Most of the complex functionality in AEC3 is done using vector maths. This CL adds a new functionality for performing these using SIMD operations in a simple manner whenever such are available. The reason for putting the implementations in the header file is to allow any possible inlining. BUG=webrtc:6018 Review-Url: https://codereview.webrtc.org/2813823002 Cr-Commit-Position: refs/heads/master@{#17663}
241 lines
9.5 KiB
C++
241 lines
9.5 KiB
C++
/*
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* Copyright (c) 2017 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 "webrtc/modules/audio_processing/aec3/suppression_gain.h"
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#include "webrtc/typedefs.h"
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#if defined(WEBRTC_ARCH_X86_FAMILY)
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#include <emmintrin.h>
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#endif
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#include <math.h>
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#include <algorithm>
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#include <functional>
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#include <numeric>
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#include "webrtc/base/checks.h"
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#include "webrtc/modules/audio_processing/aec3/vector_math.h"
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namespace webrtc {
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namespace {
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void GainPostProcessing(std::array<float, kFftLengthBy2Plus1>* gain_squared) {
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// Limit the low frequency gains to avoid the impact of the high-pass filter
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// on the lower-frequency gain influencing the overall achieved gain.
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(*gain_squared)[1] = std::min((*gain_squared)[1], (*gain_squared)[2]);
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(*gain_squared)[0] = (*gain_squared)[1];
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// Limit the high frequency gains to avoid the impact of the anti-aliasing
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// filter on the upper-frequency gains influencing the overall achieved
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// gain. TODO(peah): Update this when new anti-aliasing filters are
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// implemented.
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constexpr size_t kAntiAliasingImpactLimit = (64 * 2000) / 8000;
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std::for_each(gain_squared->begin() + kAntiAliasingImpactLimit,
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gain_squared->end() - 1,
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[gain_squared, kAntiAliasingImpactLimit](float& a) {
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a = std::min(a, (*gain_squared)[kAntiAliasingImpactLimit]);
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});
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(*gain_squared)[kFftLengthBy2] = (*gain_squared)[kFftLengthBy2Minus1];
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}
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constexpr int kNumIterations = 2;
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constexpr float kEchoMaskingMargin = 1.f / 20.f;
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constexpr float kBandMaskingFactor = 1.f / 10.f;
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constexpr float kTimeMaskingFactor = 1.f / 10.f;
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// TODO(peah): Add further optimizations, in particular for the divisions.
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void ComputeGains(
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Aec3Optimization optimization,
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const std::array<float, kFftLengthBy2Plus1>& nearend_power,
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const std::array<float, kFftLengthBy2Plus1>& residual_echo_power,
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const std::array<float, kFftLengthBy2Plus1>& comfort_noise_power,
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float strong_nearend_margin,
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std::array<float, kFftLengthBy2Minus1>* previous_gain_squared,
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std::array<float, kFftLengthBy2Minus1>* previous_masker,
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std::array<float, kFftLengthBy2Plus1>* gain) {
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std::array<float, kFftLengthBy2Minus1> masker;
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std::array<float, kFftLengthBy2Minus1> same_band_masker;
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std::array<float, kFftLengthBy2Minus1> one_by_residual_echo_power;
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std::array<bool, kFftLengthBy2Minus1> strong_nearend;
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std::array<float, kFftLengthBy2Plus1> neighboring_bands_masker;
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std::array<float, kFftLengthBy2Plus1>* gain_squared = gain;
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aec3::VectorMath math(optimization);
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// Precompute 1/residual_echo_power.
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std::transform(residual_echo_power.begin() + 1, residual_echo_power.end() - 1,
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one_by_residual_echo_power.begin(),
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[](float a) { return a > 0.f ? 1.f / a : -1.f; });
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// Precompute indicators for bands with strong nearend.
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std::transform(
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residual_echo_power.begin() + 1, residual_echo_power.end() - 1,
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nearend_power.begin() + 1, strong_nearend.begin(),
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[&](float a, float b) { return a <= strong_nearend_margin * b; });
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// Precompute masker for the same band.
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std::transform(comfort_noise_power.begin() + 1, comfort_noise_power.end() - 1,
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previous_masker->begin(), same_band_masker.begin(),
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[&](float a, float b) { return a + kTimeMaskingFactor * b; });
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for (int k = 0; k < kNumIterations; ++k) {
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if (k == 0) {
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// Add masker from the same band.
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std::copy(same_band_masker.begin(), same_band_masker.end(),
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masker.begin());
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} else {
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// Add masker for neighboring bands.
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math.Multiply(nearend_power, *gain_squared, neighboring_bands_masker);
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math.Accumulate(comfort_noise_power, neighboring_bands_masker);
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std::transform(
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neighboring_bands_masker.begin(), neighboring_bands_masker.end() - 2,
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neighboring_bands_masker.begin() + 2, masker.begin(),
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[&](float a, float b) { return kBandMaskingFactor * (a + b); });
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// Add masker from the same band.
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math.Accumulate(same_band_masker, masker);
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}
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// Compute new gain as:
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// G2(t,f) = (comfort_noise_power(t,f) + G2(t-1)*nearend_power(t-1)) *
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// kTimeMaskingFactor
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// * kEchoMaskingMargin / residual_echo_power(t,f).
