mirror of
https://github.com/danog/libtgvoip.git
synced 2024-12-13 09:37:21 +01:00
5caaaafa42
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.
194 lines
7.2 KiB
C++
194 lines
7.2 KiB
C++
/*
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* Copyright (c) 2018 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/agc2/interpolated_gain_curve.h"
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#include <algorithm>
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#include <iterator>
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#include "modules/audio_processing/agc2/agc2_common.h"
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#include "modules/audio_processing/logging/apm_data_dumper.h"
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#include "rtc_base/checks.h"
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namespace webrtc {
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constexpr std::array<float, kInterpolatedGainCurveTotalPoints>
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InterpolatedGainCurve::approximation_params_x_;
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constexpr std::array<float, kInterpolatedGainCurveTotalPoints>
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InterpolatedGainCurve::approximation_params_m_;
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constexpr std::array<float, kInterpolatedGainCurveTotalPoints>
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InterpolatedGainCurve::approximation_params_q_;
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InterpolatedGainCurve::InterpolatedGainCurve(ApmDataDumper* apm_data_dumper,
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std::string histogram_name_prefix)
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: region_logger_("WebRTC.Audio." + histogram_name_prefix +
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".FixedDigitalGainCurveRegion.Identity",
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"WebRTC.Audio." + histogram_name_prefix +
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".FixedDigitalGainCurveRegion.Knee",
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"WebRTC.Audio." + histogram_name_prefix +
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".FixedDigitalGainCurveRegion.Limiter",
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"WebRTC.Audio." + histogram_name_prefix +
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".FixedDigitalGainCurveRegion.Saturation"),
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apm_data_dumper_(apm_data_dumper) {}
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InterpolatedGainCurve::~InterpolatedGainCurve() {
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if (stats_.available) {
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RTC_DCHECK(apm_data_dumper_);
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apm_data_dumper_->DumpRaw("agc2_interp_gain_curve_lookups_identity",
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stats_.look_ups_identity_region);
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apm_data_dumper_->DumpRaw("agc2_interp_gain_curve_lookups_knee",
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stats_.look_ups_knee_region);
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apm_data_dumper_->DumpRaw("agc2_interp_gain_curve_lookups_limiter",
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stats_.look_ups_limiter_region);
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apm_data_dumper_->DumpRaw("agc2_interp_gain_curve_lookups_saturation",
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stats_.look_ups_saturation_region);
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region_logger_.LogRegionStats(stats_);
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}
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}
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InterpolatedGainCurve::RegionLogger::RegionLogger(
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std::string identity_histogram_name,
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std::string knee_histogram_name,
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std::string limiter_histogram_name,
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std::string saturation_histogram_name)
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: identity_histogram(
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metrics::HistogramFactoryGetCounts(identity_histogram_name,
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1,
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10000,
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50)),
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knee_histogram(metrics::HistogramFactoryGetCounts(knee_histogram_name,
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1,
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10000,
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50)),
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limiter_histogram(
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metrics::HistogramFactoryGetCounts(limiter_histogram_name,
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1,
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10000,
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50)),
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saturation_histogram(
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metrics::HistogramFactoryGetCounts(saturation_histogram_name,
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1,
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10000,
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50)) {}
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InterpolatedGainCurve::RegionLogger::~RegionLogger() = default;
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void InterpolatedGainCurve::RegionLogger::LogRegionStats(
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const InterpolatedGainCurve::Stats& stats) const {
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using Region = InterpolatedGainCurve::GainCurveRegion;
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const int duration_s =
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stats.region_duration_frames / (1000 / kFrameDurationMs);
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switch (stats.region) {
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case Region::kIdentity: {
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if (identity_histogram) {
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metrics::HistogramAdd(identity_histogram, duration_s);
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}
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break;
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}
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case Region::kKnee: {
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if (knee_histogram) {
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metrics::HistogramAdd(knee_histogram, duration_s);
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}
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break;
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}
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case Region::kLimiter: {
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if (limiter_histogram) {
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metrics::HistogramAdd(limiter_histogram, duration_s);
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}
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break;
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}
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case Region::kSaturation: {
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if (saturation_histogram) {
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metrics::HistogramAdd(saturation_histogram, duration_s);
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}
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break;
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}
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default: { RTC_NOTREACHED(); }
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}
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}
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void InterpolatedGainCurve::UpdateStats(float input_level) const {
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stats_.available = true;
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GainCurveRegion region;
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if (input_level < approximation_params_x_[0]) {
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stats_.look_ups_identity_region++;
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region = GainCurveRegion::kIdentity;
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} else if (input_level <
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approximation_params_x_[kInterpolatedGainCurveKneePoints - 1]) {
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stats_.look_ups_knee_region++;
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region = GainCurveRegion::kKnee;
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} else if (input_level < kMaxInputLevelLinear) {
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stats_.look_ups_limiter_region++;
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region = GainCurveRegion::kLimiter;
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} else {
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stats_.look_ups_saturation_region++;
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region = GainCurveRegion::kSaturation;
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}
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if (region == stats_.region) {
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++stats_.region_duration_frames;
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} else {
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region_logger_.LogRegionStats(stats_);
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stats_.region_duration_frames = 0;
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stats_.region = region;
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}
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}
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// Looks up a gain to apply given a non-negative input level.
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// The cost of this operation depends on the region in which |input_level|
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// falls.
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// For the identity and the saturation regions the cost is O(1).
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// For the other regions, namely knee and limiter, the cost is
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// O(2 + log2(|LightkInterpolatedGainCurveTotalPoints|), plus O(1) for the
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// linear interpolation (one product and one sum).
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float InterpolatedGainCurve::LookUpGainToApply(float input_level) const {
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UpdateStats(input_level);
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if (input_level <= approximation_params_x_[0]) {
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// Identity region.
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return 1.0f;
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}
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if (input_level >= kMaxInputLevelLinear) {
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// Saturating lower bound. The saturing samples exactly hit the clipping
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// level. This method achieves has the lowest harmonic distorsion, but it
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// may reduce the amplitude of the non-saturating samples too much.
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return 32768.f / input_level;
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}
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// Knee and limiter regions; find the linear piece index. Spelling
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// out the complete type was the only way to silence both the clang
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// plugin and the windows compilers.
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std::array<float, kInterpolatedGainCurveTotalPoints>::const_iterator it =
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std::lower_bound(approximation_params_x_.begin(),
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approximation_params_x_.end(), input_level);
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const size_t index = std::distance(approximation_params_x_.begin(), it) - 1;
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RTC_DCHECK_LE(0, index);
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RTC_DCHECK_LT(index, approximation_params_m_.size());
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RTC_DCHECK_LE(approximation_params_x_[index], input_level);
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if (index < approximation_params_m_.size() - 1) {
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RTC_DCHECK_LE(input_level, approximation_params_x_[index + 1]);
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}
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// Piece-wise linear interploation.
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const float gain = approximation_params_m_[index] * input_level +
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approximation_params_q_[index];
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RTC_DCHECK_LE(0.f, gain);
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return gain;
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}
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} // namespace webrtc
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