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/*
* 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"
#include "system_wrappers/include/field_trial.h"
namespace webrtc {
namespace {
bool UseCoarseFilterResetHangover() {
return !field_trial::IsEnabled(
"WebRTC-Aec3CoarseFilterResetHangoverKillSwitch");
}
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),
use_coarse_filter_reset_hangover_(UseCoarseFilterResetHangover()),
refined_filters_(num_capture_channels_),
coarse_filter_(num_capture_channels_),
refined_gains_(num_capture_channels_),
coarse_gains_(num_capture_channels_),
filter_misadjustment_estimators_(num_capture_channels_),
poor_coarse_filter_counters_(num_capture_channels_, 0),
coarse_filter_reset_hangover_(num_capture_channels_, 0),
refined_frequency_responses_(
num_capture_channels_,
std::vector<std::array<float, kFftLengthBy2Plus1>>(
std::max(config_.filter.refined_initial.length_blocks,
config_.filter.refined.length_blocks),
std::array<float, kFftLengthBy2Plus1>())),
refined_impulse_responses_(
num_capture_channels_,
std::vector<float>(GetTimeDomainLength(std::max(
config_.filter.refined_initial.length_blocks,
config_.filter.refined.length_blocks)),
0.f)),
coarse_impulse_responses_(0) {
// Set up the storing of coarse impulse responses if data dumping is
// available.
if (ApmDataDumper::IsAvailable()) {
coarse_impulse_responses_.resize(num_capture_channels_);
const size_t filter_size = GetTimeDomainLength(
std::max(config_.filter.coarse_initial.length_blocks,
config_.filter.coarse.length_blocks));
for (std::vector<float>& impulse_response : coarse_impulse_responses_) {
impulse_response.resize(filter_size, 0.f);
}
}
for (size_t ch = 0; ch < num_capture_channels_; ++ch) {
refined_filters_[ch] = std::make_unique<AdaptiveFirFilter>(
config_.filter.refined.length_blocks,
config_.filter.refined_initial.length_blocks,
config.filter.config_change_duration_blocks, num_render_channels,
optimization, data_dumper_);
coarse_filter_[ch] = std::make_unique<AdaptiveFirFilter>(
config_.filter.coarse.length_blocks,
config_.filter.coarse_initial.length_blocks,
config.filter.config_change_duration_blocks, num_render_channels,
optimization, data_dumper_);
refined_gains_[ch] = std::make_unique<RefinedFilterUpdateGain>(
config_.filter.refined_initial,
config_.filter.config_change_duration_blocks);
coarse_gains_[ch] = std::make_unique<CoarseFilterUpdateGain>(
config_.filter.coarse_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 : refined_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) {
refined_filters_[ch]->HandleEchoPathChange();
coarse_filter_[ch]->HandleEchoPathChange();
refined_gains_[ch]->HandleEchoPathChange(echo_path_variability);
coarse_gains_[ch]->HandleEchoPathChange();
refined_gains_[ch]->SetConfig(config_.filter.refined_initial, true);
coarse_gains_[ch]->SetConfig(config_.filter.coarse_initial, true);
refined_filters_[ch]->SetSizePartitions(
config_.filter.refined_initial.length_blocks, true);
coarse_filter_[ch]->SetSizePartitions(
config_.filter.coarse_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) {
refined_gains_[ch]->HandleEchoPathChange(echo_path_variability);
}
}
}
void Subtractor::ExitInitialState() {
for (size_t ch = 0; ch < num_capture_channels_; ++ch) {
refined_gains_[ch]->SetConfig(config_.filter.refined, false);
coarse_gains_[ch]->SetConfig(config_.filter.coarse, false);
refined_filters_[ch]->SetSizePartitions(
config_.filter.refined.length_blocks, false);
coarse_filter_[ch]->SetSizePartitions(config_.filter.coarse.length_blocks,
false);
}
}
void Subtractor::Process(const RenderBuffer& render_buffer,
const Block& capture,
const RenderSignalAnalyzer& render_signal_analyzer,
const AecState& aec_state,
rtc::ArrayView<SubtractorOutput> outputs) {
RTC_DCHECK_EQ(num_capture_channels_, capture.NumChannels());
// Compute the render powers.
const bool same_filter_sizes = refined_filters_[0]->SizePartitions() ==
coarse_filter_[0]->SizePartitions();
std::array<float, kFftLengthBy2Plus1> X2_refined;
std::array<float, kFftLengthBy2Plus1> X2_coarse_data;
auto& X2_coarse = same_filter_sizes ? X2_refined : X2_coarse_data;
if (same_filter_sizes) {
render_buffer.SpectralSum(refined_filters_[0]->SizePartitions(),
&X2_refined);
} else if (refined_filters_[0]->SizePartitions() >
coarse_filter_[0]->SizePartitions()) {
render_buffer.SpectralSums(coarse_filter_[0]->SizePartitions(),
refined_filters_[0]->SizePartitions(),
&X2_coarse, &X2_refined);
} else {
render_buffer.SpectralSums(refined_filters_[0]->SizePartitions(),
coarse_filter_[0]->SizePartitions(), &X2_refined,
&X2_coarse);
}
// Process all capture channels
for (size_t ch = 0; ch < num_capture_channels_; ++ch) {
SubtractorOutput& output = outputs[ch];
rtc::ArrayView<const float> y = capture.View(/*band=*/0, ch);
FftData& E_refined = output.E_refined;
FftData E_coarse;
std::array<float, kBlockSize>& e_refined = output.e_refined;
std::array<float, kBlockSize>& e_coarse = output.e_coarse;
FftData S;
FftData& G = S;
// Form the outputs of the refined and coarse filters.
