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webrtc/modules/audio_processing/aec3/echo_remover_metrics.cc
Jesús de Vicente Peña 496cedfe56 AEC3: Reverberation model: Changes on the decay estimation. 
In this CL we have introduced changes on the estimation of the decay involved in the exponential modeling of the reverberation. Specifically, the instantaneous ERLE has been tracked and used for adapting faster in the regions when the linear filter is performing well. Furthermore, the adaptation is just perform during render activity.


Change-Id: I974fd60e4e1a40a879660efaa24457ed940f77b4
Bug: webrtc:9479
Reviewed-on: https://webrtc-review.googlesource.com/86680
Reviewed-by: Gustaf Ullberg <gustaf@webrtc.org>
Commit-Queue: Jesus de Vicente Pena <devicentepena@webrtc.org>
Cr-Commit-Position: refs/heads/master@{#23836}
2018-07-04 10:04:32 +00:00

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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/echo_remover_metrics.h"
#include <math.h>
#include <algorithm>
#include <numeric>
#include "rtc_base/numerics/safe_minmax.h"
#include "system_wrappers/include/metrics.h"
namespace webrtc {
namespace {
constexpr float kOneByMetricsCollectionBlocks = 1.f / kMetricsCollectionBlocks;
} // namespace
EchoRemoverMetrics::DbMetric::DbMetric() : DbMetric(0.f, 0.f, 0.f) {}
EchoRemoverMetrics::DbMetric::DbMetric(float sum_value,
float floor_value,
float ceil_value)
: sum_value(sum_value), floor_value(floor_value), ceil_value(ceil_value) {}
void EchoRemoverMetrics::DbMetric::Update(float value) {
sum_value += value;
floor_value = std::min(floor_value, value);
ceil_value = std::max(ceil_value, value);
}
void EchoRemoverMetrics::DbMetric::UpdateInstant(float value) {
sum_value = value;
floor_value = std::min(floor_value, value);
ceil_value = std::max(ceil_value, value);
}
EchoRemoverMetrics::EchoRemoverMetrics() {
ResetMetrics();
}
void EchoRemoverMetrics::ResetMetrics() {
erl_.fill(DbMetric(0.f, 10000.f, 0.000f));
erl_time_domain_ = DbMetric(0.f, 10000.f, 0.000f);
erle_.fill(DbMetric(0.f, 0.f, 1000.f));
erle_time_domain_ = DbMetric(0.f, 0.f, 1000.f);
comfort_noise_.fill(DbMetric(0.f, 100000000.f, 0.f));
suppressor_gain_.fill(DbMetric(0.f, 1.f, 0.f));
active_render_count_ = 0;
saturated_capture_ = false;
}
void EchoRemoverMetrics::Update(
const AecState& aec_state,
const std::array<float, kFftLengthBy2Plus1>& comfort_noise_spectrum,
const std::array<float, kFftLengthBy2Plus1>& suppressor_gain) {
metrics_reported_ = false;
if (++block_counter_ <= kMetricsCollectionBlocks) {
aec3::UpdateDbMetric(aec_state.Erl(), &erl_);
erl_time_domain_.UpdateInstant(aec_state.ErlTimeDomain());
aec3::UpdateDbMetric(aec_state.Erle(), &erle_);
erle_time_domain_.UpdateInstant(aec_state.ErleTimeDomainLog2());
aec3::UpdateDbMetric(comfort_noise_spectrum, &comfort_noise_);
aec3::UpdateDbMetric(suppressor_gain, &suppressor_gain_);
active_render_count_ += (aec_state.ActiveRender() ? 1 : 0);
saturated_capture_ = saturated_capture_ || aec_state.SaturatedCapture();
} else {
// Report the metrics over several frames in order to lower the impact of
// the logarithms involved on the computational complexity.
