mirror of
https://github.com/danog/libtgvoip.git
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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.
229 lines
8.0 KiB
C++
229 lines
8.0 KiB
C++
/*
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* Copyright (c) 2012 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/agc/loudness_histogram.h"
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#include <string.h>
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#include <cmath>
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#include "rtc_base/checks.h"
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namespace webrtc {
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static const double kHistBinCenters[] = {
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7.59621091765857e-02, 9.02036021061016e-02, 1.07115112009343e-01,
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1.27197217770508e-01, 1.51044347572047e-01, 1.79362373905283e-01,
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2.12989507320644e-01, 2.52921107370304e-01, 3.00339145144454e-01,
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3.56647189489147e-01, 4.23511952494003e-01, 5.02912623991786e-01,
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5.97199455365749e-01, 7.09163326739184e-01, 8.42118356728544e-01,
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1.00000000000000e+00, 1.18748153630660e+00, 1.41011239906908e+00,
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1.67448243801153e+00, 1.98841697800836e+00, 2.36120844786349e+00,
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2.80389143520905e+00, 3.32956930911896e+00, 3.95380207843188e+00,
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4.69506696634852e+00, 5.57530533426190e+00, 6.62057214370769e+00,
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7.86180718043869e+00, 9.33575086877358e+00, 1.10860317842269e+01,
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1.31644580546776e+01, 1.56325508754123e+01, 1.85633655299256e+01,
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2.20436538184971e+01, 2.61764319021997e+01, 3.10840295702492e+01,
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3.69117111886792e+01, 4.38319755100383e+01, 5.20496616180135e+01,
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6.18080121423973e+01, 7.33958732149108e+01, 8.71562442838066e+01,
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1.03496430860848e+02, 1.22900100720889e+02, 1.45941600416277e+02,
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1.73302955873365e+02, 2.05794060286978e+02, 2.44376646872353e+02,
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2.90192756065437e+02, 3.44598539797631e+02, 4.09204403447902e+02,
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4.85922673669740e+02, 5.77024203055553e+02, 6.85205587130498e+02,
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8.13668983291589e+02, 9.66216894324125e+02, 1.14736472207740e+03,
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1.36247442287647e+03, 1.61791322085579e+03, 1.92124207711260e+03,
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2.28143949334655e+03, 2.70916727454970e+03, 3.21708611729384e+03,
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3.82023036499473e+03, 4.53645302286906e+03, 5.38695420497926e+03,
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6.39690865534207e+03, 7.59621091765857e+03, 9.02036021061016e+03,
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1.07115112009343e+04, 1.27197217770508e+04, 1.51044347572047e+04,
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1.79362373905283e+04, 2.12989507320644e+04, 2.52921107370304e+04,
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3.00339145144454e+04, 3.56647189489147e+04};
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static const double kProbQDomain = 1024.0;
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// Loudness of -15 dB (smallest expected loudness) in log domain,
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// loudness_db = 13.5 * log10(rms);
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static const double kLogDomainMinBinCenter = -2.57752062648587;
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// Loudness step of 1 dB in log domain
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static const double kLogDomainStepSizeInverse = 5.81954605750359;
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static const int kTransientWidthThreshold = 7;
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static const double kLowProbabilityThreshold = 0.2;
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static const int kLowProbThresholdQ10 =
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static_cast<int>(kLowProbabilityThreshold * kProbQDomain);
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LoudnessHistogram::LoudnessHistogram()
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: num_updates_(0),
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audio_content_q10_(0),
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bin_count_q10_(),
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activity_probability_(),
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hist_bin_index_(),
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buffer_index_(0),
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buffer_is_full_(false),
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len_circular_buffer_(0),
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len_high_activity_(0) {
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static_assert(
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kHistSize == sizeof(kHistBinCenters) / sizeof(kHistBinCenters[0]),
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"histogram bin centers incorrect size");
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}
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LoudnessHistogram::LoudnessHistogram(int window_size)
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: num_updates_(0),
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audio_content_q10_(0),
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bin_count_q10_(),
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activity_probability_(new int[window_size]),
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hist_bin_index_(new int[window_size]),
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buffer_index_(0),
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buffer_is_full_(false),
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len_circular_buffer_(window_size),
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len_high_activity_(0) {}
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LoudnessHistogram::~LoudnessHistogram() {}
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void LoudnessHistogram::Update(double rms, double activity_probaility) {
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// If circular histogram is activated then remove the oldest entry.
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if (len_circular_buffer_ > 0)
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RemoveOldestEntryAndUpdate();
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// Find the corresponding bin.
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int hist_index = GetBinIndex(rms);
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// To Q10 domain.
