blob: 4590f856bed2f5893386bfebe5802299f3778721 [file] [log] [blame]
/*
* 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 <stddef.h>
#include <algorithm>
#include <cmath>
#include <numeric>
#include "rtc_base/checks.h"
#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.FullBandErleLog2());
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 * std::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