mirror of
https://github.com/danog/libtgvoip.git
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327 lines
14 KiB
C++
327 lines
14 KiB
C++
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/*
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* Copyright (c) 2017 The WebRTC project authors. All Rights Reserved.
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*
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* Use of this source code is governed by a BSD-style license
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* that can be found in the LICENSE file in the root of the source
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* tree. An additional intellectual property rights grant can be found
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* in the file PATENTS. All contributing project authors may
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* be found in the AUTHORS file in the root of the source tree.
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*/
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#include "modules/audio_processing/aec3/echo_remover_metrics.h"
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#include <math.h>
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#include <stddef.h>
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#include <algorithm>
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#include <numeric>
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#include "rtc_base/checks.h"
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#include "rtc_base/numerics/safe_minmax.h"
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#include "system_wrappers/include/metrics.h"
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namespace webrtc {
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namespace {
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constexpr float kOneByMetricsCollectionBlocks = 1.f / kMetricsCollectionBlocks;
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} // namespace
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EchoRemoverMetrics::DbMetric::DbMetric() : DbMetric(0.f, 0.f, 0.f) {}
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EchoRemoverMetrics::DbMetric::DbMetric(float sum_value,
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float floor_value,
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float ceil_value)
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: sum_value(sum_value), floor_value(floor_value), ceil_value(ceil_value) {}
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void EchoRemoverMetrics::DbMetric::Update(float value) {
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sum_value += value;
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floor_value = std::min(floor_value, value);
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ceil_value = std::max(ceil_value, value);
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}
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void EchoRemoverMetrics::DbMetric::UpdateInstant(float value) {
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sum_value = value;
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floor_value = std::min(floor_value, value);
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ceil_value = std::max(ceil_value, value);
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}
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EchoRemoverMetrics::EchoRemoverMetrics() {
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ResetMetrics();
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}
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void EchoRemoverMetrics::ResetMetrics() {
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erl_.fill(DbMetric(0.f, 10000.f, 0.000f));
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erl_time_domain_ = DbMetric(0.f, 10000.f, 0.000f);
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erle_.fill(DbMetric(0.f, 0.f, 1000.f));
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erle_time_domain_ = DbMetric(0.f, 0.f, 1000.f);
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comfort_noise_.fill(DbMetric(0.f, 100000000.f, 0.f));
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suppressor_gain_.fill(DbMetric(0.f, 1.f, 0.f));
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active_render_count_ = 0;
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saturated_capture_ = false;
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}
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void EchoRemoverMetrics::Update(
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const AecState& aec_state,
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const std::array<float, kFftLengthBy2Plus1>& comfort_noise_spectrum,
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const std::array<float, kFftLengthBy2Plus1>& suppressor_gain) {
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metrics_reported_ = false;
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if (++block_counter_ <= kMetricsCollectionBlocks) {
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aec3::UpdateDbMetric(aec_state.Erl(), &erl_);
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erl_time_domain_.UpdateInstant(aec_state.ErlTimeDomain());
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aec3::UpdateDbMetric(aec_state.Erle(), &erle_);
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erle_time_domain_.UpdateInstant(aec_state.FullBandErleLog2());
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aec3::UpdateDbMetric(comfort_noise_spectrum, &comfort_noise_);
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aec3::UpdateDbMetric(suppressor_gain, &suppressor_gain_);
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active_render_count_ += (aec_state.ActiveRender() ? 1 : 0);
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saturated_capture_ = saturated_capture_ || aec_state.SaturatedCapture();
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} else {
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// Report the metrics over several frames in order to lower the impact of
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// the logarithms involved on the computational complexity.
