modules/audio_processing/aec3/subtractor.cc - src - Git at Google

 /*
  *  Copyright (c) 2017 The WebRTC project authors. All Rights Reserved.
  *
  *  Use of this source code is governed by a BSD-style license
  *  that can be found in the LICENSE file in the root of the source
  *  tree. An additional intellectual property rights grant can be found
  *  in the file PATENTS.  All contributing project authors may
  *  be found in the AUTHORS file in the root of the source tree.
  */

 #include "modules/audio_processing/aec3/subtractor.h"

 #include <algorithm>
 #include <utility>

 #include "api/array_view.h"
 #include "modules/audio_processing/aec3/adaptive_fir_filter_erl.h"
 #include "modules/audio_processing/aec3/fft_data.h"
 #include "modules/audio_processing/logging/apm_data_dumper.h"
 #include "rtc_base/checks.h"
 #include "rtc_base/numerics/safe_minmax.h"

 namespace webrtc {

 namespace {

 void PredictionError(const Aec3Fft& fft,
                      const FftData& S,
                      rtc::ArrayView<const float> y,
                      std::array<float, kBlockSize>* e,
                      std::array<float, kBlockSize>* s) {
   std::array<float, kFftLength> tmp;
   fft.Ifft(S, &tmp);
   constexpr float kScale = 1.0f / kFftLengthBy2;
   std::transform(y.begin(), y.end(), tmp.begin() + kFftLengthBy2, e->begin(),
                  [&](float a, float b) { return a - b * kScale; });

   if (s) {
     for (size_t k = 0; k < s->size(); ++k) {
       (*s)[k] = kScale * tmp[k + kFftLengthBy2];
     }
   }
 }

 void ScaleFilterOutput(rtc::ArrayView<const float> y,
                        float factor,
                        rtc::ArrayView<float> e,
                        rtc::ArrayView<float> s) {
   RTC_DCHECK_EQ(y.size(), e.size());
   RTC_DCHECK_EQ(y.size(), s.size());
   for (size_t k = 0; k < y.size(); ++k) {
     s[k] *= factor;
     e[k] = y[k] - s[k];
   }
 }

 }  // namespace

 Subtractor::Subtractor(const EchoCanceller3Config& config,
                        size_t num_render_channels,
                        size_t num_capture_channels,
                        ApmDataDumper* data_dumper,
                        Aec3Optimization optimization)
     : fft_(),
       data_dumper_(data_dumper),
       optimization_(optimization),
       config_(config),
       num_capture_channels_(num_capture_channels),
       main_filters_(num_capture_channels_),
       shadow_filter_(num_capture_channels_),
       main_gains_(num_capture_channels_),
       shadow_gains_(num_capture_channels_),
       filter_misadjustment_estimators_(num_capture_channels_),
       poor_shadow_filter_counters_(num_capture_channels_, 0),
       main_frequency_responses_(
           num_capture_channels_,
           std::vector<std::array<float, kFftLengthBy2Plus1>>(
               std::max(config_.filter.main_initial.length_blocks,
                        config_.filter.main.length_blocks),
               std::array<float, kFftLengthBy2Plus1>())),
       main_impulse_responses_(
           num_capture_channels_,
           std::vector<float>(GetTimeDomainLength(std::max(
                                  config_.filter.main_initial.length_blocks,
                                  config_.filter.main.length_blocks)),
                              0.f)) {
   for (size_t ch = 0; ch < num_capture_channels_; ++ch) {
     main_filters_[ch] = std::make_unique<AdaptiveFirFilter>(
         config_.filter.main.length_blocks,
         config_.filter.main_initial.length_blocks,
         config.filter.config_change_duration_blocks, num_render_channels,
         optimization, data_dumper_);

     shadow_filter_[ch] = std::make_unique<AdaptiveFirFilter>(
         config_.filter.shadow.length_blocks,
         config_.filter.shadow_initial.length_blocks,
         config.filter.config_change_duration_blocks, num_render_channels,
         optimization, data_dumper_);
     main_gains_[ch] = std::make_unique<MainFilterUpdateGain>(
         config_.filter.main_initial,
         config_.filter.config_change_duration_blocks);
     shadow_gains_[ch] = std::make_unique<ShadowFilterUpdateGain>(
         config_.filter.shadow_initial,
         config.filter.config_change_duration_blocks);
   }

