// ivectorbin/merge-vads.cc // Copyright 2015 David Snyder // 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 "util/stl-utils.h" namespace kaldi { /** PrepareMap creates a mapping between the pairs of VAD decisions and the output label. If map_rxfilename is empty, we create a mapping in which a frame is only classified as speech (represented as "1") if both VAD decisions agree on speech, and nonspeech (represented as "0") otherwise. If map_rxfilename is not empty, then that table provides the mapping. If the first set of VAD decisions has N classes and the second has M classes, then the table needs to have NxM rows, and three columns. The first two columns correspond to the labels in the first and second VAD decisions respectively, and the last column is the resultant output label. For example: 0 0 0 0 1 0 0 2 0 1 0 0 1 1 1 1 2 1 */ void PrepareMap(const std::string map_rxfilename, unordered_map, int32, PairHasher > *map) { Input map_input(map_rxfilename); // If a map file isn't specified, provide an obvious mapping. The // following mapping assumes "0" corresponds to nonspeech and "1" // corresponds to speech. The combination of two VAD decisions only // results in a decision of speech if both input frames are // classified as speech. if (map_rxfilename.empty()) { (*map)[std::pair(0, 0)] = 0; (*map)[std::pair(0, 1)] = 0; (*map)[std::pair(1, 0)] = 0; (*map)[std::pair(1, 1)] = 1; } else { std::string line; while (std::getline(map_input.Stream(), line)) { if (line.size() == 0) continue; int32 start = line.find_first_not_of(" \t"); int32 end = line.find_first_of('#'); if (start == std::string::npos || start == end) continue; end = line.find_last_not_of(" \t", end - 1); KALDI_ASSERT(end >= start); std::vector fields; SplitStringToVector(line.substr(start, end - start + 1), " \t\n\r", true, &fields); if (fields.size() != 3) { KALDI_ERR << "Bad line. Expected three fields, got: " << line; } int32 label1 = std::atoi(fields[0].c_str()), label2 = std::atoi(fields[1].c_str()), result_label = std::atoi(fields[2].c_str()); (*map)[std::pair(label1, label2)] = result_label; } } } } int main(int argc, char *argv[]) { using namespace kaldi; typedef kaldi::int32 int32; try { const char *usage = "This program merges two archives of per-frame weights representing\n" "voice activity decisions. By default, the program assumes that the\n" "input vectors consist of floats that are 0.0 if a frame is judged\n" "as nonspeech and 1.0 if it is considered speech. The default\n" "behavior produces a frame-level decision of 1.0 if both input frames\n" "are 1.0, and 0.0 otherwise. Additional classes (e.g., 2.0 for music)\n" "can be handled using the \"map\" option.\n" "\n" "Usage: merge-vads [options] \n" " \n" "e.g.: merge-vads [options] scp:vad_energy.scp scp:vad_gmm.scp\n" " ark:vad.ark\n" "See also: compute-vad-from-frame-likes, compute-vad, ali-to-post,\n" "post-to-weights\n"; ParseOptions po(usage); std::string map_rxfilename; po.Register("map", &map_rxfilename, "This table specifies a mapping " "between the labels of the frame-level decisions in the first and " "second input archives to the integer output label."); po.Read(argc, argv); if (po.NumArgs() != 3) { po.PrintUsage(); exit(1); } unordered_map, int32, PairHasher > map; PrepareMap(map_rxfilename, &map); SequentialBaseFloatVectorReader first_vad_reader(po.GetArg(1)); RandomAccessBaseFloatVectorReader second_vad_reader(po.GetArg(2)); BaseFloatVectorWriter vad_writer(po.GetArg(3)); int32 num_done = 0, num_err = 0; for (;!first_vad_reader.Done(); first_vad_reader.Next()) { std::string utt = first_vad_reader.Key(); Vector vad1(first_vad_reader.Value()); if (!second_vad_reader.HasKey(utt)) { KALDI_WARN << "No vector for utterance " << utt; num_err++; continue; } Vector vad2(second_vad_reader.Value(utt)); if (vad1.Dim() != vad2.Dim()) { KALDI_WARN << "VAD length mismatch for utterance " << utt; num_err++; continue; } Vector vad_result(vad1.Dim()); for (int32 i = 0; i < vad1.Dim(); i++) { std::pair key(static_cast(vad1(i)), static_cast(vad2(i))); unordered_map, int32, PairHasher >::const_iterator iter = map.find(key); if (iter == map.end()) { KALDI_ERR << "Map is missing combination " << vad1(i) << " and " << vad2(i); } else { vad_result(i) = iter->second; } } vad_writer.Write(utt, vad_result); num_done++; } KALDI_LOG << "Merged voice activity detection decisions; " << "processed " << num_done << " utterances successfully; " << num_err << " had errors."; return (num_done != 0 ? 0 : 1); } catch(const std::exception &e) { std::cerr << e.what(); return -1; } }