Update audio_processing module
Corresponds to upstream commit 524e9b043e7e86fd72353b987c9d5f6a1ebf83e1 Update notes: * Pull in third party license file * Replace .gypi files with BUILD.gn to keep track of what changes upstream * Bunch of new filse pulled in as dependencies * Won't build yet due to changes needed on top of these
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/*
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* Copyright (c) 2013 The WebRTC project authors. All Rights Reserved.
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*
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* Use of this source code is governed by a BSD-style license
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* that can be found in the LICENSE file in the root of the source
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* tree. An additional intellectual property rights grant can be found
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* in the file PATENTS. All contributing project authors may
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* be found in the AUTHORS file in the root of the source tree.
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*/
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#ifndef WEBRTC_MODULES_AUDIO_PROCESSING_TRANSIENT_TRANSIENT_DETECTOR_H_
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#define WEBRTC_MODULES_AUDIO_PROCESSING_TRANSIENT_TRANSIENT_DETECTOR_H_
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#include <deque>
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#include "webrtc/base/scoped_ptr.h"
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#include "webrtc/modules/audio_processing/transient/moving_moments.h"
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#include "webrtc/modules/audio_processing/transient/wpd_tree.h"
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namespace webrtc {
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// This is an implementation of the transient detector described in "Causal
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// Wavelet based transient detector".
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// Calculates the log-likelihood of a transient to happen on a signal at any
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// given time based on the previous samples; it uses a WPD tree to analyze the
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// signal. It preserves its state, so it can be multiple-called.
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class TransientDetector {
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public:
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// TODO(chadan): The only supported wavelet is Daubechies 8 using a WPD tree
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// of 3 levels. Make an overloaded constructor to allow different wavelets and
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// depths of the tree. When needed.
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// Creates a wavelet based transient detector.
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TransientDetector(int sample_rate_hz);
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~TransientDetector();
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// Calculates the log-likelihood of the existence of a transient in |data|.
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// |data_length| has to be equal to |samples_per_chunk_|.
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// Returns a value between 0 and 1, as a non linear representation of this
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// likelihood.
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// Returns a negative value on error.
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float Detect(const float* data,
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size_t data_length,
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const float* reference_data,
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size_t reference_length);
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bool using_reference() { return using_reference_; }
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private:
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float ReferenceDetectionValue(const float* data, size_t length);
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static const size_t kLevels = 3;
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static const size_t kLeaves = 1 << kLevels;
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size_t samples_per_chunk_;
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rtc::scoped_ptr<WPDTree> wpd_tree_;
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size_t tree_leaves_data_length_;
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// A MovingMoments object is needed for each leaf in the WPD tree.
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rtc::scoped_ptr<MovingMoments> moving_moments_[kLeaves];
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rtc::scoped_ptr<float[]> first_moments_;
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rtc::scoped_ptr<float[]> second_moments_;
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// Stores the last calculated moments from the previous detection.
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float last_first_moment_[kLeaves];
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float last_second_moment_[kLeaves];
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// We keep track of the previous results from the previous chunks, so it can
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// be used to effectively give results according to the |transient_length|.
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std::deque<float> previous_results_;
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// Number of chunks that are going to return only zeros at the beginning of
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// the detection. It helps to avoid infs and nans due to the lack of
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// information.
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int chunks_at_startup_left_to_delete_;
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float reference_energy_;
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bool using_reference_;
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};
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} // namespace webrtc
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#endif // WEBRTC_MODULES_AUDIO_PROCESSING_TRANSIENT_TRANSIENT_DETECTOR_H_
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