   RTC_DCHECK(data_dumper_);
   for (size_t ch = 0; ch < num_capture_channels_; ++ch) {
     for (auto& H2_k : main_frequency_responses_[ch]) {
       H2_k.fill(0.f);
     }
   }
 }

 Subtractor::~Subtractor() = default;

 void Subtractor::HandleEchoPathChange(
     const EchoPathVariability& echo_path_variability) {
   const auto full_reset = [&]() {
     for (size_t ch = 0; ch < num_capture_channels_; ++ch) {
       main_filters_[ch]->HandleEchoPathChange();
       shadow_filter_[ch]->HandleEchoPathChange();
       main_gains_[ch]->HandleEchoPathChange(echo_path_variability);
       shadow_gains_[ch]->HandleEchoPathChange();
       main_gains_[ch]->SetConfig(config_.filter.main_initial, true);
       shadow_gains_[ch]->SetConfig(config_.filter.shadow_initial, true);
       main_filters_[ch]->SetSizePartitions(
           config_.filter.main_initial.length_blocks, true);
       shadow_filter_[ch]->SetSizePartitions(
           config_.filter.shadow_initial.length_blocks, true);
     }
   };

   if (echo_path_variability.delay_change !=
       EchoPathVariability::DelayAdjustment::kNone) {
     full_reset();
   }

   if (echo_path_variability.gain_change) {
     for (size_t ch = 0; ch < num_capture_channels_; ++ch) {
       main_gains_[ch]->HandleEchoPathChange(echo_path_variability);
     }
   }
 }

 void Subtractor::ExitInitialState() {
   for (size_t ch = 0; ch < num_capture_channels_; ++ch) {
     main_gains_[ch]->SetConfig(config_.filter.main, false);
     shadow_gains_[ch]->SetConfig(config_.filter.shadow, false);
     main_filters_[ch]->SetSizePartitions(config_.filter.main.length_blocks,
                                          false);
     shadow_filter_[ch]->SetSizePartitions(config_.filter.shadow.length_blocks,
                                           false);
   }
 }

 void Subtractor::Process(const RenderBuffer& render_buffer,
                          const std::vector<std::vector<float>>& capture,
                          const RenderSignalAnalyzer& render_signal_analyzer,
                          const AecState& aec_state,
                          rtc::ArrayView<SubtractorOutput> outputs) {
   RTC_DCHECK_EQ(num_capture_channels_, capture.size());

   // Compute the render powers.
   const bool same_filter_sizes =
       main_filters_[0]->SizePartitions() == shadow_filter_[0]->SizePartitions();
   std::array<float, kFftLengthBy2Plus1> X2_main;
   std::array<float, kFftLengthBy2Plus1> X2_shadow_data;
   auto& X2_shadow = same_filter_sizes ? X2_main : X2_shadow_data;
   if (same_filter_sizes) {
     render_buffer.SpectralSum(main_filters_[0]->SizePartitions(), &X2_main);
   } else if (main_filters_[0]->SizePartitions() >
              shadow_filter_[0]->SizePartitions()) {
     render_buffer.SpectralSums(shadow_filter_[0]->SizePartitions(),
                                main_filters_[0]->SizePartitions(), &X2_shadow,
                                &X2_main);
   } else {
     render_buffer.SpectralSums(main_filters_[0]->SizePartitions(),
                                shadow_filter_[0]->SizePartitions(), &X2_main,
                                &X2_shadow);
   }

