parent
446e83ad25
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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 <deque>
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#include <iostream>
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#include <istream>
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#include <map>
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#include <memory>
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#include <ostream>
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#include <set>
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#include <sstream>
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#include <stack>
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#include <string>
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#include <vector>
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#include <unordered_map>
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#include <unordered_set>
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#include "base/log.h"
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#include "base/basic_types.h"
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#include "base/macros.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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#pragma once
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#include "fst/flags.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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#pragma once
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#include "glog/logging.h"
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// this code is from https://github.com/progschj/ThreadPool
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#ifndef BASE_THREAD_POOL_H
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#define BASE_THREAD_POOL_H
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#include <vector>
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#include <queue>
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#include <memory>
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#include <thread>
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#include <mutex>
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#include <condition_variable>
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#include <future>
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#include <functional>
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#include <stdexcept>
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class ThreadPool {
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public:
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ThreadPool(size_t);
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template<class F, class... Args>
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auto enqueue(F&& f, Args&&... args)
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-> std::future<typename std::result_of<F(Args...)>::type>;
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~ThreadPool();
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private:
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// need to keep track of threads so we can join them
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std::vector< std::thread > workers;
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// the task queue
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std::queue< std::function<void()> > tasks;
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// synchronization
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std::mutex queue_mutex;
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std::condition_variable condition;
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bool stop;
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};
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// the constructor just launches some amount of workers
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inline ThreadPool::ThreadPool(size_t threads)
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: stop(false)
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{
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for(size_t i = 0;i<threads;++i)
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workers.emplace_back(
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[this]
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{
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for(;;)
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{
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std::function<void()> task;
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{
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std::unique_lock<std::mutex> lock(this->queue_mutex);
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this->condition.wait(lock,
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[this]{ return this->stop || !this->tasks.empty(); });
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if(this->stop && this->tasks.empty())
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return;
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task = std::move(this->tasks.front());
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this->tasks.pop();
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}
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task();
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}
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}
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);
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}
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// add new work item to the pool
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template<class F, class... Args>
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auto ThreadPool::enqueue(F&& f, Args&&... args)
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-> std::future<typename std::result_of<F(Args...)>::type>
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{
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using return_type = typename std::result_of<F(Args...)>::type;
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auto task = std::make_shared< std::packaged_task<return_type()> >(
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std::bind(std::forward<F>(f), std::forward<Args>(args)...)
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);
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std::future<return_type> res = task->get_future();
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{
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std::unique_lock<std::mutex> lock(queue_mutex);
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// don't allow enqueueing after stopping the pool
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if(stop)
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throw std::runtime_error("enqueue on stopped ThreadPool");
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tasks.emplace([task](){ (*task)(); });
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}
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condition.notify_one();
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return res;
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}
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// the destructor joins all threads
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inline ThreadPool::~ThreadPool()
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{
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{
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std::unique_lock<std::mutex> lock(queue_mutex);
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stop = true;
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}
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condition.notify_all();
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for(std::thread &worker: workers)
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worker.join();
