196 lines
7.8 KiB
C++
196 lines
7.8 KiB
C++
/*
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* Copyright (c) 2019 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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#include "modules/audio_processing/ns/noise_estimator.h"
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#include <algorithm>
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#include "modules/audio_processing/ns/fast_math.h"
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#include "rtc_base/checks.h"
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namespace webrtc {
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namespace {
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// Log(i).
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constexpr std::array<float, 129> log_table = {
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0.f, 0.f, 0.f, 0.f, 0.f, 1.609438f, 1.791759f,
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1.945910f, 2.079442f, 2.197225f, 2.302585f, 2.397895f, 2.484907f, 2.564949f,
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2.639057f, 2.708050f, 2.772589f, 2.833213f, 2.890372f, 2.944439f, 2.995732f,
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3.044522f, 3.091043f, 3.135494f, 3.178054f, 3.218876f, 3.258097f, 3.295837f,
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3.332205f, 3.367296f, 3.401197f, 3.433987f, 3.465736f, 3.496507f, 3.526361f,
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3.555348f, 3.583519f, 3.610918f, 3.637586f, 3.663562f, 3.688879f, 3.713572f,
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3.737669f, 3.761200f, 3.784190f, 3.806663f, 3.828641f, 3.850147f, 3.871201f,
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3.891820f, 3.912023f, 3.931826f, 3.951244f, 3.970292f, 3.988984f, 4.007333f,
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4.025352f, 4.043051f, 4.060443f, 4.077538f, 4.094345f, 4.110874f, 4.127134f,
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4.143135f, 4.158883f, 4.174387f, 4.189655f, 4.204693f, 4.219508f, 4.234107f,
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4.248495f, 4.262680f, 4.276666f, 4.290460f, 4.304065f, 4.317488f, 4.330733f,
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4.343805f, 4.356709f, 4.369448f, 4.382027f, 4.394449f, 4.406719f, 4.418841f,
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4.430817f, 4.442651f, 4.454347f, 4.465908f, 4.477337f, 4.488636f, 4.499810f,
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4.510859f, 4.521789f, 4.532599f, 4.543295f, 4.553877f, 4.564348f, 4.574711f,
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4.584968f, 4.595119f, 4.605170f, 4.615121f, 4.624973f, 4.634729f, 4.644391f,
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4.653960f, 4.663439f, 4.672829f, 4.682131f, 4.691348f, 4.700480f, 4.709530f,
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4.718499f, 4.727388f, 4.736198f, 4.744932f, 4.753591f, 4.762174f, 4.770685f,
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4.779124f, 4.787492f, 4.795791f, 4.804021f, 4.812184f, 4.820282f, 4.828314f,
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4.836282f, 4.844187f, 4.852030f};
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} // namespace
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NoiseEstimator::NoiseEstimator(const SuppressionParams& suppression_params)
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: suppression_params_(suppression_params) {
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noise_spectrum_.fill(0.f);
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prev_noise_spectrum_.fill(0.f);
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conservative_noise_spectrum_.fill(0.f);
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parametric_noise_spectrum_.fill(0.f);
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}
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void NoiseEstimator::PrepareAnalysis() {
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std::copy(noise_spectrum_.begin(), noise_spectrum_.end(),
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prev_noise_spectrum_.begin());
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}
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void NoiseEstimator::PreUpdate(
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int32_t num_analyzed_frames,
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rtc::ArrayView<const float, kFftSizeBy2Plus1> signal_spectrum,
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float signal_spectral_sum) {
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quantile_noise_estimator_.Estimate(signal_spectrum, noise_spectrum_);
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if (num_analyzed_frames < kShortStartupPhaseBlocks) {
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// Compute simplified noise model during startup.
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const size_t kStartBand = 5;
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float sum_log_i_log_magn = 0.f;
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float sum_log_i = 0.f;
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float sum_log_i_square = 0.f;
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float sum_log_magn = 0.f;
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for (size_t i = kStartBand; i < kFftSizeBy2Plus1; ++i) {
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float log_i = log_table[i];
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sum_log_i += log_i;
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sum_log_i_square += log_i * log_i;
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float log_signal = LogApproximation(signal_spectrum[i]);
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sum_log_magn += log_signal;
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sum_log_i_log_magn += log_i * log_signal;
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}
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// Estimate the parameter for the level of the white noise.
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constexpr float kOneByFftSizeBy2Plus1 = 1.f / kFftSizeBy2Plus1;
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white_noise_level_ += signal_spectral_sum * kOneByFftSizeBy2Plus1 *
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suppression_params_.over_subtraction_factor;
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// Estimate pink noise parameters.