   // Process all capture channels
   for (size_t ch = 0; ch < num_capture_channels_; ++ch) {
     RTC_DCHECK_EQ(kBlockSize, capture[ch].size());
     SubtractorOutput& output = outputs[ch];
     rtc::ArrayView<const float> y = capture[ch];
     FftData& E_main = output.E_main;
     FftData E_shadow;
     std::array<float, kBlockSize>& e_main = output.e_main;
     std::array<float, kBlockSize>& e_shadow = output.e_shadow;

     FftData S;
     FftData& G = S;

     // Form the outputs of the main and shadow filters.
     main_filters_[ch]->Filter(render_buffer, &S);
     PredictionError(fft_, S, y, &e_main, &output.s_main);

     shadow_filter_[ch]->Filter(render_buffer, &S);
     PredictionError(fft_, S, y, &e_shadow, &output.s_shadow);

     // Compute the signal powers in the subtractor output.
     output.ComputeMetrics(y);

     // Adjust the filter if needed.
     bool main_filters_adjusted = false;
     filter_misadjustment_estimators_[ch].Update(output);
     if (filter_misadjustment_estimators_[ch].IsAdjustmentNeeded()) {
       float scale = filter_misadjustment_estimators_[ch].GetMisadjustment();
       main_filters_[ch]->ScaleFilter(scale);
       for (auto& h_k : main_impulse_responses_[ch]) {
         h_k *= scale;
       }
       ScaleFilterOutput(y, scale, e_main, output.s_main);
       filter_misadjustment_estimators_[ch].Reset();
       main_filters_adjusted = true;
     }

     // Compute the FFts of the main and shadow filter outputs.
     fft_.ZeroPaddedFft(e_main, Aec3Fft::Window::kHanning, &E_main);
     fft_.ZeroPaddedFft(e_shadow, Aec3Fft::Window::kHanning, &E_shadow);

     // Compute spectra for future use.
     E_shadow.Spectrum(optimization_, output.E2_shadow);
     E_main.Spectrum(optimization_, output.E2_main);

     // Update the main filter.
     if (!main_filters_adjusted) {
       std::array<float, kFftLengthBy2Plus1> erl;
       ComputeErl(optimization_, main_frequency_responses_[ch], erl);
       main_gains_[ch]->Compute(X2_main, render_signal_analyzer, output, erl,
                                main_filters_[ch]->SizePartitions(),
                                aec_state.SaturatedCapture(), &G);
     } else {
       G.re.fill(0.f);
       G.im.fill(0.f);
     }
     main_filters_[ch]->Adapt(render_buffer, G, &main_impulse_responses_[ch]);
     main_filters_[ch]->ComputeFrequencyResponse(&main_frequency_responses_[ch]);

     if (ch == 0) {
       data_dumper_->DumpRaw("aec3_subtractor_G_main", G.re);
       data_dumper_->DumpRaw("aec3_subtractor_G_main", G.im);
     }

     // Update the shadow filter.
     poor_shadow_filter_counters_[ch] =
         output.e2_main < output.e2_shadow ? poor_shadow_filter_counters_[ch] + 1
                                           : 0;
     if (poor_shadow_filter_counters_[ch] < 5) {
       shadow_gains_[ch]->Compute(X2_shadow, render_signal_analyzer, E_shadow,
                                  shadow_filter_[ch]->SizePartitions(),
                                  aec_state.SaturatedCapture(), &G);
     } else {
       poor_shadow_filter_counters_[ch] = 0;
       shadow_filter_[ch]->SetFilter(main_filters_[ch]->SizePartitions(),
                                     main_filters_[ch]->GetFilter());
       shadow_gains_[ch]->Compute(X2_shadow, render_signal_analyzer, E_main,
                                  shadow_filter_[ch]->SizePartitions(),
                                  aec_state.SaturatedCapture(), &G);
     }

     shadow_filter_[ch]->Adapt(render_buffer, G);
     if (ch == 0) {
       data_dumper_->DumpRaw("aec3_subtractor_G_shadow", G.re);
       data_dumper_->DumpRaw("aec3_subtractor_G_shadow", G.im);
       filter_misadjustment_estimators_[ch].Dump(data_dumper_);
       DumpFilters();
     }

