tor-browser

The Tor Browser
git clone https://git.dasho.dev/tor-browser.git
Log | Files | Refs | README | LICENSE

interpolated_gain_curve.h (6555B)


      1 /*
      2 *  Copyright (c) 2018 The WebRTC project authors. All Rights Reserved.
      3 *
      4 *  Use of this source code is governed by a BSD-style license
      5 *  that can be found in the LICENSE file in the root of the source
      6 *  tree. An additional intellectual property rights grant can be found
      7 *  in the file PATENTS.  All contributing project authors may
      8 *  be found in the AUTHORS file in the root of the source tree.
      9 */
     10 
     11 #ifndef MODULES_AUDIO_PROCESSING_AGC2_INTERPOLATED_GAIN_CURVE_H_
     12 #define MODULES_AUDIO_PROCESSING_AGC2_INTERPOLATED_GAIN_CURVE_H_
     13 
     14 #include <array>
     15 #include <cstddef>
     16 #include <cstdint>
     17 
     18 #include "absl/strings/string_view.h"
     19 #include "modules/audio_processing/agc2/agc2_common.h"
     20 #include "rtc_base/gtest_prod_util.h"
     21 #include "system_wrappers/include/metrics.h"
     22 
     23 namespace webrtc {
     24 
     25 class ApmDataDumper;
     26 
     27 constexpr float kInputLevelScalingFactor = 32768.0f;
     28 
     29 // Defined as DbfsToLinear(kLimiterMaxInputLevelDbFs)
     30 constexpr float kMaxInputLevelLinear = static_cast<float>(36766.300710566735);
     31 
     32 // Interpolated gain curve using under-approximation to avoid saturation.
     33 //
     34 // The goal of this class is allowing fast look ups to get an accurate
     35 // estimates of the gain to apply given an estimated input level.
     36 class InterpolatedGainCurve {
     37 public:
     38  enum class GainCurveRegion {
     39    kIdentity = 0,
     40    kKnee = 1,
     41    kLimiter = 2,
     42    kSaturation = 3
     43  };
     44 
     45  struct Stats {
     46    // Region in which the output level equals the input one.
     47    size_t look_ups_identity_region = 0;
     48    // Smoothing between the identity and the limiter regions.
     49    size_t look_ups_knee_region = 0;
     50    // Limiter region in which the output and input levels are linearly related.
     51    size_t look_ups_limiter_region = 0;
     52    // Region in which saturation may occur since the input level is beyond the
     53    // maximum expected by the limiter.
     54    size_t look_ups_saturation_region = 0;
     55    // True if stats have been populated.
     56    bool available = false;
     57 
     58    // The current region, and for how many frames the level has been
     59    // in that region.
     60    GainCurveRegion region = GainCurveRegion::kIdentity;
     61    int64_t region_duration_frames = 0;
     62  };
     63 
     64  InterpolatedGainCurve(ApmDataDumper* apm_data_dumper,
     65                        absl::string_view histogram_name_prefix);
     66  ~InterpolatedGainCurve();
     67 
     68  InterpolatedGainCurve(const InterpolatedGainCurve&) = delete;
     69  InterpolatedGainCurve& operator=(const InterpolatedGainCurve&) = delete;
     70 
     71  Stats get_stats() const { return stats_; }
     72 
     73  // Given a non-negative input level (linear scale), a scalar factor to apply
     74  // to a sub-frame is returned.
     75  // Levels above kLimiterMaxInputLevelDbFs will be reduced to 0 dBFS
     76  // after applying this gain
     77  float LookUpGainToApply(float input_level) const;
     78 
     79 private:
     80  // For comparing 'approximation_params_*_' with ones computed by
     81  // ComputeInterpolatedGainCurve.
     82  FRIEND_TEST_ALL_PREFIXES(GainController2InterpolatedGainCurve,
     83                           CheckApproximationParams);
     84 
     85  struct RegionLogger {
     86    metrics::Histogram* identity_histogram;
     87    metrics::Histogram* knee_histogram;
     88    metrics::Histogram* limiter_histogram;