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int prob_q10 =
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static_cast<int16_t>(floor(activity_probaility * kProbQDomain));
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InsertNewestEntryAndUpdate(prob_q10, hist_index);
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}
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// Doing nothing if buffer is not full, yet.
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void LoudnessHistogram::RemoveOldestEntryAndUpdate() {
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RTC_DCHECK_GT(len_circular_buffer_, 0);
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// Do nothing if circular buffer is not full.
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if (!buffer_is_full_)
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return;
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int oldest_prob = activity_probability_[buffer_index_];
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int oldest_hist_index = hist_bin_index_[buffer_index_];
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UpdateHist(-oldest_prob, oldest_hist_index);
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}
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void LoudnessHistogram::RemoveTransient() {
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// Don't expect to be here if high-activity region is longer than
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// |kTransientWidthThreshold| or there has not been any transient.
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RTC_DCHECK_LE(len_high_activity_, kTransientWidthThreshold);
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int index =
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(buffer_index_ > 0) ? (buffer_index_ - 1) : len_circular_buffer_ - 1;
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while (len_high_activity_ > 0) {
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UpdateHist(-activity_probability_[index], hist_bin_index_[index]);
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activity_probability_[index] = 0;
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index = (index > 0) ? (index - 1) : (len_circular_buffer_ - 1);
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len_high_activity_--;
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}
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}
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void LoudnessHistogram::InsertNewestEntryAndUpdate(int activity_prob_q10,
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int hist_index) {
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// Update the circular buffer if it is enabled.
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if (len_circular_buffer_ > 0) {
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// Removing transient.
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if (activity_prob_q10 <= kLowProbThresholdQ10) {
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// Lower than threshold probability, set it to zero.
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activity_prob_q10 = 0;
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// Check if this has been a transient.
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if (len_high_activity_ <= kTransientWidthThreshold)
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RemoveTransient(); // Remove this transient.
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len_high_activity_ = 0;
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} else if (len_high_activity_ <= kTransientWidthThreshold) {
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len_high_activity_++;
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}
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// Updating the circular buffer.
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activity_probability_[buffer_index_] = activity_prob_q10;
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hist_bin_index_[buffer_index_] = hist_index;
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// Increment the buffer index and check for wrap-around.
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buffer_index_++;
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if (buffer_index_ >= len_circular_buffer_) {
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buffer_index_ = 0;
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buffer_is_full_ = true;
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}
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}
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num_updates_++;
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if (num_updates_ < 0)
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num_updates_--;
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UpdateHist(activity_prob_q10, hist_index);
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}
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void LoudnessHistogram::UpdateHist(int activity_prob_q10, int hist_index) {
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bin_count_q10_[hist_index] += activity_prob_q10;
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audio_content_q10_ += activity_prob_q10;
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}
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double LoudnessHistogram::AudioContent() const {
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return audio_content_q10_ / kProbQDomain;
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}
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LoudnessHistogram* LoudnessHistogram::Create() {
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return new LoudnessHistogram;
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}
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LoudnessHistogram* LoudnessHistogram::Create(int window_size) {
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if (window_size < 0)
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return NULL;
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return new LoudnessHistogram(window_size);
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}
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void LoudnessHistogram::Reset() {
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// Reset the histogram, audio-content and number of updates.
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memset(bin_count_q10_, 0, sizeof(bin_count_q10_));
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audio_content_q10_ = 0;
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num_updates_ = 0;
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// Empty the circular buffer.
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buffer_index_ = 0;
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buffer_is_full_ = false;
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len_high_activity_ = 0;
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}
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int LoudnessHistogram::GetBinIndex(double rms) {
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// First exclude overload cases.
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if (rms <= kHistBinCenters[0]) {
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return 0;
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} else if (rms >= kHistBinCenters[kHistSize - 1]) {
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return kHistSize - 1;
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} else {
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// The quantizer is uniform in log domain. Alternatively we could do binary
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// search in linear domain.
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double rms_log = log(rms);
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int index = static_cast<int>(
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floor((rms_log - kLogDomainMinBinCenter) * kLogDomainStepSizeInverse));
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// The final decision is in linear domain.
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double b = 0.5 * (kHistBinCenters[index] + kHistBinCenters[index + 1]);
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if (rms > b) {
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return index + 1;
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}
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return index;
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}
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}
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double LoudnessHistogram::CurrentRms() const {
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double p;
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double mean_val = 0;
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if (audio_content_q10_ > 0) {
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double p_total_inverse = 1. / static_cast<double>(audio_content_q10_);
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for (int n = 0; n < kHistSize; n++) {
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p = static_cast<double>(bin_count_q10_[n]) * p_total_inverse;
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mean_val += p * kHistBinCenters[n];
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}
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} else {
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mean_val = kHistBinCenters[0];
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}
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return mean_val;
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}
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} // namespace webrtc
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