     std::for_each(e_main.begin(), e_main.end(),
                   [](float& a) { a = rtc::SafeClamp(a, -32768.f, 32767.f); });

     if (ch == 0) {
       data_dumper_->DumpWav("aec3_main_filters_output", kBlockSize, &e_main[0],
                             16000, 1);
       data_dumper_->DumpWav("aec3_shadow_filter_output", kBlockSize,
                             &e_shadow[0], 16000, 1);
     }
   }
 }

 void Subtractor::FilterMisadjustmentEstimator::Update(
     const SubtractorOutput& output) {
   e2_acum_ += output.e2_main;
   y2_acum_ += output.y2;
   if (++n_blocks_acum_ == n_blocks_) {
     if (y2_acum_ > n_blocks_ * 200.f * 200.f * kBlockSize) {
       float update = (e2_acum_ / y2_acum_);
       if (e2_acum_ > n_blocks_ * 7500.f * 7500.f * kBlockSize) {
         // Duration equal to blockSizeMs * n_blocks_ * 4.
         overhang_ = 4;
       } else {
         overhang_ = std::max(overhang_ - 1, 0);
       }

       if ((update < inv_misadjustment_) || (overhang_ > 0)) {
         inv_misadjustment_ += 0.1f * (update - inv_misadjustment_);
       }
     }
     e2_acum_ = 0.f;
     y2_acum_ = 0.f;
     n_blocks_acum_ = 0;
   }
 }

 void Subtractor::FilterMisadjustmentEstimator::Reset() {
   e2_acum_ = 0.f;
   y2_acum_ = 0.f;
   n_blocks_acum_ = 0;
   inv_misadjustment_ = 0.f;
   overhang_ = 0.f;
 }

 void Subtractor::FilterMisadjustmentEstimator::Dump(
     ApmDataDumper* data_dumper) const {
   data_dumper->DumpRaw("aec3_inv_misadjustment_factor", inv_misadjustment_);
 }

 }  // namespace webrtc
	/*
	* Copyright (c) 2017 The WebRTC project authors. All Rights Reserved.
	*
	* Use of this source code is governed by a BSD-style license
	* that can be found in the LICENSE file in the root of the source
	* tree. An additional intellectual property rights grant can be found
	* in the file PATENTS. All contributing project authors may
	* be found in the AUTHORS file in the root of the source tree.
	*/

	#include "modules/audio_processing/aec3/subtractor.h"

	#include <algorithm>
	#include <utility>

	#include "api/array_view.h"
	#include "modules/audio_processing/aec3/adaptive_fir_filter_erl.h"
	#include "modules/audio_processing/aec3/fft_data.h"
	#include "modules/audio_processing/logging/apm_data_dumper.h"
	#include "rtc_base/checks.h"
	#include "rtc_base/numerics/safe_minmax.h"

	namespace webrtc {

	namespace {

	void PredictionError(const Aec3Fft& fft,
	const FftData& S,
	rtc::ArrayView<const float> y,
	std::array<float, kBlockSize>* e,
	std::array<float, kBlockSize>* s) {
	std::array<float, kFftLength> tmp;
	fft.Ifft(S, &tmp);
	constexpr float kScale = 1.0f / kFftLengthBy2;
	std::transform(y.begin(), y.end(), tmp.begin() + kFftLengthBy2, e->begin(),
	[&](float a, float b) { return a - b * kScale; });

	if (s) {
	for (size_t k = 0; k < s->size(); ++k) {
	(s)[k] = kScale tmp[k + kFftLengthBy2];
	}
	}
	}

	void ScaleFilterOutput(rtc::ArrayView<const float> y,
	float factor,
	rtc::ArrayView<float> e,
	rtc::ArrayView<float> s) {
	RTC_DCHECK_EQ(y.size(), e.size());
	RTC_DCHECK_EQ(y.size(), s.size());
	for (size_t k = 0; k < y.size(); ++k) {
	s[k] *= factor;
	e[k] = y[k] - s[k];
	}
	}

