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https://github.com/danog/libtgvoip.git
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5caaaafa42
I'm now using the entire audio processing module from WebRTC as opposed to individual DSP algorithms pulled from there before. Seems to work better this way.
89 lines
3.0 KiB
C++
89 lines
3.0 KiB
C++
/*
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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 MODULES_AUDIO_PROCESSING_TRANSIENT_TRANSIENT_DETECTOR_H_
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#define MODULES_AUDIO_PROCESSING_TRANSIENT_TRANSIENT_DETECTOR_H_
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#include <stddef.h>
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#include <deque>
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#include <memory>
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#include "modules/audio_processing/transient/moving_moments.h"
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#include "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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std::unique_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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std::unique_ptr<MovingMoments> moving_moments_[kLeaves];
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std::unique_ptr<float[]> first_moments_;
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std::unique_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 // MODULES_AUDIO_PROCESSING_TRANSIENT_TRANSIENT_DETECTOR_H_
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