4896aaa9e4
Although the algorithm should generate the optimal gains, these limits are in place so that it doesn't go bananas in extreme noise situations or if there are some errors on the noise estimate. The limits were chosen as the extreme values from recordings with -3dB SNR, which is the minimum where the POLQA metric increases when processed. Review-Url: https://codereview.webrtc.org/1925933002 Cr-Commit-Position: refs/heads/master@{#12550}
70 lines
2.1 KiB
C++
70 lines
2.1 KiB
C++
/*
|
|
* Copyright (c) 2014 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.
|
|
*/
|
|
|
|
#include "webrtc/modules/audio_processing/intelligibility/intelligibility_utils.h"
|
|
|
|
#include <math.h>
|
|
#include <stdlib.h>
|
|
#include <string.h>
|
|
#include <algorithm>
|
|
#include <limits>
|
|
|
|
namespace webrtc {
|
|
|
|
namespace intelligibility {
|
|
|
|
namespace {
|
|
|
|
const float kMinFactor = 0.01f;
|
|
const float kMaxFactor = 1000.f;
|
|
|
|
// Return |current| changed towards |target|, with the relative change being at
|
|
// most |limit|.
|
|
float UpdateFactor(float target, float current, float limit) {
|
|
float gain = target / (current + std::numeric_limits<float>::epsilon());
|
|
gain = std::min(std::max(gain, 1.f - limit), 1.f + limit);
|
|
return std::min(std::max(current * gain, kMinFactor), kMaxFactor);;
|
|
}
|
|
|
|
} // namespace
|
|
|
|
template<typename T>
|
|
PowerEstimator<T>::PowerEstimator(size_t num_freqs, float decay)
|
|
: power_(num_freqs, 0.f), decay_(decay) {}
|
|
|
|
template<typename T>
|
|
void PowerEstimator<T>::Step(const T* data) {
|
|
for (size_t i = 0; i < power_.size(); ++i) {
|
|
power_[i] = decay_ * power_[i] +
|
|
(1.f - decay_) * std::abs(data[i]) * std::abs(data[i]);
|
|
}
|
|
}
|
|
|
|
template class PowerEstimator<float>;
|
|
template class PowerEstimator<std::complex<float>>;
|
|
|
|
GainApplier::GainApplier(size_t freqs, float relative_change_limit)
|
|
: num_freqs_(freqs),
|
|
relative_change_limit_(relative_change_limit),
|
|
target_(freqs, 1.f),
|
|
current_(freqs, 1.f) {}
|
|
|
|
void GainApplier::Apply(const std::complex<float>* in_block,
|
|
std::complex<float>* out_block) {
|
|
for (size_t i = 0; i < num_freqs_; ++i) {
|
|
current_[i] = UpdateFactor(target_[i], current_[i], relative_change_limit_);
|
|
out_block[i] = sqrtf(fabsf(current_[i])) * in_block[i];
|
|
}
|
|
}
|
|
|
|
} // namespace intelligibility
|
|
|
|
} // namespace webrtc
|