	} // namespace

	Subtractor::Subtractor(const EchoCanceller3Config& config,
	size_t num_render_channels,
	size_t num_capture_channels,
	ApmDataDumper* data_dumper,
	Aec3Optimization optimization)
	: fft_(),
	data_dumper_(data_dumper),
	optimization_(optimization),
	config_(config),
	num_capture_channels_(num_capture_channels),
	main_filters_(num_capture_channels_),
	shadow_filter_(num_capture_channels_),
	main_gains_(num_capture_channels_),
	shadow_gains_(num_capture_channels_),
	filter_misadjustment_estimators_(num_capture_channels_),
	poor_shadow_filter_counters_(num_capture_channels_, 0),
	main_frequency_responses_(
	num_capture_channels_,
	std::vector<std::array<float, kFftLengthBy2Plus1>>(
	std::max(config_.filter.main_initial.length_blocks,
	config_.filter.main.length_blocks),
	std::array<float, kFftLengthBy2Plus1>())),
	main_impulse_responses_(
	num_capture_channels_,
	std::vector<float>(GetTimeDomainLength(std::max(
	config_.filter.main_initial.length_blocks,
	config_.filter.main.length_blocks)),
	0.f)) {
	for (size_t ch = 0; ch < num_capture_channels_; ++ch) {
	main_filters_[ch] = std::make_unique<AdaptiveFirFilter>(
	config_.filter.main.length_blocks,
	config_.filter.main_initial.length_blocks,
	config.filter.config_change_duration_blocks, num_render_channels,
	optimization, data_dumper_);

	shadow_filter_[ch] = std::make_unique<AdaptiveFirFilter>(
	config_.filter.shadow.length_blocks,
	config_.filter.shadow_initial.length_blocks,
	config.filter.config_change_duration_blocks, num_render_channels,
	optimization, data_dumper_);
	main_gains_[ch] = std::make_unique<MainFilterUpdateGain>(
	config_.filter.main_initial,
	config_.filter.config_change_duration_blocks);
	shadow_gains_[ch] = std::make_unique<ShadowFilterUpdateGain>(
	config_.filter.shadow_initial,
	config.filter.config_change_duration_blocks);
	}

	RTC_DCHECK(data_dumper_);
	for (size_t ch = 0; ch < num_capture_channels_; ++ch) {
	for (auto& H2_k : main_frequency_responses_[ch]) {
	H2_k.fill(0.f);
	}
	}
	}

	Subtractor::~Subtractor() = default;

	void Subtractor::HandleEchoPathChange(
	const EchoPathVariability& echo_path_variability) {
	const auto full_reset = [&]() {
	for (size_t ch = 0; ch < num_capture_channels_; ++ch) {
	main_filters_[ch]->HandleEchoPathChange();
	shadow_filter_[ch]->HandleEchoPathChange();
	main_gains_[ch]->HandleEchoPathChange(echo_path_variability);
	shadow_gains_[ch]->HandleEchoPathChange();
	main_gains_[ch]->SetConfig(config_.filter.main_initial, true);
	shadow_gains_[ch]->SetConfig(config_.filter.shadow_initial, true);
	main_filters_[ch]->SetSizePartitions(
	config_.filter.main_initial.length_blocks, true);
	shadow_filter_[ch]->SetSizePartitions(
	config_.filter.shadow_initial.length_blocks, true);
	}
	};

	if (echo_path_variability.delay_change !=
	EchoPathVariability::DelayAdjustment::kNone) {
	full_reset();
	}

	if (echo_path_variability.gain_change) {
	for (size_t ch = 0; ch < num_capture_channels_; ++ch) {
	main_gains_[ch]->HandleEchoPathChange(echo_path_variability);
	}
	}
	}