constexpr int kMetricsCollectionBlocksBy2 = kMetricsCollectionBlocks / 2;
constexpr float kComfortNoiseScaling = 1.f / (kBlockSize * kBlockSize);
switch (block_counter_) {
case kMetricsCollectionBlocks + 1:
RTC_HISTOGRAM_COUNTS_LINEAR(
"WebRTC.Audio.EchoCanceller.ErleBand0.Average",
aec3::TransformDbMetricForReporting(true, 0.f, 19.f, 0.f,
kOneByMetricsCollectionBlocks,
erle_[0].sum_value),
0, 19, 20);
RTC_HISTOGRAM_COUNTS_LINEAR(
"WebRTC.Audio.EchoCanceller.ErleBand0.Max",
aec3::TransformDbMetricForReporting(true, 0.f, 19.f, 0.f, 1.f,
erle_[0].ceil_value),
0, 19, 20);
RTC_HISTOGRAM_COUNTS_LINEAR(
"WebRTC.Audio.EchoCanceller.ErleBand0.Min",
aec3::TransformDbMetricForReporting(true, 0.f, 19.f, 0.f, 1.f,
erle_[0].floor_value),
0, 19, 20);
break;
case kMetricsCollectionBlocks + 2:
RTC_HISTOGRAM_COUNTS_LINEAR(
"WebRTC.Audio.EchoCanceller.ErleBand1.Average",
aec3::TransformDbMetricForReporting(true, 0.f, 19.f, 0.f,
kOneByMetricsCollectionBlocks,
erle_[1].sum_value),
0, 19, 20);
RTC_HISTOGRAM_COUNTS_LINEAR(
"WebRTC.Audio.EchoCanceller.ErleBand1.Max",
aec3::TransformDbMetricForReporting(true, 0.f, 19.f, 0.f, 1.f,
erle_[1].ceil_value),
0, 19, 20);
RTC_HISTOGRAM_COUNTS_LINEAR(
"WebRTC.Audio.EchoCanceller.ErleBand1.Min",
aec3::TransformDbMetricForReporting(true, 0.f, 19.f, 0.f, 1.f,
erle_[1].floor_value),
0, 19, 20);
break;
case kMetricsCollectionBlocks + 3:
RTC_HISTOGRAM_COUNTS_LINEAR(
"WebRTC.Audio.EchoCanceller.ErlBand0.Average",
aec3::TransformDbMetricForReporting(true, 0.f, 59.f, 30.f,
kOneByMetricsCollectionBlocks,
erl_[0].sum_value),
0, 59, 30);
RTC_HISTOGRAM_COUNTS_LINEAR(
"WebRTC.Audio.EchoCanceller.ErlBand0.Max",
aec3::TransformDbMetricForReporting(true, 0.f, 59.f, 30.f, 1.f,
erl_[0].ceil_value),
0, 59, 30);
RTC_HISTOGRAM_COUNTS_LINEAR(
"WebRTC.Audio.EchoCanceller.ErlBand0.Min",
aec3::TransformDbMetricForReporting(true, 0.f, 59.f, 30.f, 1.f,
erl_[0].floor_value),
0, 59, 30);
break;
case kMetricsCollectionBlocks + 4:
RTC_HISTOGRAM_COUNTS_LINEAR(
"WebRTC.Audio.EchoCanceller.ErlBand1.Average",
aec3::TransformDbMetricForReporting(true, 0.f, 59.f, 30.f,
kOneByMetricsCollectionBlocks,
erl_[1].sum_value),
0, 59, 30);
RTC_HISTOGRAM_COUNTS_LINEAR(
"WebRTC.Audio.EchoCanceller.ErlBand1.Max",
aec3::TransformDbMetricForReporting(true, 0.f, 59.f, 30.f, 1.f,
erl_[1].ceil_value),
0, 59, 30);
RTC_HISTOGRAM_COUNTS_LINEAR(
"WebRTC.Audio.EchoCanceller.ErlBand1.Min",
aec3::TransformDbMetricForReporting(true, 0.f, 59.f, 30.f, 1.f,
erl_[1].floor_value),
0, 59, 30);
break;
case kMetricsCollectionBlocks + 5:
RTC_HISTOGRAM_COUNTS_LINEAR(
"WebRTC.Audio.EchoCanceller.ComfortNoiseBand0.Average",
aec3::TransformDbMetricForReporting(
true, 0.f, 89.f, -90.3f,