refined_filters_[ch]->Filter(render_buffer, &S);
PredictionError(fft_, S, y, &e_refined, &output.s_refined);
coarse_filter_[ch]->Filter(render_buffer, &S);
PredictionError(fft_, S, y, &e_coarse, &output.s_coarse);
// Compute the signal powers in the subtractor output.
output.ComputeMetrics(y);
// Adjust the filter if needed.
bool refined_filters_adjusted = false;
filter_misadjustment_estimators_[ch].Update(output);
if (filter_misadjustment_estimators_[ch].IsAdjustmentNeeded()) {
float scale = filter_misadjustment_estimators_[ch].GetMisadjustment();
refined_filters_[ch]->ScaleFilter(scale);
for (auto& h_k : refined_impulse_responses_[ch]) {
h_k *= scale;
}
ScaleFilterOutput(y, scale, e_refined, output.s_refined);
filter_misadjustment_estimators_[ch].Reset();
refined_filters_adjusted = true;
}
// Compute the FFts of the refined and coarse filter outputs.
fft_.ZeroPaddedFft(e_refined, Aec3Fft::Window::kHanning, &E_refined);
fft_.ZeroPaddedFft(e_coarse, Aec3Fft::Window::kHanning, &E_coarse);
// Compute spectra for future use.
E_coarse.Spectrum(optimization_, output.E2_coarse);
E_refined.Spectrum(optimization_, output.E2_refined);
// Update the refined filter.
if (!refined_filters_adjusted) {
// Do not allow the performance of the coarse filter to affect the
// adaptation speed of the refined filter just after the coarse filter has
// been reset.
const bool disallow_leakage_diverged =
coarse_filter_reset_hangover_[ch] > 0 &&
use_coarse_filter_reset_hangover_;
std::array<float, kFftLengthBy2Plus1> erl;
ComputeErl(optimization_, refined_frequency_responses_[ch], erl);
refined_gains_[ch]->Compute(X2_refined, render_signal_analyzer, output,
erl, refined_filters_[ch]->SizePartitions(),
aec_state.SaturatedCapture(),
disallow_leakage_diverged, &G);
} else {
G.re.fill(0.f);
G.im.fill(0.f);
}
refined_filters_[ch]->Adapt(render_buffer, G,
&refined_impulse_responses_[ch]);
refined_filters_[ch]->ComputeFrequencyResponse(
&refined_frequency_responses_[ch]);
if (ch == 0) {
data_dumper_->DumpRaw("aec3_subtractor_G_refined", G.re);
data_dumper_->DumpRaw("aec3_subtractor_G_refined", G.im);
}
// Update the coarse filter.
poor_coarse_filter_counters_[ch] =
output.e2_refined < output.e2_coarse
? poor_coarse_filter_counters_[ch] + 1
: 0;
if (poor_coarse_filter_counters_[ch] < 5) {
coarse_gains_[ch]->Compute(X2_coarse, render_signal_analyzer, E_coarse,
coarse_filter_[ch]->SizePartitions(),
aec_state.SaturatedCapture(), &G);
coarse_filter_reset_hangover_[ch] =
std::max(coarse_filter_reset_hangover_[ch] - 1, 0);
} else {
poor_coarse_filter_counters_[ch] = 0;
coarse_filter_[ch]->SetFilter(refined_filters_[ch]->SizePartitions(),
refined_filters_[ch]->GetFilter());
coarse_gains_[ch]->Compute(X2_coarse, render_signal_analyzer, E_refined,
coarse_filter_[ch]->SizePartitions(),
aec_state.SaturatedCapture(), &G);
coarse_filter_reset_hangover_[ch] =
config_.filter.coarse_reset_hangover_blocks;
}
if (ApmDataDumper::IsAvailable()) {
RTC_DCHECK_LT(ch, coarse_impulse_responses_.size());
coarse_filter_[ch]->Adapt(render_buffer, G,
&coarse_impulse_responses_[ch]);
} else {
coarse_filter_[ch]->Adapt(render_buffer, G);
}
if (ch == 0) {
data_dumper_->DumpRaw("aec3_subtractor_G_coarse", G.re);
data_dumper_->DumpRaw("aec3_subtractor_G_coarse", G.im);
filter_misadjustment_estimators_[ch].Dump(data_dumper_);
DumpFilters();
}
std::for_each(e_refined.begin(), e_refined.end(),
[](float& a) { a = rtc::SafeClamp(a, -32768.f, 32767.f); });
if (ch == 0) {
data_dumper_->DumpWav("aec3_refined_filters_output", kBlockSize,
&e_refined[0], 16000, 1);
data_dumper_->DumpWav("aec3_coarse_filter_output", kBlockSize,
&e_coarse[0], 16000, 1);
}
}
}
void Subtractor::FilterMisadjustmentEstimator::Update(
const SubtractorOutput& output) {
e2_acum_ += output.e2_refined;
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