// Copyright (c) 2022 PaddlePaddle Authors. All Rights Reserved.
//
// 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
//
// Unless required by applicable law or agreed to in writing, software
// distributed under the License is distributed on an "AS IS" BASIS,
// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
// See the License for the specific language governing permissions and
// limitations under the License.
// todo refactor, repalce with gtest
#include "base/flags.h"
#include "base/log.h"
#include "frontend/audio_cache.h"
#include "frontend/data_cache.h"
#include "frontend/fbank.h"
#include "frontend/feature_cache.h"
#include "frontend/frontend_itf.h"
#include "frontend/normalizer.h"
#include "frontend/wave-reader.h"
#include "kaldi/util/kaldi-io.h"
#include "kaldi/util/table-types.h"
DEFINE_string(wav_rspecifier, "", "test wav scp path");
DEFINE_string(feature_wspecifier, "", "output feats wspecifier");
DEFINE_string(cmvn_file, "", "read cmvn");
DEFINE_double(streaming_chunk, 0.36, "streaming feature chunk size");
DEFINE_int32(num_bins, 161, "fbank num bins");
DEFINE_int32(sample_rate, 16000, "sampe rate: 16k, 8k.");
int main(int argc, char* argv[]) {
gflags::SetUsageMessage("Usage:");
gflags::ParseCommandLineFlags(&argc, &argv, false);
google::InitGoogleLogging(argv[0]);
google::InstallFailureSignalHandler();
FLAGS_logtostderr = 1;
CHECK_GT(FLAGS_wav_rspecifier.size(), 0);
CHECK_GT(FLAGS_feature_wspecifier.size(), 0);
kaldi::SequentialTableReader<kaldi::WaveHolder> wav_reader(
FLAGS_wav_rspecifier);
kaldi::SequentialTableReader<kaldi::WaveInfoHolder> wav_info_reader(
FLAGS_wav_rspecifier);
kaldi::BaseFloatMatrixWriter feat_writer(FLAGS_feature_wspecifier);
int32 num_done = 0, num_err = 0;
// feature pipeline: wave cache --> povey window
// -->fbank --> global cmvn -> feat cache
std::unique_ptr<ppspeech::FrontendInterface> data_source(
new ppspeech::AudioCache(3600 * 1600, false));
knf::FbankOptions opt;
opt.frame_opts.frame_length_ms = 25;
opt.frame_opts.frame_shift_ms = 10;
opt.mel_opts.num_bins = FLAGS_num_bins;
opt.frame_opts.dither = 0.0;
LOG(INFO) << "frame_length_ms: " << opt.frame_opts.frame_length_ms;
LOG(INFO) << "frame_shift_ms: " << opt.frame_opts.frame_shift_ms;
LOG(INFO) << "num_bins: " << opt.mel_opts.num_bins;
LOG(INFO) << "dither: " << opt.frame_opts.dither;
std::unique_ptr<ppspeech::FrontendInterface> fbank(
new ppspeech::Fbank(opt, std::move(data_source)));
std::unique_ptr<ppspeech::FrontendInterface> cmvn(
new ppspeech::CMVN(FLAGS_cmvn_file, std::move(fbank)));
// the feature cache output feature chunk by chunk.
ppspeech::FeatureCache feature_cache(kint16max, std::move(cmvn));
LOG(INFO) << "fbank: " << true;
LOG(INFO) << "feat dim: " << feature_cache.Dim();
float streaming_chunk = FLAGS_streaming_chunk;
int chunk_sample_size = streaming_chunk * FLAGS_sample_rate;
LOG(INFO) << "sr: " << FLAGS_sample_rate;
LOG(INFO) << "chunk size (sec): " << streaming_chunk;
LOG(INFO) << "chunk size (sample): " << chunk_sample_size;
for (; !wav_reader.Done() && !wav_info_reader.Done();
wav_reader.Next(), wav_info_reader.Next()) {
const std::string& utt = wav_reader.Key();
const kaldi::WaveData& wave_data = wav_reader.Value();
const std::string& utt2 = wav_info_reader.Key();
const kaldi::WaveInfo& wave_info = wav_info_reader.Value();
CHECK(utt == utt2)
<< "wav reader and wav info reader using diff rspecifier!!!";
LOG(INFO) << "utt: " << utt;
LOG(INFO) << "samples: " << wave_info.SampleCount();
LOG(INFO) << "dur: " << wave_info.Duration() << " sec";
CHECK(wave_info.SampFreq() == FLAGS_sample_rate)
<< "need " << FLAGS_sample_rate << " get " << wave_info.SampFreq();
// load first channel wav
int32 this_channel = 0;
kaldi::SubVector<kaldi::BaseFloat> waveform(wave_data.Data(),
this_channel);
// compute feat chunk by chunk
int tot_samples = waveform.Dim();
int sample_offset = 0;
std::vector<kaldi::Vector<BaseFloat>> feats;
int feature_rows = 0;
while (sample_offset < tot_samples) {
// cur chunk size
int cur_chunk_size =
std::min(chunk_sample_size, tot_samples - sample_offset);
// get chunk wav
std::vector<kaldi::BaseFloat> wav_chunk(cur_chunk_size);
for (int i = 0; i < cur_chunk_size; ++i) {
wav_chunk[i] = waveform(sample_offset + i);
}
// compute feat
feature_cache.Accept(wav_chunk);
// send finish signal
if (cur_chunk_size < chunk_sample_size) {
feature_cache.SetFinished();
}
// read feat
kaldi::Vector<BaseFloat> features(feature_cache.Dim());
bool flag = true;
do {
std::vector<BaseFloat> tmp;
flag = feature_cache.Read(&tmp);
std::memcpy(features.Data(),
tmp.data(),
tmp.size() * sizeof(BaseFloat));
if (flag && features.Dim() != 0) {
feats.push_back(features);
feature_rows += features.Dim() / feature_cache.Dim();
}
} while (flag == true && features.Dim() != 0);
// forward offset
sample_offset += cur_chunk_size;
}
int cur_idx = 0;
kaldi::Matrix<kaldi::BaseFloat> features(feature_rows,
feature_cache.Dim());
for (auto feat : feats) {
int num_rows = feat.Dim() / feature_cache.Dim();
for (int row_idx = 0; row_idx < num_rows; ++row_idx) {
for (size_t col_idx = 0; col_idx < feature_cache.Dim();
++col_idx) {
features(cur_idx, col_idx) =
feat(row_idx * feature_cache.Dim() + col_idx);
}
++cur_idx;
}
}
LOG(INFO) << "feat shape: " << features.NumRows() << " , "
<< features.NumCols();
feat_writer.Write(utt, features);
// reset frontend pipeline state
feature_cache.Reset();
if (num_done % 50 == 0 && num_done != 0)
VLOG(2) << "Processed " << num_done << " utterances";
num_done++;
}
LOG(INFO) << "Done " << num_done << " utterances, " << num_err
<< " with errors.";
return (num_done != 0 ? 0 : 1);
}