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constexpr int kMetricsCollectionBlocksBy2 = kMetricsCollectionBlocks / 2;
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constexpr float kComfortNoiseScaling = 1.f / (kBlockSize * kBlockSize);
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switch (block_counter_) {
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case kMetricsCollectionBlocks + 1:
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RTC_HISTOGRAM_COUNTS_LINEAR(
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"WebRTC.Audio.EchoCanceller.ErleBand0.Average",
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aec3::TransformDbMetricForReporting(true, 0.f, 19.f, 0.f,
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kOneByMetricsCollectionBlocks,
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erle_[0].sum_value),
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0, 19, 20);
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RTC_HISTOGRAM_COUNTS_LINEAR(
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"WebRTC.Audio.EchoCanceller.ErleBand0.Max",
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aec3::TransformDbMetricForReporting(true, 0.f, 19.f, 0.f, 1.f,
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erle_[0].ceil_value),
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0, 19, 20);
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RTC_HISTOGRAM_COUNTS_LINEAR(
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"WebRTC.Audio.EchoCanceller.ErleBand0.Min",
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aec3::TransformDbMetricForReporting(true, 0.f, 19.f, 0.f, 1.f,
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erle_[0].floor_value),
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0, 19, 20);
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break;
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case kMetricsCollectionBlocks + 2:
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RTC_HISTOGRAM_COUNTS_LINEAR(
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"WebRTC.Audio.EchoCanceller.ErleBand1.Average",
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aec3::TransformDbMetricForReporting(true, 0.f, 19.f, 0.f,
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kOneByMetricsCollectionBlocks,
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erle_[1].sum_value),
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0, 19, 20);
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RTC_HISTOGRAM_COUNTS_LINEAR(
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"WebRTC.Audio.EchoCanceller.ErleBand1.Max",
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aec3::TransformDbMetricForReporting(true, 0.f, 19.f, 0.f, 1.f,
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erle_[1].ceil_value),
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0, 19, 20);
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RTC_HISTOGRAM_COUNTS_LINEAR(
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"WebRTC.Audio.EchoCanceller.ErleBand1.Min",
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aec3::TransformDbMetricForReporting(true, 0.f, 19.f, 0.f, 1.f,
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erle_[1].floor_value),
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0, 19, 20);
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break;
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case kMetricsCollectionBlocks + 3:
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RTC_HISTOGRAM_COUNTS_LINEAR(
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"WebRTC.Audio.EchoCanceller.ErlBand0.Average",
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aec3::TransformDbMetricForReporting(true, 0.f, 59.f, 30.f,
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kOneByMetricsCollectionBlocks,
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erl_[0].sum_value),
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0, 59, 30);
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RTC_HISTOGRAM_COUNTS_LINEAR(
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"WebRTC.Audio.EchoCanceller.ErlBand0.Max",
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aec3::TransformDbMetricForReporting(true, 0.f, 59.f, 30.f, 1.f,
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erl_[0].ceil_value),
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0, 59, 30);
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RTC_HISTOGRAM_COUNTS_LINEAR(
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"WebRTC.Audio.EchoCanceller.ErlBand0.Min",
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aec3::TransformDbMetricForReporting(true, 0.f, 59.f, 30.f, 1.f,
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erl_[0].floor_value),
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0, 59, 30);
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break;
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case kMetricsCollectionBlocks + 4:
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RTC_HISTOGRAM_COUNTS_LINEAR(
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"WebRTC.Audio.EchoCanceller.ErlBand1.Average",
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aec3::TransformDbMetricForReporting(true, 0.f, 59.f, 30.f,
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kOneByMetricsCollectionBlocks,
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erl_[1].sum_value),
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0, 59, 30);
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RTC_HISTOGRAM_COUNTS_LINEAR(
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"WebRTC.Audio.EchoCanceller.ErlBand1.Max",
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aec3::TransformDbMetricForReporting(true, 0.f, 59.f, 30.f, 1.f,
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erl_[1].ceil_value),
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0, 59, 30);
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RTC_HISTOGRAM_COUNTS_LINEAR(
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"WebRTC.Audio.EchoCanceller.ErlBand1.Min",
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aec3::TransformDbMetricForReporting(true, 0.f, 59.f, 30.f, 1.f,
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erl_[1].floor_value),
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0, 59, 30);
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break;
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case kMetricsCollectionBlocks + 5:
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RTC_HISTOGRAM_COUNTS_LINEAR(
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"WebRTC.Audio.EchoCanceller.ComfortNoiseBand0.Average",
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aec3::TransformDbMetricForReporting(
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true, 0.f, 89.f, -90.3f,
