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src/ivectorbin/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 " "utterances of each speaker using the spk2utt file. " "Input the spk2utt file and a set of iVectors indexed by " "utterance; output is iVectors indexed by speaker. If 4 " "arguments are given, extra argument is a table for the number " "of utterances per speaker (can be useful for PLDA). If 2 " "arguments are given, computes the mean of all input files and " "writes out the mean vector. " " " "Usage: ivector-mean <spk2utt-rspecifier> <ivector-rspecifier> " "<ivector-wspecifier> [<num-utt-wspecifier>] " "or: ivector-mean <ivector-rspecifier> <mean-wxfilename> " "e.g.: ivector-mean data/spk2utt exp/ivectors.ark exp/spk_ivectors.ark exp/spk_num_utts.ark " "or: ivector-mean exp/ivectors.ark exp/mean.vec " "See also: ivector-subtract-global-mean "; 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; } } |