	void Subtractor::ExitInitialState() {
	for (size_t ch = 0; ch < num_capture_channels_; ++ch) {
	main_gains_[ch]->SetConfig(config_.filter.main, false);
	shadow_gains_[ch]->SetConfig(config_.filter.shadow, false);
	main_filters_[ch]->SetSizePartitions(config_.filter.main.length_blocks,
	false);
	shadow_filter_[ch]->SetSizePartitions(config_.filter.shadow.length_blocks,
	false);
	}
	}

	void Subtractor::Process(const RenderBuffer& render_buffer,
	const std::vector<std::vector<float>>& capture,
	const RenderSignalAnalyzer& render_signal_analyzer,
	const AecState& aec_state,
	rtc::ArrayView<SubtractorOutput> outputs) {
	RTC_DCHECK_EQ(num_capture_channels_, capture.size());

	// Compute the render powers.
	const bool same_filter_sizes =
	main_filters_[0]->SizePartitions() == shadow_filter_[0]->SizePartitions();
	std::array<float, kFftLengthBy2Plus1> X2_main;
	std::array<float, kFftLengthBy2Plus1> X2_shadow_data;
	auto& X2_shadow = same_filter_sizes ? X2_main : X2_shadow_data;
	if (same_filter_sizes) {
	render_buffer.SpectralSum(main_filters_[0]->SizePartitions(), &X2_main);
	} else if (main_filters_[0]->SizePartitions() >
	shadow_filter_[0]->SizePartitions()) {
	render_buffer.SpectralSums(shadow_filter_[0]->SizePartitions(),
	main_filters_[0]->SizePartitions(), &X2_shadow,
	&X2_main);
	} else {
	render_buffer.SpectralSums(main_filters_[0]->SizePartitions(),
	shadow_filter_[0]->SizePartitions(), &X2_main,
	&X2_shadow);
	}

	// Process all capture channels
	for (size_t ch = 0; ch < num_capture_channels_; ++ch) {
	RTC_DCHECK_EQ(kBlockSize, capture[ch].size());
	SubtractorOutput& output = outputs[ch];
	rtc::ArrayView<const float> y = capture[ch];
	FftData& E_main = output.E_main;
	FftData E_shadow;
	std::array<float, kBlockSize>& e_main = output.e_main;
	std::array<float, kBlockSize>& e_shadow = output.e_shadow;

	FftData S;
	FftData& G = S;

	// Form the outputs of the main and shadow filters.
	main_filters_[ch]->Filter(render_buffer, &S);
	PredictionError(fft_, S, y, &e_main, &output.s_main);

	shadow_filter_[ch]->Filter(render_buffer, &S);
	PredictionError(fft_, S, y, &e_shadow, &output.s_shadow);

	// Compute the signal powers in the subtractor output.
	output.ComputeMetrics(y);

	// Adjust the filter if needed.
	bool main_filters_adjusted = false;
	filter_misadjustment_estimators_[ch].Update(output);
	if (filter_misadjustment_estimators_[ch].IsAdjustmentNeeded()) {
	float scale = filter_misadjustment_estimators_[ch].GetMisadjustment();
	main_filters_[ch]->ScaleFilter(scale);
	for (auto& h_k : main_impulse_responses_[ch]) {
	h_k *= scale;
	}
	ScaleFilterOutput(y, scale, e_main, output.s_main);
	filter_misadjustment_estimators_[ch].Reset();
	main_filters_adjusted = true;
	}

	// Compute the FFts of the main and shadow filter outputs.
	fft_.ZeroPaddedFft(e_main, Aec3Fft::Window::kHanning, &E_main);
	fft_.ZeroPaddedFft(e_shadow, Aec3Fft::Window::kHanning, &E_shadow);

	// Compute spectra for future use.
	E_shadow.Spectrum(optimization_, output.E2_shadow);
	E_main.Spectrum(optimization_, output.E2_main);