kComfortNoiseScaling * kOneByMetricsCollectionBlocks,
comfort_noise_[0].sum_value),
0, 89, 45);
RTC_HISTOGRAM_COUNTS_LINEAR(
"WebRTC.Audio.EchoCanceller.ComfortNoiseBand0.Max",
aec3::TransformDbMetricForReporting(true, 0.f, 89.f, -90.3f,
kComfortNoiseScaling,
comfort_noise_[0].ceil_value),
0, 89, 45);
RTC_HISTOGRAM_COUNTS_LINEAR(
"WebRTC.Audio.EchoCanceller.ComfortNoiseBand0.Min",
aec3::TransformDbMetricForReporting(true, 0.f, 89.f, -90.3f,
kComfortNoiseScaling,
comfort_noise_[0].floor_value),
0, 89, 45);
break;
case kMetricsCollectionBlocks + 6:
RTC_HISTOGRAM_COUNTS_LINEAR(
"WebRTC.Audio.EchoCanceller.ComfortNoiseBand1.Average",
aec3::TransformDbMetricForReporting(
true, 0.f, 89.f, -90.3f,
kComfortNoiseScaling * kOneByMetricsCollectionBlocks,
comfort_noise_[1].sum_value),
0, 89, 45);
RTC_HISTOGRAM_COUNTS_LINEAR(
"WebRTC.Audio.EchoCanceller.ComfortNoiseBand1.Max",
aec3::TransformDbMetricForReporting(true, 0.f, 89.f, -90.3f,
kComfortNoiseScaling,
comfort_noise_[1].ceil_value),
0, 89, 45);
RTC_HISTOGRAM_COUNTS_LINEAR(
"WebRTC.Audio.EchoCanceller.ComfortNoiseBand1.Min",
aec3::TransformDbMetricForReporting(true, 0.f, 89.f, -90.3f,
kComfortNoiseScaling,
comfort_noise_[1].floor_value),
0, 89, 45);
break;
case kMetricsCollectionBlocks + 7:
RTC_HISTOGRAM_COUNTS_LINEAR(
"WebRTC.Audio.EchoCanceller.SuppressorGainBand0.Average",
aec3::TransformDbMetricForReporting(true, 0.f, 59.f, 0.f,
kOneByMetricsCollectionBlocks,
suppressor_gain_[0].sum_value),
0, 59, 30);
RTC_HISTOGRAM_COUNTS_LINEAR(
"WebRTC.Audio.EchoCanceller.SuppressorGainBand0.Max",
aec3::TransformDbMetricForReporting(true, 0.f, 59.f, 0.f, 1.f,
suppressor_gain_[0].ceil_value),
0, 59, 30);
RTC_HISTOGRAM_COUNTS_LINEAR(
"WebRTC.Audio.EchoCanceller.SuppressorGainBand0.Min",
aec3::TransformDbMetricForReporting(
true, 0.f, 59.f, 0.f, 1.f, suppressor_gain_[0].floor_value),
0, 59, 30);
break;
case kMetricsCollectionBlocks + 8:
RTC_HISTOGRAM_COUNTS_LINEAR(
"WebRTC.Audio.EchoCanceller.SuppressorGainBand1.Average",
aec3::TransformDbMetricForReporting(true, 0.f, 59.f, 0.f,
kOneByMetricsCollectionBlocks,
suppressor_gain_[1].sum_value),
0, 59, 30);
RTC_HISTOGRAM_COUNTS_LINEAR(
"WebRTC.Audio.EchoCanceller.SuppressorGainBand1.Max",
aec3::TransformDbMetricForReporting(true, 0.f, 59.f, 0.f, 1.f,
suppressor_gain_[1].ceil_value),
0, 59, 30);
RTC_HISTOGRAM_COUNTS_LINEAR(
"WebRTC.Audio.EchoCanceller.SuppressorGainBand1.Min",
aec3::TransformDbMetricForReporting(
true, 0.f, 59.f, 0.f, 1.f, suppressor_gain_[1].floor_value),
0, 59, 30);
break;
case kMetricsCollectionBlocks + 9:
RTC_HISTOGRAM_BOOLEAN(
"WebRTC.Audio.EchoCanceller.UsableLinearEstimate",
static_cast<int>(aec_state.UsableLinearEstimate() ? 1 : 0));
RTC_HISTOGRAM_BOOLEAN(