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kComfortNoiseScaling * kOneByMetricsCollectionBlocks,
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comfort_noise_[0].sum_value),
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0, 89, 45);
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RTC_HISTOGRAM_COUNTS_LINEAR(
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"WebRTC.Audio.EchoCanceller.ComfortNoiseBand0.Max",
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aec3::TransformDbMetricForReporting(true, 0.f, 89.f, -90.3f,
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kComfortNoiseScaling,
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comfort_noise_[0].ceil_value),
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0, 89, 45);
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RTC_HISTOGRAM_COUNTS_LINEAR(
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"WebRTC.Audio.EchoCanceller.ComfortNoiseBand0.Min",
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aec3::TransformDbMetricForReporting(true, 0.f, 89.f, -90.3f,
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kComfortNoiseScaling,
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comfort_noise_[0].floor_value),
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0, 89, 45);
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break;
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case kMetricsCollectionBlocks + 6:
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RTC_HISTOGRAM_COUNTS_LINEAR(
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"WebRTC.Audio.EchoCanceller.ComfortNoiseBand1.Average",
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aec3::TransformDbMetricForReporting(
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true, 0.f, 89.f, -90.3f,
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kComfortNoiseScaling * kOneByMetricsCollectionBlocks,
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comfort_noise_[1].sum_value),
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0, 89, 45);
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RTC_HISTOGRAM_COUNTS_LINEAR(
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"WebRTC.Audio.EchoCanceller.ComfortNoiseBand1.Max",
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aec3::TransformDbMetricForReporting(true, 0.f, 89.f, -90.3f,
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kComfortNoiseScaling,
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comfort_noise_[1].ceil_value),
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0, 89, 45);
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RTC_HISTOGRAM_COUNTS_LINEAR(
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"WebRTC.Audio.EchoCanceller.ComfortNoiseBand1.Min",
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aec3::TransformDbMetricForReporting(true, 0.f, 89.f, -90.3f,
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kComfortNoiseScaling,
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comfort_noise_[1].floor_value),
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0, 89, 45);
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break;
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case kMetricsCollectionBlocks + 7:
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RTC_HISTOGRAM_COUNTS_LINEAR(
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"WebRTC.Audio.EchoCanceller.SuppressorGainBand0.Average",
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aec3::TransformDbMetricForReporting(true, 0.f, 59.f, 0.f,
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kOneByMetricsCollectionBlocks,
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suppressor_gain_[0].sum_value),
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0, 59, 30);
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RTC_HISTOGRAM_COUNTS_LINEAR(
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"WebRTC.Audio.EchoCanceller.SuppressorGainBand0.Max",
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aec3::TransformDbMetricForReporting(true, 0.f, 59.f, 0.f, 1.f,
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suppressor_gain_[0].ceil_value),
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0, 59, 30);
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RTC_HISTOGRAM_COUNTS_LINEAR(
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"WebRTC.Audio.EchoCanceller.SuppressorGainBand0.Min",
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aec3::TransformDbMetricForReporting(
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true, 0.f, 59.f, 0.f, 1.f, suppressor_gain_[0].floor_value),
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0, 59, 30);
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break;
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case kMetricsCollectionBlocks + 8:
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RTC_HISTOGRAM_COUNTS_LINEAR(
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"WebRTC.Audio.EchoCanceller.SuppressorGainBand1.Average",
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aec3::TransformDbMetricForReporting(true, 0.f, 59.f, 0.f,
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kOneByMetricsCollectionBlocks,
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suppressor_gain_[1].sum_value),
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0, 59, 30);
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RTC_HISTOGRAM_COUNTS_LINEAR(
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"WebRTC.Audio.EchoCanceller.SuppressorGainBand1.Max",
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aec3::TransformDbMetricForReporting(true, 0.f, 59.f, 0.f, 1.f,
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suppressor_gain_[1].ceil_value),
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0, 59, 30);
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RTC_HISTOGRAM_COUNTS_LINEAR(
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"WebRTC.Audio.EchoCanceller.SuppressorGainBand1.Min",
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aec3::TransformDbMetricForReporting(
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true, 0.f, 59.f, 0.f, 1.f, suppressor_gain_[1].floor_value),
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0, 59, 30);
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break;
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case kMetricsCollectionBlocks + 9:
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RTC_HISTOGRAM_BOOLEAN(
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"WebRTC.Audio.EchoCanceller.UsableLinearEstimate",
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static_cast<int>(aec_state.UsableLinearEstimate() ? 1 : 0));
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RTC_HISTOGRAM_BOOLEAN(
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"WebRTC.Audio.EchoCanceller.ActiveRender",