     89    metrics::Histogram* saturation_histogram;
     90 
     91    RegionLogger(absl::string_view identity_histogram_name,
     92                 absl::string_view knee_histogram_name,
     93                 absl::string_view limiter_histogram_name,
     94                 absl::string_view saturation_histogram_name);
     95 
     96    ~RegionLogger();
     97 
     98    void LogRegionStats(const InterpolatedGainCurve::Stats& stats) const;
     99  } region_logger_;
    100 
    101  void UpdateStats(float input_level) const;
    102 
    103  ApmDataDumper* const apm_data_dumper_;
    104 
    105  static constexpr std::array<float, kInterpolatedGainCurveTotalPoints>
    106      approximation_params_x_ = {
    107          {30057.296875,    30148.986328125, 30240.67578125,  30424.052734375,
    108           30607.4296875,   30790.806640625, 30974.18359375,  31157.560546875,
    109           31340.939453125, 31524.31640625,  31707.693359375, 31891.0703125,
    110           32074.447265625, 32257.82421875,  32441.201171875, 32624.580078125,
    111           32807.95703125,  32991.33203125,  33174.7109375,   33358.08984375,
    112           33541.46484375,  33724.84375,     33819.53515625,  34009.5390625,
    113           34200.05859375,  34389.81640625,  34674.48828125,  35054.375,
    114           35434.86328125,  35814.81640625,  36195.16796875,  36575.03125}};
    115  static constexpr std::array<float, kInterpolatedGainCurveTotalPoints>
    116      approximation_params_m_ = {
    117          {-3.515235675877192989e-07, -1.050251626111275982e-06,
    118           -2.085213736791047268e-06, -3.443004743530764244e-06,
    119           -4.773849468620028347e-06, -6.077375928725814447e-06,
    120           -7.353257842623861507e-06, -8.601219633419532329e-06,
    121           -9.821013009059242904e-06, -1.101243378798244521e-05,
    122           -1.217532644659513608e-05, -1.330956911260727793e-05,
    123           -1.441507538402220234e-05, -1.549179251014720649e-05,
    124           -1.653970684856176376e-05, -1.755882840370759368e-05,
    125           -1.854918446042574942e-05, -1.951086778717581183e-05,
    126           -2.044398024736437947e-05, -2.1348627342376858e-05,
    127           -2.222496914328075945e-05, -2.265374678245279938e-05,
    128           -2.242570917587727308e-05, -2.220122041762806475e-05,
    129           -2.19802095671184361e-05,  -2.176260204578284174e-05,
    130           -2.133731686626560986e-05, -2.092481918225530535e-05,
    131           -2.052459603874012828e-05, -2.013615448959171772e-05,
    132           -1.975903069251216948e-05, -1.939277899509761482e-05}};
    133 
    134  static constexpr std::array<float, kInterpolatedGainCurveTotalPoints>
    135      approximation_params_q_ = {
    136          {1.010565876960754395, 1.031631827354431152, 1.062929749488830566,
    137           1.104239225387573242, 1.144973039627075195, 1.185109615325927734,
    138           1.224629044532775879, 1.263512492179870605, 1.301741957664489746,
    139           1.339300632476806641, 1.376173257827758789, 1.412345528602600098,
    140           1.447803974151611328, 1.482536554336547852, 1.516532182693481445,
    141           1.549780607223510742, 1.582272171974182129, 1.613999366760253906,
    142           1.644955039024353027, 1.675132393836975098, 1.704526185989379883,
    143           1.718986630439758301, 1.711274504661560059, 1.703639745712280273,
    144           1.696081161499023438, 1.688597679138183594, 1.673851132392883301,
    145           1.659391283988952637, 1.645209431648254395, 1.631297469139099121,
    146           1.617647409439086914, 1.604251742362976074}};
    147 
    148  // Stats.
    149  mutable Stats stats_;
    150 };
    151 
    152 }  // namespace webrtc
    153 
    154 #endif  // MODULES_AUDIO_PROCESSING_AGC2_INTERPOLATED_GAIN_CURVE_H_