Merge pull request #2003 from SmileGoat/refactor_file_struct
[speechx] refactor frontendpull/2005/head
Hui Zhang
2 years ago
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GitHub
commit
182858bf88
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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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#pragma once
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#include "frontend_itf.h"
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#include "kaldi/feat/feature-window.h"
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namespace ppspeech {
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template <class F>
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class StreamingFeatureTpl : public FrontendInterface {
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public:
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typedef typename F::Options Options;
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StreamingFeatureTpl(const Options& opts,
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std::unique_ptr<FrontendInterface> base_extractor);
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virtual void Accept(const kaldi::VectorBase<kaldi::BaseFloat>& waves);
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virtual bool Read(kaldi::Vector<kaldi::BaseFloat>* feats);
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// the dim_ is the dim of single frame feature
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virtual size_t Dim() const { return computer_.Dim(); }
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virtual void SetFinished() { base_extractor_->SetFinished(); }
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virtual bool IsFinished() const { return base_extractor_->IsFinished(); }
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virtual void Reset() {
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base_extractor_->Reset();
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remained_wav_.Resize(0);
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}
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private:
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bool Compute(const kaldi::Vector<kaldi::BaseFloat>& waves,
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kaldi::Vector<kaldi::BaseFloat>* feats);
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Options opts_;
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std::unique_ptr<FrontendInterface> base_extractor_;
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kaldi::FeatureWindowFunction window_function_;
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kaldi::Vector<kaldi::BaseFloat> remained_wav_;
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F computer_;
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};
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} // namespace ppspeech
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#include "frontend/audio/feature_common_inl.h"
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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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namespace ppspeech {
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template <class F>
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StreamingFeatureTpl<F>::StreamingFeatureTpl(const Options& opts,
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std::unique_ptr<FrontendInterface> base_extractor):
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opts_(opts),
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computer_(opts),
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window_function_(opts.frame_opts) {
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base_extractor_ = std::move(base_extractor);
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}
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template <class F>
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void StreamingFeatureTpl<F>::Accept(const kaldi::VectorBase<kaldi::BaseFloat>& waves) {
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base_extractor_->Accept(waves);
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}
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template <class F>
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bool StreamingFeatureTpl<F>::Read(kaldi::Vector<kaldi::BaseFloat>* feats) {
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kaldi::Vector<kaldi::BaseFloat> wav(base_extractor_->Dim());
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bool flag = base_extractor_->Read(&wav);
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if (flag == false || wav.Dim() == 0) return false;
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// append remaned waves
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int32 wav_len = wav.Dim();
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int32 left_len = remained_wav_.Dim();
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kaldi::Vector<kaldi::BaseFloat> waves(left_len + wav_len);
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waves.Range(0, left_len).CopyFromVec(remained_wav_);
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waves.Range(left_len, wav_len).CopyFromVec(wav);
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// compute speech feature
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Compute(waves, feats);
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// cache remaned waves
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kaldi::FrameExtractionOptions frame_opts = computer_.GetFrameOptions();
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int32 num_frames = kaldi::NumFrames(waves.Dim(), frame_opts);
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int32 frame_shift = frame_opts.WindowShift();
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int32 left_samples = waves.Dim() - frame_shift * num_frames;
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remained_wav_.Resize(left_samples);
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remained_wav_.CopyFromVec(
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waves.Range(frame_shift * num_frames, left_samples));
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return true;
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}
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// Compute feat
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template <class F>
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bool StreamingFeatureTpl<F>::Compute(const kaldi::Vector<kaldi::BaseFloat>& waves,
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kaldi::Vector<kaldi::BaseFloat>* feats) {
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const kaldi::FrameExtractionOptions& frame_opts =
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computer_.GetFrameOptions();
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int32 num_samples = waves.Dim();
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int32 frame_length = frame_opts.WindowSize();
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int32 sample_rate = frame_opts.samp_freq;
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if (num_samples < frame_length) {
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return true;
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}
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int32 num_frames = kaldi::NumFrames(num_samples, frame_opts);
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feats->Resize(num_frames * Dim());
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kaldi::Vector<kaldi::BaseFloat> window;
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bool need_raw_log_energy = computer_.NeedRawLogEnergy();
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for (int32 frame = 0; frame < num_frames; frame++) {
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kaldi::BaseFloat raw_log_energy = 0.0;
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kaldi::ExtractWindow(0,
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waves,
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frame,
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frame_opts,
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window_function_,
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&window,
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need_raw_log_energy ? &raw_log_energy : NULL);
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kaldi::Vector<kaldi::BaseFloat> this_feature(computer_.Dim(), kaldi::kUndefined);
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computer_.Compute(&window, &this_feature);
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kaldi::SubVector<kaldi::BaseFloat> output_row(feats->Data() + frame * Dim(), Dim());
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output_row.CopyFromVec(this_feature);
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}
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return true;
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}
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} // namespace ppspeech
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