1
0
mirror of https://github.com/danog/libtgvoip.git synced 2024-12-03 10:07:45 +01:00
libtgvoip/webrtc_dsp/modules/audio_processing/aec3/echo_remover_metrics.cc
Grishka 5caaaafa42 Updated WebRTC APM
I'm now using the entire audio processing module from WebRTC as opposed to individual DSP algorithms pulled from there before. Seems to work better this way.
2018-11-23 04:02:53 +03:00

327 lines
14 KiB
C++

/*
* 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 <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 * 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