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}
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#endif
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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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// wrap the fbank feat of kaldi, todo (SmileGoat)
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#include "kaldi/feat/feature-mfcc.h"
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#incldue "kaldi/matrix/kaldi-vector.h"
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namespace ppspeech {
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class FbankExtractor : FeatureExtractorInterface {
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public:
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explicit FbankExtractor(const FbankOptions& opts,
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share_ptr<FeatureExtractorInterface> pre_extractor);
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virtual void AcceptWaveform(const kaldi::Vector<kaldi::BaseFloat>& input) = 0;
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virtual void Read(kaldi::Vector<kaldi::BaseFloat>* feat) = 0;
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virtual size_t Dim() const = 0;
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private:
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bool Compute(const kaldi::Vector<kaldi::BaseFloat>& wave,
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kaldi::Vector<kaldi::BaseFloat>* feat) const;
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};
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} // namespace ppspeech
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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 "base/basic_types.h"
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#incldue "kaldi/matrix/kaldi-vector.h"
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namespace ppspeech {
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class FeatureExtractorInterface {
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public:
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virtual void AcceptWaveform(const kaldi::Vector<kaldi::BaseFloat>& input) = 0;
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virtual void Read(kaldi::Vector<kaldi::BaseFloat>* feat) = 0;
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virtual size_t Dim() const = 0;
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};
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} // namespace ppspeech
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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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#include "frontend/linear_spectrogram.h"
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#include "kaldi/base/kaldi-math.h"
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#include "kaldi/matrix/matrix-functions.h"
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using kaldi::int32;
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using kaldi::BaseFloat;
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using kaldi::Vector;
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using kaldi::Matrix;
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using std::vector;
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LinearSpectrogram::LinearSpectrogram(const LinearSpectrogramOptions& opts) {
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int32 window_size = opts.frame_opts.WindowSize();
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int32 window_shift = opts.frame_opts.WindowShift();
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fft_points_ = window_size;
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hanning_window_.resize(window_size);
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double a = M_2PI / (window_size - 1);
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hanning_window_energy_ = 0;
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for (int i = 0; i < window_size; ++i) {
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hanning_window_[i] = 0.5 - 0.5 * cos(a * i);
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hanning_window_energy_ += hanning_window_[i] * hanning_window_[i];
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}
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}
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void LinearSpectrogram::AcceptWavefrom(const Vector<BaseFloat>& input) {
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wavefrom_.resize(input.Dim());
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for (size_t idx = 0; idx < input.Dim(); ++idx) {
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waveform_[idx] = input(idx);
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}
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}
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void LinearSpectrogram::Hanning(vector<float>* data) const {
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CHECK_GE(data->size(), hanning_window_.size());
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for (size_t i = 0; i < hanning_window_.size(); ++i) {
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data->at(i) *= hanning_window_[i];
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}
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}
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bool LinearSpectrogram::NumpyFft(vector<BaseFloat>* v,
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vector<BaseFloat>* real,
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vector<BaseFloat>* img) {
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if (RealFft(v, true)) {
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LOG(ERROR) << "compute the fft occurs error";
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return false;
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}
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real->push_back(v->at(0));
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img->push_back(0);
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for (int i = 1; i < v->size() / 2; i++) {
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real->push_back(v->at(2 * i));
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img->push_back(v->at(2 * i + 1));
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}
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real->push_back(v->at(1));
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img->push_back(0);
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return true;
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}
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// todo refactor later
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bool LinearSpectrogram::ReadFeats(Matrix<BaseFloat>* feats) const {
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vector<vector<BaseFloat>> feat;
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if (wavefrom_.empty()) {
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return false;
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}
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vector<vector<BaseFloat>> result;
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Compute(wavefrom_, result);
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feats->Resize(result.size(), result[0].size());
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for (int row_idx = 0; row_idx < result.size(); ++row_idx) {
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for (int col_idx = 0; col_idx < result.size(); ++col_idx) {
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feats(row_idx, col_idx) = result[row_idx][col_idx];
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}
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wavefrom_.clear();
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return true;
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}