	// Update the main filter.
	if (!main_filters_adjusted) {
	std::array<float, kFftLengthBy2Plus1> erl;
	ComputeErl(optimization_, main_frequency_responses_[ch], erl);
	main_gains_[ch]->Compute(X2_main, render_signal_analyzer, output, erl,
	main_filters_[ch]->SizePartitions(),
	aec_state.SaturatedCapture(), &G);
	} else {
	G.re.fill(0.f);
	G.im.fill(0.f);
	}
	main_filters_[ch]->Adapt(render_buffer, G, &main_impulse_responses_[ch]);
	main_filters_[ch]->ComputeFrequencyResponse(&main_frequency_responses_[ch]);

	if (ch == 0) {
	data_dumper_->DumpRaw("aec3_subtractor_G_main", G.re);
	data_dumper_->DumpRaw("aec3_subtractor_G_main", G.im);
	}

	// Update the shadow filter.
	poor_shadow_filter_counters_[ch] =
	output.e2_main < output.e2_shadow ? poor_shadow_filter_counters_[ch] + 1
	: 0;
	if (poor_shadow_filter_counters_[ch] < 5) {
	shadow_gains_[ch]->Compute(X2_shadow, render_signal_analyzer, E_shadow,
	shadow_filter_[ch]->SizePartitions(),
	aec_state.SaturatedCapture(), &G);
	} else {
	poor_shadow_filter_counters_[ch] = 0;
	shadow_filter_[ch]->SetFilter(main_filters_[ch]->SizePartitions(),
	main_filters_[ch]->GetFilter());
	shadow_gains_[ch]->Compute(X2_shadow, render_signal_analyzer, E_main,
	shadow_filter_[ch]->SizePartitions(),
	aec_state.SaturatedCapture(), &G);
	}

	shadow_filter_[ch]->Adapt(render_buffer, G);
	if (ch == 0) {
	data_dumper_->DumpRaw("aec3_subtractor_G_shadow", G.re);
	data_dumper_->DumpRaw("aec3_subtractor_G_shadow", G.im);
	filter_misadjustment_estimators_[ch].Dump(data_dumper_);
	DumpFilters();
	}

	std::for_each(e_main.begin(), e_main.end(),
	[](float& a) { a = rtc::SafeClamp(a, -32768.f, 32767.f); });

	if (ch == 0) {
	data_dumper_->DumpWav("aec3_main_filters_output", kBlockSize, &e_main[0],
	16000, 1);
	data_dumper_->DumpWav("aec3_shadow_filter_output", kBlockSize,
	&e_shadow[0], 16000, 1);
	}
	}
	}

	void Subtractor::FilterMisadjustmentEstimator::Update(
	const SubtractorOutput& output) {
	e2_acum_ += output.e2_main;
	y2_acum_ += output.y2;
	if (++n_blocks_acum_ == n_blocks_) {
	if (y2_acum_ > n_blocks_ * 200.f * 200.f * kBlockSize) {
	float update = (e2_acum_ / y2_acum_);
	if (e2_acum_ > n_blocks_ * 7500.f * 7500.f * kBlockSize) {
	// Duration equal to blockSizeMs * n_blocks_ * 4.
	overhang_ = 4;
	} else {
	overhang_ = std::max(overhang_ - 1, 0);
	}

	if ((update < inv_misadjustment_) \|\| (overhang_ > 0)) {
	inv_misadjustment_ += 0.1f * (update - inv_misadjustment_);
	}
	}
	e2_acum_ = 0.f;
	y2_acum_ = 0.f;
	n_blocks_acum_ = 0;
	}
	}

	void Subtractor::FilterMisadjustmentEstimator::Reset() {
	e2_acum_ = 0.f;
	y2_acum_ = 0.f;
	n_blocks_acum_ = 0;
	inv_misadjustment_ = 0.f;
	overhang_ = 0.f;
	}

	void Subtractor::FilterMisadjustmentEstimator::Dump(
	ApmDataDumper* data_dumper) const {
	data_dumper->DumpRaw("aec3_inv_misadjustment_factor", inv_misadjustment_);
	}

	} // namespace webrtc