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float denom = sum_log_i_square * (kFftSizeBy2Plus1 - kStartBand) -
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sum_log_i * sum_log_i;
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float num =
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sum_log_i_square * sum_log_magn - sum_log_i * sum_log_i_log_magn;
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RTC_DCHECK_NE(denom, 0.f);
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float pink_noise_adjustment = num / denom;
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// Constrain the estimated spectrum to be positive.
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pink_noise_adjustment = std::max(pink_noise_adjustment, 0.f);
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pink_noise_numerator_ += pink_noise_adjustment;
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num = sum_log_i * sum_log_magn -
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(kFftSizeBy2Plus1 - kStartBand) * sum_log_i_log_magn;
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RTC_DCHECK_NE(denom, 0.f);
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pink_noise_adjustment = num / denom;
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// Constrain the pink noise power to be in the interval [0, 1].
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pink_noise_adjustment = std::max(std::min(pink_noise_adjustment, 1.f), 0.f);
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pink_noise_exp_ += pink_noise_adjustment;
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const float one_by_num_analyzed_frames_plus_1 =
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1.f / (num_analyzed_frames + 1.f);
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// Calculate the frequency-independent parts of parametric noise estimate.
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float parametric_exp = 0.f;
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float parametric_num = 0.f;
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if (pink_noise_exp_ > 0.f) {
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// Use pink noise estimate.
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parametric_num = ExpApproximation(pink_noise_numerator_ *
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one_by_num_analyzed_frames_plus_1);
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parametric_num *= num_analyzed_frames + 1.f;
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parametric_exp = pink_noise_exp_ * one_by_num_analyzed_frames_plus_1;
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}
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constexpr float kOneByShortStartupPhaseBlocks =
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1.f / kShortStartupPhaseBlocks;
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for (size_t i = 0; i < kFftSizeBy2Plus1; ++i) {
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// Estimate the background noise using the white and pink noise
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// parameters.
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if (pink_noise_exp_ == 0.f) {
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// Use white noise estimate.
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parametric_noise_spectrum_[i] = white_noise_level_;
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} else {
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// Use pink noise estimate.
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float use_band = i < kStartBand ? kStartBand : i;
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float denom = PowApproximation(use_band, parametric_exp);
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RTC_DCHECK_NE(denom, 0.f);
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parametric_noise_spectrum_[i] = parametric_num / denom;
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}
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}
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// Weight quantile noise with modeled noise.
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for (size_t i = 0; i < kFftSizeBy2Plus1; ++i) {
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noise_spectrum_[i] *= num_analyzed_frames;
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float tmp = parametric_noise_spectrum_[i] *
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(kShortStartupPhaseBlocks - num_analyzed_frames);
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noise_spectrum_[i] += tmp * one_by_num_analyzed_frames_plus_1;
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noise_spectrum_[i] *= kOneByShortStartupPhaseBlocks;
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}
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}
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}
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void NoiseEstimator::PostUpdate(
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rtc::ArrayView<const float> speech_probability,
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rtc::ArrayView<const float, kFftSizeBy2Plus1> signal_spectrum) {
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// Time-avg parameter for noise_spectrum update.
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constexpr float kNoiseUpdate = 0.9f;
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float gamma = kNoiseUpdate;
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for (size_t i = 0; i < kFftSizeBy2Plus1; ++i) {
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const float prob_speech = speech_probability[i];
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const float prob_non_speech = 1.f - prob_speech;
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// Temporary noise update used for speech frames if update value is less
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// than previous.
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float noise_update_tmp =
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gamma * prev_noise_spectrum_[i] +
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(1.f - gamma) * (prob_non_speech * signal_spectrum[i] +
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prob_speech * prev_noise_spectrum_[i]);
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// Time-constant based on speech/noise_spectrum state.
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float gamma_old = gamma;
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// Increase gamma for frame likely to be seech.
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constexpr float kProbRange = .2f;
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gamma = prob_speech > kProbRange ? .99f : kNoiseUpdate;
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// Conservative noise_spectrum update.
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if (prob_speech < kProbRange) {
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conservative_noise_spectrum_[i] +=
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0.05f * (signal_spectrum[i] - conservative_noise_spectrum_[i]);
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}
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// Noise_spectrum update.
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if (gamma == gamma_old) {
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noise_spectrum_[i] = noise_update_tmp;
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} else {
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noise_spectrum_[i] =
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gamma * prev_noise_spectrum_[i] +
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(1.f - gamma) * (prob_non_speech * signal_spectrum[i] +
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prob_speech * prev_noise_spectrum_[i]);
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// Allow for noise_spectrum update downwards: If noise_spectrum update
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// decreases the noise_spectrum, it is safe, so allow it to happen.
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noise_spectrum_[i] = std::min(noise_spectrum_[i], noise_update_tmp);
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}
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}
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}
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} // namespace webrtc
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