm of mean of speakers is " << mean_length
<< ", root-mean-square speaker-iVector length divided by "
<< "sqrt(dim) is " << norm_spk_length;
}
return (num_spk_done != 0 ? 0 : 1);
}
} catch(const std::exception &e) {
std::cerr << e.what();
return -1;
}
}