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// Compute spectrogram feat, return num frames
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// todo: refactor later (SmileGoat)
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int32 LinearSpectrogram::Compute(const vector<float>& wave,
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vector<vector<float>>& feat) {
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int num_samples = wave.size();
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const int& frame_length = opts.frame_opts.WindowSize();
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const int& sample_rate = opts.frame_opts.samp_freq;
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const int& frame_shift = opts.frame_opts.WindowShift();
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const int& fft_points = fft_points_;
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const float scale = hanning_window_energy_ * frame_shift;
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if (num_samples < frame_length) {
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return 0;
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}
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int num_frames = 1 + ((num_samples - frame_length) / frame_shift);
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feat.resize(num_frames);
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vector<float> fft_real((fft_points_ / 2 + 1), 0);
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vector<float> fft_img((fft_points_ / 2 + 1), 0);
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vector<float> v(frame_length, 0);
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vector<float> power((fft_points / 2 + 1));
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for (int i = 0; i < num_frames; ++i) {
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vector<float> data(wave.data() + i * frame_shift,
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wave.data() + i * frame_shift + frame_length);
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Hanning(data);
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fft_img.clear();
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fft_real.clear();
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v.assign(data.begin(), data.end());
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if (NumpyFft(&v, fft_real, fft_img)) {
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LOG(ERROR)<< i << " fft compute occurs error, please checkout the input data";
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return -1;
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}
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feat[i].resize(fft_points / 2 + 1); // the last dimension is Fs/2 Hz
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for (int j = 0; j < (fft_points / 2 + 1); ++j) {
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power[j] = fft_real[j] * fft_real[j] + fft_img[j] * fft_img[j];
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feat[i][j] = power[j];
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if (j == 0 || j == feat[0].size() - 1) {
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feat[i][j] /= scale;
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} else {
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feat[i][j] *= (2.0 / scale);
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}
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// log added eps=1e-14
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feat[i][j] = std::log(feat[i][j] + 1e-14);
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}
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return 0;
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}
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#pragma once
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#include "frontend/feature_extractor_interface.h"
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#include "kaldi/feat/feature-window.h"
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#include "base/common.h"
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namespace ppspeech {
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struct LinearSpectrogramOptions {
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kaldi::FrameExtrationOptions frame_opts;
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|
LinearSpectrogramOptions():
|
||||||
|
frame_opts() {}
|
||||||
|
|
||||||
|
void Register(kaldi::OptionsItf* opts) {
|
||||||
|
frame_opts.Register(opts);
|
||||||
|
}
|
||||||
|
};
|
||||||
|
|
||||||
|
class LinearSpectrogram : public FeatureExtractorInterface {
|
||||||
|
public:
|
||||||
|
explict LinearSpectrogram(const LinearSpectrogramOptions& opts);
|
||||||
|
virtual void AcceptWavefrom(const kaldi::Vector<kaldi::BaseFloat>& input);
|
||||||
|
virtual void Read(kaldi::Vector<kaldi::BaseFloat>* feat);
|
||||||
|
virtual size_t Dim() const;
|
||||||
|
void ReadFeats(kaldi::Matrix<kaldi::BaesFloat>* feats) const;
|
||||||
|
|
||||||
|
private:
|
||||||
|
void Hanning(std::vector<kaldi::BaseFloat>& data) const;
|
||||||
|
kaldi::int32 Compute(const std::vector<kaldi::BaseFloat>& wave,
|
||||||
|
std::vector<std::vector<kaldi::BaseFloat>>& feat) const;
|
||||||
|
bool NumpyFft(std::vector<kaldi::BaseFloat>* v,
|
||||||
|
std::vector<kaldi::BaseFloat>* real,
|
||||||
|
std::vector<kaldi::BaseFloat>* img) const;
|
||||||
|
|
||||||
|
kaldi::int32 fft_points_;
|
||||||
|
size_t dim_;
|
||||||
|
std::vector<kaldi::BaseFloat> hanning_window_;
|
||||||
|
kaldi::BaseFloat hanning_window_energy_;
|
||||||
|
LinearSpectrogramOptions opts_;
|
||||||
|
std::vector<kaldi::BaseFloat> wavefrom_; // remove later, todo(SmileGoat)
|
||||||
|
DISALLOW_COPY_AND_ASSIGN(LinearSpectrogram);
|
||||||
|
};
|
||||||
|
|
||||||
|
|
||||||
|
} // namespace ppspeech
|
@ -0,0 +1,39 @@
|
|||||||
|
|
||||||
|
#include "frontend/linear_spectrogram.h"
|
||||||
|
#include "kaldi/util/table-types.h"
|
||||||
|
#include "base/log.h"
|
||||||
|
#include "base/flags.h"
|
||||||
|
#include "kaldi/feat/wave-reader.h"
|
||||||
|
|
||||||
|
DEFINE_string(wav_rspecifier, "", "test wav path");
|
||||||
|
DEFINE_string(feature_wspecifier, "", "test wav ark");
|
||||||
|
|
||||||
|
int main(int argc, char* argv[]) {
|
||||||
|
google::ParseCommandLineFlags(&argc, &argv, false);
|
||||||
|
google::InitGoogleLogging(argv[0]);
|
||||||
|
|
||||||
|
kaldi::SequentialTableReader<kaldi::WaveHolder> wav_reader(FLAGS_wav_rspecifier);
|
||||||
|
kaldi::BaseFloatMatrixWriter feat_writer(FLAGS_feature_wspecifier);
|
||||||
|
|
||||||
|
int32 num_done = 0, num_err = 0;
|
||||||
|
ppspeech::LinearSpectrogramOptions opt;
|
||||||
|
ppspeech::LinearSpectrogram linear_spectrogram(opt);
|
||||||
|
for (; !wav_reader.Done(); wav_reader.Next()) {
|
||||||
|
std::string utt = wav_reader.Key();
|
||||||
|
const kaldi::WaveData &wave_data = wav_reader.Value();
|
||||||
|
|
||||||
|
int32 this_channel = 0;
|
||||||
|
kaldi::SubVector<kaldi::BaseFloat> waveform(wave_data.Data(), this_channel);
|
||||||
|
kaldi::Matrix<BaseFloat> features;
|
||||||
|
linear_spectrogram.AcceptWaveform(waveform);
|
||||||
|
linear_spectrogram.ReadFeats(&features);
|
||||||
|
|
||||||
|
feat_writer.Write(utt, features);
|
||||||
|
if (num_done % 50 == 0 && num_done != 0)
|
||||||
|
KALDI_VLOG(2) << "Processed " << num_done << " utterances";
|
||||||
|
num_done++;
|
||||||
|
}
|
||||||
|
KALDI_LOG << "Done " << num_done << " utterances, " << num_err
|
||||||
|
<< " with errors.";
|
||||||
|
return (num_done != 0 ? 0 : 1);
|
||||||
|
}
|
@ -0,0 +1,16 @@
|
|||||||
|
// 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.
|
||||||
|
|
||||||
|
// wrap the mfcc feat of kaldi, todo (SmileGoat)
|
||||||
|
#include "kaldi/feat/feature-mfcc.h"
|
@ -0,0 +1,16 @@
|
|||||||
|
// 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.
|
||||||
|
|
||||||
|
// extract the window of kaldi feat.
|
||||||
|
|
Loading…
Reference in new issue