Yang Zhou
2 years ago
parent
33ca17359f
commit
d568c8730a
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// Copyright (c) 2022 PaddlePaddle Authors. All Rights Reserved.
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//
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// Licensed under the Apache License, Version 2.0 (the "License");
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// you may not use this file except in compliance with the License.
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// You may obtain a copy of the License at
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//
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// http://www.apache.org/licenses/LICENSE-2.0
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//
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// Unless required by applicable law or agreed to in writing, software
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// distributed under the License is distributed on an "AS IS" BASIS,
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// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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// See the License for the specific language governing permissions and
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// limitations under the License.
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// todo refactor, repalce with gtest
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#include "base/flags.h"
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#include "base/log.h"
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#include "kaldi/feat/wave-reader.h"
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#include "kaldi/util/kaldi-io.h"
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#include "kaldi/util/table-types.h"
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#include "frontend/audio/audio_cache.h"
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#include "frontend/audio/data_cache.h"
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#include "frontend/audio/fbank.h"
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#include "frontend/audio/feature_cache.h"
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#include "frontend/audio/frontend_itf.h"
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#include "frontend/audio/normalizer.h"
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DEFINE_string(wav_rspecifier, "", "test wav scp path");
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DEFINE_string(feature_wspecifier, "", "output feats wspecifier");
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DEFINE_string(cmvn_file, "", "read cmvn");
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DEFINE_double(streaming_chunk, 0.36, "streaming feature chunk size");
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DEFINE_int32(num_bins, 161, "fbank num bins");
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int main(int argc, char* argv[]) {
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gflags::ParseCommandLineFlags(&argc, &argv, false);
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google::InitGoogleLogging(argv[0]);
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kaldi::SequentialTableReader<kaldi::WaveHolder> wav_reader(
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FLAGS_wav_rspecifier);
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kaldi::BaseFloatMatrixWriter feat_writer(FLAGS_feature_wspecifier);
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int32 num_done = 0, num_err = 0;
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// feature pipeline: wave cache --> hanning window
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// -->fbank --> global cmvn -> feat cache
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std::unique_ptr<ppspeech::FrontendInterface> data_source(
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new ppspeech::AudioCache(3600 * 1600, false));
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ppspeech::FbankOptions opt;
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opt.fbank_opts.frame_opts.frame_length_ms = 25;
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opt.fbank_opts.frame_opts.frame_shift_ms = 10;
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opt.streaming_chunk = FLAGS_streaming_chunk;
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opt.fbank_opts.mel_opts.num_bins = FLAGS_num_bins;
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opt.fbank_opts.frame_opts.dither = 0.0;
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std::unique_ptr<ppspeech::FrontendInterface> fbank(
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new ppspeech::Fbank(opt, std::move(data_source)));
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std::unique_ptr<ppspeech::FrontendInterface> cmvn(
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new ppspeech::CMVN(FLAGS_cmvn_file, std::move(fbank)));
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ppspeech::FeatureCacheOptions feat_cache_opts;
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// the feature cache output feature chunk by chunk.
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// frame_chunk_size : num frame of a chunk.
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// frame_chunk_stride: chunk sliding window stride.
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feat_cache_opts.frame_chunk_stride = 1;
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feat_cache_opts.frame_chunk_size = 1;
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ppspeech::FeatureCache feature_cache(feat_cache_opts, std::move(cmvn));
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LOG(INFO) << "feat dim: " << feature_cache.Dim();
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int sample_rate = 16000;
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float streaming_chunk = FLAGS_streaming_chunk;
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int chunk_sample_size = streaming_chunk * sample_rate;
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LOG(INFO) << "sr: " << sample_rate;
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LOG(INFO) << "chunk size (s): " << streaming_chunk;
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LOG(INFO) << "chunk size (sample): " << chunk_sample_size;
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for (; !wav_reader.Done(); wav_reader.Next()) {
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std::string utt = wav_reader.Key();
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const kaldi::WaveData& wave_data = wav_reader.Value();
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LOG(INFO) << "process utt: " << utt;
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int32 this_channel = 0;
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kaldi::SubVector<kaldi::BaseFloat> waveform(wave_data.Data(),
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this_channel);
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int tot_samples = waveform.Dim();
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LOG(INFO) << "wav len (sample): " << tot_samples;
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int sample_offset = 0;
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std::vector<kaldi::Vector<BaseFloat>> feats;
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int feature_rows = 0;
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while (sample_offset < tot_samples) {
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int cur_chunk_size =
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std::min(chunk_sample_size, tot_samples - sample_offset);
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kaldi::Vector<kaldi::BaseFloat> wav_chunk(cur_chunk_size);
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for (int i = 0; i < cur_chunk_size; ++i) {
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wav_chunk(i) = waveform(sample_offset + i);
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}
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kaldi::Vector<BaseFloat> features;
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feature_cache.Accept(wav_chunk);
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if (cur_chunk_size < chunk_sample_size) {
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feature_cache.SetFinished();
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}
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bool flag = true;
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do {
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flag = feature_cache.Read(&features);
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feats.push_back(features);
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feature_rows += features.Dim() / feature_cache.Dim();
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} while (flag == true && features.Dim() != 0);
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sample_offset += cur_chunk_size;
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}
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int cur_idx = 0;
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kaldi::Matrix<kaldi::BaseFloat> features(feature_rows,
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feature_cache.Dim());
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for (auto feat : feats) {
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int num_rows = feat.Dim() / feature_cache.Dim();
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for (int row_idx = 0; row_idx < num_rows; ++row_idx) {
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for (size_t col_idx = 0; col_idx < feature_cache.Dim();
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++col_idx) {
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features(cur_idx, col_idx) =
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feat(row_idx * feature_cache.Dim() + col_idx);
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}
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++cur_idx;
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}
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}
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feat_writer.Write(utt, features);
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feature_cache.Reset();
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if (num_done % 50 == 0 && num_done != 0)
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KALDI_VLOG(2) << "Processed " << num_done << " utterances";
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num_done++;
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}
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KALDI_LOG << "Done " << num_done << " utterances, " << num_err
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<< " with errors.";
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return (num_done != 0 ? 0 : 1);
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}
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