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libtgvoip/webrtc_dsp/modules/audio_processing/agc2/interpolated_gain_curve.h
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

154 lines
6.3 KiB
C++

/*
* Copyright (c) 2018 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.
*/
#ifndef MODULES_AUDIO_PROCESSING_AGC2_INTERPOLATED_GAIN_CURVE_H_
#define MODULES_AUDIO_PROCESSING_AGC2_INTERPOLATED_GAIN_CURVE_H_
#include <array>
#include <string>
#include "modules/audio_processing/agc2/agc2_common.h"
#include "rtc_base/constructormagic.h"
#include "rtc_base/gtest_prod_util.h"
#include "system_wrappers/include/metrics.h"
namespace webrtc {
class ApmDataDumper;
constexpr float kInputLevelScalingFactor = 32768.0f;
// Defined as DbfsToLinear(kLimiterMaxInputLevelDbFs)
constexpr float kMaxInputLevelLinear = static_cast<float>(36766.300710566735);
// Interpolated gain curve using under-approximation to avoid saturation.
//
// The goal of this class is allowing fast look ups to get an accurate
// estimates of the gain to apply given an estimated input level.
class InterpolatedGainCurve {
public:
enum class GainCurveRegion {
kIdentity = 0,
kKnee = 1,
kLimiter = 2,
kSaturation = 3
};
struct Stats {
// Region in which the output level equals the input one.
size_t look_ups_identity_region = 0;
// Smoothing between the identity and the limiter regions.
size_t look_ups_knee_region = 0;
// Limiter region in which the output and input levels are linearly related.
size_t look_ups_limiter_region = 0;
// Region in which saturation may occur since the input level is beyond the
// maximum expected by the limiter.
size_t look_ups_saturation_region = 0;
// True if stats have been populated.
bool available = false;
// The current region, and for how many frames the level has been
// in that region.
GainCurveRegion region = GainCurveRegion::kIdentity;
int64_t region_duration_frames = 0;
};
InterpolatedGainCurve(ApmDataDumper* apm_data_dumper,
std::string histogram_name_prefix);
~InterpolatedGainCurve();
Stats get_stats() const { return stats_; }
// Given a non-negative input level (linear scale), a scalar factor to apply
// to a sub-frame is returned.
// Levels above kLimiterMaxInputLevelDbFs will be reduced to 0 dBFS
// after applying this gain
float LookUpGainToApply(float input_level) const;
private:
// For comparing 'approximation_params_*_' with ones computed by
// ComputeInterpolatedGainCurve.
FRIEND_TEST_ALL_PREFIXES(AutomaticGainController2InterpolatedGainCurve,
CheckApproximationParams);
struct RegionLogger {
metrics::Histogram* identity_histogram;
metrics::Histogram* knee_histogram;
metrics::Histogram* limiter_histogram;
metrics::Histogram* saturation_histogram;
RegionLogger(std::string identity_histogram_name,
std::string knee_histogram_name,
std::string limiter_histogram_name,
std::string saturation_histogram_name);
~RegionLogger();
void LogRegionStats(const InterpolatedGainCurve::Stats& stats) const;
} region_logger_;
void UpdateStats(float input_level) const;
ApmDataDumper* const apm_data_dumper_;
static constexpr std::array<float, kInterpolatedGainCurveTotalPoints>
approximation_params_x_ = {
{30057.296875, 30148.986328125, 30240.67578125, 30424.052734375,
30607.4296875, 30790.806640625, 30974.18359375, 31157.560546875,
31340.939453125, 31524.31640625, 31707.693359375, 31891.0703125,
32074.447265625, 32257.82421875, 32441.201171875, 32624.580078125,
32807.95703125, 32991.33203125, 33174.7109375, 33358.08984375,
33541.46484375, 33724.84375, 33819.53515625, 34009.5390625,
34200.05859375, 34389.81640625, 34674.48828125, 35054.375,
35434.86328125, 35814.81640625, 36195.16796875, 36575.03125}};
static constexpr std::array<float, kInterpolatedGainCurveTotalPoints>
approximation_params_m_ = {
{-3.515235675877192989e-07, -1.050251626111275982e-06,
-2.085213736791047268e-06, -3.443004743530764244e-06,
-4.773849468620028347e-06, -6.077375928725814447e-06,
-7.353257842623861507e-06, -8.601219633419532329e-06,
-9.821013009059242904e-06, -1.101243378798244521e-05,
-1.217532644659513608e-05, -1.330956911260727793e-05,
-1.441507538402220234e-05, -1.549179251014720649e-05,
-1.653970684856176376e-05, -1.755882840370759368e-05,
-1.854918446042574942e-05, -1.951086778717581183e-05,
-2.044398024736437947e-05, -2.1348627342376858e-05,
-2.222496914328075945e-05, -2.265374678245279938e-05,
-2.242570917587727308e-05, -2.220122041762806475e-05,
-2.19802095671184361e-05, -2.176260204578284174e-05,
-2.133731686626560986e-05, -2.092481918225530535e-05,
-2.052459603874012828e-05, -2.013615448959171772e-05,
-1.975903069251216948e-05, -1.939277899509761482e-05}};
static constexpr std::array<float, kInterpolatedGainCurveTotalPoints>
approximation_params_q_ = {
{1.010565876960754395, 1.031631827354431152, 1.062929749488830566,
1.104239225387573242, 1.144973039627075195, 1.185109615325927734,
1.224629044532775879, 1.263512492179870605, 1.301741957664489746,
1.339300632476806641, 1.376173257827758789, 1.412345528602600098,
1.447803974151611328, 1.482536554336547852, 1.516532182693481445,
1.549780607223510742, 1.582272171974182129, 1.613999366760253906,
1.644955039024353027, 1.675132393836975098, 1.704526185989379883,
1.718986630439758301, 1.711274504661560059, 1.703639745712280273,
1.696081161499023438, 1.688597679138183594, 1.673851132392883301,
1.659391283988952637, 1.645209431648254395, 1.631297469139099121,
1.617647409439086914, 1.604251742362976074}};
// Stats.
mutable Stats stats_;
RTC_DISALLOW_COPY_AND_ASSIGN(InterpolatedGainCurve);
};
} // namespace webrtc
#endif // MODULES_AUDIO_PROCESSING_AGC2_INTERPOLATED_GAIN_CURVE_H_