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// or
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// G2(t,f) = ((comfort_noise_power(t,f) + G2(t-1) *
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// nearend_power(t-1)) * kTimeMaskingFactor +
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// (comfort_noise_power(t, f-1) + comfort_noise_power(t, f+1) +
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// (G2(t,f-1)*nearend_power(t, f-1) +
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// G2(t,f+1)*nearend_power(t, f+1)) *
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// kTimeMaskingFactor) * kBandMaskingFactor)
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// * kEchoMaskingMargin / residual_echo_power(t,f).
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std::transform(
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masker.begin(), masker.end(), one_by_residual_echo_power.begin(),
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gain_squared->begin() + 1, [&](float a, float b) {
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return b >= 0 ? std::min(kEchoMaskingMargin * a * b, 1.f) : 1.f;
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});
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// Limit gain for bands with strong nearend.
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std::transform(gain_squared->begin() + 1, gain_squared->end() - 1,
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strong_nearend.begin(), gain_squared->begin() + 1,
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[](float a, bool b) { return b ? 1.f : a; });
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// Limit the allowed gain update over time.
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std::transform(gain_squared->begin() + 1, gain_squared->end() - 1,
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previous_gain_squared->begin(), gain_squared->begin() + 1,
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[](float a, float b) {
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return b < 0.001f ? std::min(a, 0.001f)
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: std::min(a, b * 2.f);
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});
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// Process the gains to avoid artefacts caused by gain realization in the
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// filterbank and impact of external pre-processing of the signal.
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GainPostProcessing(gain_squared);
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}
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std::copy(gain_squared->begin() + 1, gain_squared->end() - 1,
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previous_gain_squared->begin());
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math.Multiply(
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rtc::ArrayView<const float>(&(*gain_squared)[1], previous_masker->size()),
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rtc::ArrayView<const float>(&nearend_power[1], previous_masker->size()),
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*previous_masker);
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math.Accumulate(rtc::ArrayView<const float>(&comfort_noise_power[1],
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previous_masker->size()),
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*previous_masker);
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math.Sqrt(*gain);
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}
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} // namespace
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// Computes an upper bound on the gain to apply for high frequencies.
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float HighFrequencyGainBound(bool saturated_echo,
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const std::vector<std::vector<float>>& render) {
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if (render.size() == 1) {
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return 1.f;
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}
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// Always attenuate the upper bands when there is saturated echo.
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if (saturated_echo) {
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return 0.001f;
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}
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// Compute the upper and lower band energies.
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float low_band_energy =
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std::accumulate(render[0].begin(), render[0].end(), 0.f,
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[](float a, float b) -> float { return a + b * b; });
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float high_band_energies = 0.f;
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for (size_t k = 1; k < render.size(); ++k) {
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high_band_energies = std::max(
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high_band_energies,
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std::accumulate(render[k].begin(), render[k].end(), 0.f,
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[](float a, float b) -> float { return a + b * b; }));
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}
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// If there is more power in the lower frequencies than the upper frequencies,
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// or if the power in upper frequencies is low, do not bound the gain in the
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// upper bands.
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if (high_band_energies < low_band_energy ||
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high_band_energies < kSubBlockSize * 10.f * 10.f) {
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return 1.f;
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}
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// In all other cases, bound the gain for upper frequencies.
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RTC_DCHECK_LE(low_band_energy, high_band_energies);
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return 0.01f * sqrtf(low_band_energy / high_band_energies);
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}
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SuppressionGain::SuppressionGain(Aec3Optimization optimization)
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: optimization_(optimization) {
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previous_gain_squared_.fill(1.f);
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previous_masker_.fill(0.f);
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}
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void SuppressionGain::GetGain(
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const std::array<float, kFftLengthBy2Plus1>& nearend_power,
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const std::array<float, kFftLengthBy2Plus1>& residual_echo_power,
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const std::array<float, kFftLengthBy2Plus1>& comfort_noise_power,
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bool saturated_echo,
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const std::vector<std::vector<float>>& render,
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size_t num_capture_bands,
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bool force_zero_gain,
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float* high_bands_gain,
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std::array<float, kFftLengthBy2Plus1>* low_band_gain) {
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RTC_DCHECK(high_bands_gain);
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RTC_DCHECK(low_band_gain);
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if (force_zero_gain) {
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previous_gain_squared_.fill(0.f);
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std::copy(comfort_noise_power.begin() + 1, comfort_noise_power.end() - 1,
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previous_masker_.begin());
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low_band_gain->fill(0.f);
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*high_bands_gain = 0.f;
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return;
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}
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// Choose margin to use.
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const float margin = saturated_echo ? 0.001f : 0.01f;
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ComputeGains(optimization_, nearend_power, residual_echo_power,
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comfort_noise_power, margin, &previous_gain_squared_,
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&previous_masker_, low_band_gain);
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if (num_capture_bands > 1) {
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// Compute the gain for upper frequencies.
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const float min_high_band_gain =
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HighFrequencyGainBound(saturated_echo, render);
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*high_bands_gain =
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*std::min_element(low_band_gain->begin() + 32, low_band_gain->end());
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*high_bands_gain = std::min(*high_bands_gain, min_high_band_gain);
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} else {
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*high_bands_gain = 1.f;
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}
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}
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} // namespace webrtc
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