online2-wav-dump-features.cc
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// online2bin/online2-wav-dump-features.cc
// Copyright 2014 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 "feat/wave-reader.h"
#include "online2/online-nnet2-decoding.h"
#include "online2/online-nnet2-feature-pipeline.h"
#include "online2/onlinebin-util.h"
#include "online2/online-timing.h"
#include "online2/online-endpoint.h"
#include "fstext/fstext-lib.h"
#include "lat/lattice-functions.h"
int main(int argc, char *argv[]) {
try {
using namespace kaldi;
using namespace fst;
typedef kaldi::int32 int32;
typedef kaldi::int64 int64;
const char *usage =
"Reads in wav file(s) and processes them as in online2-wav-nnet2-latgen-faster,\n"
"but instead of decoding, dumps the features. Most of the parameters\n"
"are set via configuration variables.\n"
"\n"
"Usage: online2-wav-dump-features [options] <spk2utt-rspecifier> <wav-rspecifier> <feature-wspecifier>\n"
"The spk2utt-rspecifier can just be <utterance-id> <utterance-id> if\n"
"you want to generate features utterance by utterance.\n"
"Alternate usage: online2-wav-dump-features [options] --print-ivector-dim=true\n"
"See steps/online/nnet2/{dump_nnet_activations,get_egs.sh} for examples.\n";
ParseOptions po(usage);
// feature_config includes configuration for the iVector adaptation,
// as well as the basic features.
OnlineNnet2FeaturePipelineConfig feature_config;
BaseFloat chunk_length_secs = 0.05;
bool print_ivector_dim = false;
po.Register("chunk-length", &chunk_length_secs,
"Length of chunk size in seconds, that we process.");
po.Register("print-ivector-dim", &print_ivector_dim,
"If true, print iVector dimension (possibly zero) and exit. This "
"version requires no arguments.");
feature_config.Register(&po);
po.Read(argc, argv);
if (!print_ivector_dim && po.NumArgs() != 3) {
po.PrintUsage();
return 1;
}
OnlineNnet2FeaturePipelineInfo feature_info(feature_config);
if (print_ivector_dim) {
std::cout << feature_info.IvectorDim() << std::endl;
exit(0);
}
std::string spk2utt_rspecifier = po.GetArg(1),
wav_rspecifier = po.GetArg(2),
feats_wspecifier = po.GetArg(3);
int32 num_done = 0, num_err = 0;
int64 num_frames_tot = 0;
SequentialTokenVectorReader spk2utt_reader(spk2utt_rspecifier);
RandomAccessTableReader<WaveHolder> wav_reader(wav_rspecifier);
BaseFloatMatrixWriter feats_writer(feats_wspecifier);
for (; !spk2utt_reader.Done(); spk2utt_reader.Next()) {
std::string spk = spk2utt_reader.Key();
const std::vector<std::string> &uttlist = spk2utt_reader.Value();
OnlineIvectorExtractorAdaptationState adaptation_state(
feature_info.ivector_extractor_info);
for (size_t i = 0; i < uttlist.size(); i++) {
std::string utt = uttlist[i];
if (!wav_reader.HasKey(utt)) {
KALDI_WARN << "Did not find audio for utterance " << utt;
num_err++;
continue;
}
const WaveData &wave_data = wav_reader.Value(utt);
// get the data for channel zero (if the signal is not mono, we only
// take the first channel).
SubVector<BaseFloat> data(wave_data.Data(), 0);
OnlineNnet2FeaturePipeline feature_pipeline(feature_info);
feature_pipeline.SetAdaptationState(adaptation_state);
std::vector<Vector<BaseFloat> *> feature_data;
// We retrieve data from the feature pipeline while adding the wav data bit
// by bit... for features like pitch features, this may make a
// difference to what we get, and we want to make sure that the data we
// get it exactly compatible with online decoding.
BaseFloat samp_freq = wave_data.SampFreq();
int32 chunk_length = int32(samp_freq * chunk_length_secs);
if (chunk_length == 0) chunk_length = 1;
int32 samp_offset = 0;
while (samp_offset < data.Dim()) {
int32 samp_remaining = data.Dim() - samp_offset;
int32 num_samp = chunk_length < samp_remaining ? chunk_length
: samp_remaining;
SubVector<BaseFloat> wave_part(data, samp_offset, num_samp);
feature_pipeline.AcceptWaveform(samp_freq, wave_part);
samp_offset += num_samp;
if (samp_offset == data.Dim()) // no more input. flush out last frames
feature_pipeline.InputFinished();
while (static_cast<int32>(feature_data.size()) <
feature_pipeline.NumFramesReady()) {
int32 t = static_cast<int32>(feature_data.size());
feature_data.push_back(new Vector<BaseFloat>(feature_pipeline.Dim(),
kUndefined));
feature_pipeline.GetFrame(t, feature_data.back());
}
}
int32 T = static_cast<int32>(feature_data.size());
if (T == 0) {
KALDI_WARN << "Got no frames of data for utterance " << utt;
num_err++;
continue;
}
Matrix<BaseFloat> feats(T, feature_pipeline.Dim());
for (int32 t = 0; t < T; t++) {
feats.Row(t).CopyFromVec(*(feature_data[t]));
delete feature_data[t];
}
num_frames_tot += T;
feats_writer.Write(utt, feats);
feature_pipeline.GetAdaptationState(&adaptation_state);
num_done++;
}
}
KALDI_LOG << "Processed " << num_done << " utterances, "
<< num_err << " with errors; " << num_frames_tot
<< " frames in total.";
return (num_done != 0 ? 0 : 1);
} catch(const std::exception& e) {
std::cerr << e.what();
return -1;
}
} // main()