webrtc_m130/modules/audio_processing/aec3/fullband_erle_estimator.cc
Jesús de Vicente Peña 44974e143c AEC3: Adding a correction factor for the Erle estimation that depends on the portion of the filter that is currently in use.
In this CL a more precise estimation of the Erle is introduced. This is done by creating different estimators that are specialized in different regions of the linear filter. An estimation of which regions were used for generating the current echo estimate is performed and used for selecting the right Erle estimator.

Bug: webrtc:9961
Change-Id: Iba6eb24596c067c3c66d40df590be379d3e1bb7b
Reviewed-on: https://webrtc-review.googlesource.com/c/109400
Reviewed-by: Per Åhgren <peah@webrtc.org>
Commit-Queue: Jesus de Vicente Pena <devicentepena@webrtc.org>
Cr-Commit-Position: refs/heads/master@{#25707}
2018-11-20 12:28:05 +00:00

170 lines
5.4 KiB
C++

/*
* Copyright (c) 2018 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/fullband_erle_estimator.h"
#include <algorithm>
#include <memory>
#include <numeric>
#include "absl/types/optional.h"
#include "api/array_view.h"
#include "modules/audio_processing/aec3/aec3_common.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 {
constexpr float kEpsilon = 1e-3f;
constexpr float kX2BandEnergyThreshold = 44015068.0f;
constexpr int kBlocksToHoldErle = 100;
constexpr int kPointsToAccumulate = 6;
} // namespace
FullBandErleEstimator::FullBandErleEstimator(float min_erle, float max_erle_lf)
: min_erle_log2_(FastApproxLog2f(min_erle + kEpsilon)),
max_erle_lf_log2(FastApproxLog2f(max_erle_lf + kEpsilon)) {
Reset();
}
FullBandErleEstimator::~FullBandErleEstimator() = default;
void FullBandErleEstimator::Reset() {
instantaneous_erle_.Reset();
erle_time_domain_log2_ = min_erle_log2_;
hold_counter_time_domain_ = 0;
}
void FullBandErleEstimator::Update(rtc::ArrayView<const float> X2,
rtc::ArrayView<const float> Y2,
rtc::ArrayView<const float> E2,
bool converged_filter) {
if (converged_filter) {
// Computes the fullband ERLE.
const float X2_sum = std::accumulate(X2.begin(), X2.end(), 0.0f);
if (X2_sum > kX2BandEnergyThreshold * X2.size()) {
const float Y2_sum = std::accumulate(Y2.begin(), Y2.end(), 0.0f);
const float E2_sum = std::accumulate(E2.begin(), E2.end(), 0.0f);
if (instantaneous_erle_.Update(Y2_sum, E2_sum)) {
hold_counter_time_domain_ = kBlocksToHoldErle;
erle_time_domain_log2_ +=
0.1f * ((instantaneous_erle_.GetInstErleLog2().value()) -
erle_time_domain_log2_);
erle_time_domain_log2_ = rtc::SafeClamp(
erle_time_domain_log2_, min_erle_log2_, max_erle_lf_log2);
}
}
}
--hold_counter_time_domain_;
if (hold_counter_time_domain_ <= 0) {
erle_time_domain_log2_ =
std::max(min_erle_log2_, erle_time_domain_log2_ - 0.044f);
}
if (hold_counter_time_domain_ == 0) {
instantaneous_erle_.ResetAccumulators();
}
}
void FullBandErleEstimator::Dump(
const std::unique_ptr<ApmDataDumper>& data_dumper) const {
data_dumper->DumpRaw("aec3_fullband_erle_log2", FullbandErleLog2());
instantaneous_erle_.Dump(data_dumper);
}
FullBandErleEstimator::ErleInstantaneous::ErleInstantaneous() {
Reset();
}
FullBandErleEstimator::ErleInstantaneous::~ErleInstantaneous() = default;
bool FullBandErleEstimator::ErleInstantaneous::Update(const float Y2_sum,
const float E2_sum) {
bool update_estimates = false;
E2_acum_ += E2_sum;
Y2_acum_ += Y2_sum;
num_points_++;
if (num_points_ == kPointsToAccumulate) {
if (E2_acum_ > 0.f) {
update_estimates = true;
erle_log2_ = FastApproxLog2f(Y2_acum_ / E2_acum_ + kEpsilon);
}
num_points_ = 0;
E2_acum_ = 0.f;
Y2_acum_ = 0.f;
}
if (update_estimates) {
UpdateMaxMin();
UpdateQualityEstimate();
}
return update_estimates;
}
void FullBandErleEstimator::ErleInstantaneous::Reset() {
ResetAccumulators();
max_erle_log2_ = -10.f; // -30 dB.
min_erle_log2_ = 33.f; // 100 dB.
inst_quality_estimate_ = 0.f;
}
void FullBandErleEstimator::ErleInstantaneous::ResetAccumulators() {
erle_log2_ = absl::nullopt;
inst_quality_estimate_ = 0.f;
num_points_ = 0;
E2_acum_ = 0.f;
Y2_acum_ = 0.f;
}
void FullBandErleEstimator::ErleInstantaneous::Dump(
const std::unique_ptr<ApmDataDumper>& data_dumper) const {
data_dumper->DumpRaw("aec3_fullband_erle_inst_log2",
erle_log2_ ? *erle_log2_ : -10.f);
data_dumper->DumpRaw(
"aec3_erle_instantaneous_quality",
GetQualityEstimate() ? GetQualityEstimate().value() : 0.f);
data_dumper->DumpRaw("aec3_fullband_erle_max_log2", max_erle_log2_);
data_dumper->DumpRaw("aec3_fullband_erle_min_log2", min_erle_log2_);
}
void FullBandErleEstimator::ErleInstantaneous::UpdateMaxMin() {
RTC_DCHECK(erle_log2_);
if (erle_log2_.value() > max_erle_log2_) {
max_erle_log2_ = erle_log2_.value();
} else {
max_erle_log2_ -= 0.0004; // Forget factor, approx 1dB every 3 sec.
}
if (erle_log2_.value() < min_erle_log2_) {
min_erle_log2_ = erle_log2_.value();
} else {
min_erle_log2_ += 0.0004; // Forget factor, approx 1dB every 3 sec.
}
}
void FullBandErleEstimator::ErleInstantaneous::UpdateQualityEstimate() {
const float alpha = 0.07f;
float quality_estimate = 0.f;
RTC_DCHECK(erle_log2_);
if (max_erle_log2_ > min_erle_log2_) {
quality_estimate = (erle_log2_.value() - min_erle_log2_) /
(max_erle_log2_ - min_erle_log2_);
}
if (quality_estimate > inst_quality_estimate_) {
inst_quality_estimate_ = quality_estimate;
} else {
inst_quality_estimate_ +=
alpha * (quality_estimate - inst_quality_estimate_);
}
}
} // namespace webrtc