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static_cast<int>(
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active_render_count_ > kMetricsCollectionBlocksBy2 ? 1 : 0));
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RTC_HISTOGRAM_COUNTS_LINEAR("WebRTC.Audio.EchoCanceller.FilterDelay",
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aec_state.FilterDelayBlocks(), 0, 30, 31);
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RTC_HISTOGRAM_BOOLEAN("WebRTC.Audio.EchoCanceller.CaptureSaturation",
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static_cast<int>(saturated_capture_ ? 1 : 0));
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break;
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case kMetricsCollectionBlocks + 10:
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RTC_HISTOGRAM_COUNTS_LINEAR(
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"WebRTC.Audio.EchoCanceller.Erl.Value",
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aec3::TransformDbMetricForReporting(true, 0.f, 59.f, 30.f, 1.f,
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erl_time_domain_.sum_value),
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0, 59, 30);
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RTC_HISTOGRAM_COUNTS_LINEAR(
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"WebRTC.Audio.EchoCanceller.Erl.Max",
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aec3::TransformDbMetricForReporting(true, 0.f, 59.f, 30.f, 1.f,
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erl_time_domain_.ceil_value),
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0, 59, 30);
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RTC_HISTOGRAM_COUNTS_LINEAR(
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"WebRTC.Audio.EchoCanceller.Erl.Min",
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aec3::TransformDbMetricForReporting(true, 0.f, 59.f, 30.f, 1.f,
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erl_time_domain_.floor_value),
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0, 59, 30);
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break;
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case kMetricsCollectionBlocks + 11:
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RTC_HISTOGRAM_COUNTS_LINEAR(
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"WebRTC.Audio.EchoCanceller.Erle.Value",
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aec3::TransformDbMetricForReporting(false, 0.f, 19.f, 0.f, 1.f,
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erle_time_domain_.sum_value),
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0, 19, 20);
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RTC_HISTOGRAM_COUNTS_LINEAR(
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"WebRTC.Audio.EchoCanceller.Erle.Max",
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aec3::TransformDbMetricForReporting(false, 0.f, 19.f, 0.f, 1.f,
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erle_time_domain_.ceil_value),
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0, 19, 20);
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RTC_HISTOGRAM_COUNTS_LINEAR(
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"WebRTC.Audio.EchoCanceller.Erle.Min",
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aec3::TransformDbMetricForReporting(false, 0.f, 19.f, 0.f, 1.f,
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erle_time_domain_.floor_value),
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0, 19, 20);
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metrics_reported_ = true;
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RTC_DCHECK_EQ(kMetricsReportingIntervalBlocks, block_counter_);
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block_counter_ = 0;
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ResetMetrics();
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break;
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default:
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RTC_NOTREACHED();
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break;
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}
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}
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}
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|
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|
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namespace aec3 {
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|
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|
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|
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void UpdateDbMetric(const std::array<float, kFftLengthBy2Plus1>& value,
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|
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std::array<EchoRemoverMetrics::DbMetric, 2>* statistic) {
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RTC_DCHECK(statistic);
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// Truncation is intended in the band width computation.
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constexpr int kNumBands = 2;
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constexpr int kBandWidth = 65 / kNumBands;
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constexpr float kOneByBandWidth = 1.f / kBandWidth;
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RTC_DCHECK_EQ(kNumBands, statistic->size());
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RTC_DCHECK_EQ(65, value.size());
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for (size_t k = 0; k < statistic->size(); ++k) {
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float average_band =
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std::accumulate(value.begin() + kBandWidth * k,
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value.begin() + kBandWidth * (k + 1), 0.f) *
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kOneByBandWidth;
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(*statistic)[k].Update(average_band);
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}
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}
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int TransformDbMetricForReporting(bool negate,
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float min_value,
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|
|
float max_value,
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|
|
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));
|
||
|
|
}
|
||
|
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|
||
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} // namespace aec3
|
||
|
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||
|
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} // namespace webrtc
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