"WebRTC.Audio.EchoCanceller.ActiveRender",
static_cast<int>(
active_render_count_ > kMetricsCollectionBlocksBy2 ? 1 : 0));
RTC_HISTOGRAM_COUNTS_LINEAR("WebRTC.Audio.EchoCanceller.FilterDelay",
aec_state.FilterDelayBlocks(), 0, 30, 31);
RTC_HISTOGRAM_BOOLEAN("WebRTC.Audio.EchoCanceller.CaptureSaturation",
static_cast<int>(saturated_capture_ ? 1 : 0));
break;
case kMetricsCollectionBlocks + 10:
RTC_HISTOGRAM_COUNTS_LINEAR(
"WebRTC.Audio.EchoCanceller.Erl.Value",
aec3::TransformDbMetricForReporting(true, 0.f, 59.f, 30.f, 1.f,
erl_time_domain_.sum_value),
0, 59, 30);
RTC_HISTOGRAM_COUNTS_LINEAR(
"WebRTC.Audio.EchoCanceller.Erl.Max",
aec3::TransformDbMetricForReporting(true, 0.f, 59.f, 30.f, 1.f,
erl_time_domain_.ceil_value),
0, 59, 30);
RTC_HISTOGRAM_COUNTS_LINEAR(
"WebRTC.Audio.EchoCanceller.Erl.Min",
aec3::TransformDbMetricForReporting(true, 0.f, 59.f, 30.f, 1.f,
erl_time_domain_.floor_value),
0, 59, 30);
break;
case kMetricsCollectionBlocks + 11:
RTC_HISTOGRAM_COUNTS_LINEAR(
"WebRTC.Audio.EchoCanceller.Erle.Value",
aec3::TransformDbMetricForReporting(false, 0.f, 19.f, 0.f, 1.f,
erle_time_domain_.sum_value),
0, 19, 20);
RTC_HISTOGRAM_COUNTS_LINEAR(
"WebRTC.Audio.EchoCanceller.Erle.Max",
aec3::TransformDbMetricForReporting(false, 0.f, 19.f, 0.f, 1.f,
erle_time_domain_.ceil_value),
0, 19, 20);
RTC_HISTOGRAM_COUNTS_LINEAR(
"WebRTC.Audio.EchoCanceller.Erle.Min",
aec3::TransformDbMetricForReporting(false, 0.f, 19.f, 0.f, 1.f,
erle_time_domain_.floor_value),
0, 19, 20);
metrics_reported_ = true;
RTC_DCHECK_EQ(kMetricsReportingIntervalBlocks, block_counter_);
block_counter_ = 0;
ResetMetrics();
break;
default:
RTC_NOTREACHED();
break;
}
}
}
namespace aec3 {
void UpdateDbMetric(const std::array<float, kFftLengthBy2Plus1>& value,
std::array<EchoRemoverMetrics::DbMetric, 2>* statistic) {
RTC_DCHECK(statistic);
// Truncation is intended in the band width computation.
constexpr int kNumBands = 2;
constexpr int kBandWidth = 65 / kNumBands;
constexpr float kOneByBandWidth = 1.f / kBandWidth;
RTC_DCHECK_EQ(kNumBands, statistic->size());
RTC_DCHECK_EQ(65, value.size());
for (size_t k = 0; k < statistic->size(); ++k) {
float average_band =
std::accumulate(value.begin() + kBandWidth * k,
value.begin() + kBandWidth * (k + 1), 0.f) *
kOneByBandWidth;
(*statistic)[k].Update(average_band);
}
}
int TransformDbMetricForReporting(bool negate,
float min_value,
float max_value,
float offset,
float scaling,
float value) {
float new_value = 10.f * log10(value * scaling + 1e-10f) + offset;
if (negate) {
new_value = -new_value;
}
return static_cast<int>(rtc::SafeClamp(new_value, min_value, max_value));
}
} // namespace aec3
} // namespace webrtc
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