blob: 83ded425d58bcd353af68acad13427d9bcbb76ee [file] [log] [blame]
/*
* Copyright (c) 2017 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 "modules/audio_processing/aec3/suppression_filter.h"
#include <algorithm>
#include <cmath>
#include <cstring>
#include <functional>
#include <iterator>
#include "modules/audio_processing/aec3/vector_math.h"
#include "rtc_base/checks.h"
#include "rtc_base/numerics/safe_minmax.h"
namespace webrtc {
namespace {
// Hanning window from Matlab command win = sqrt(hanning(128)).
const float kSqrtHanning[kFftLength] = {
0.00000000000000f, 0.02454122852291f, 0.04906767432742f, 0.07356456359967f,
0.09801714032956f, 0.12241067519922f, 0.14673047445536f, 0.17096188876030f,
0.19509032201613f, 0.21910124015687f, 0.24298017990326f, 0.26671275747490f,
0.29028467725446f, 0.31368174039889f, 0.33688985339222f, 0.35989503653499f,
0.38268343236509f, 0.40524131400499f, 0.42755509343028f, 0.44961132965461f,
0.47139673682600f, 0.49289819222978f, 0.51410274419322f, 0.53499761988710f,
0.55557023301960f, 0.57580819141785f, 0.59569930449243f, 0.61523159058063f,
0.63439328416365f, 0.65317284295378f, 0.67155895484702f, 0.68954054473707f,
0.70710678118655f, 0.72424708295147f, 0.74095112535496f, 0.75720884650648f,
0.77301045336274f, 0.78834642762661f, 0.80320753148064f, 0.81758481315158f,
0.83146961230255f, 0.84485356524971f, 0.85772861000027f, 0.87008699110871f,
0.88192126434835f, 0.89322430119552f, 0.90398929312344f, 0.91420975570353f,
0.92387953251129f, 0.93299279883474f, 0.94154406518302f, 0.94952818059304f,
0.95694033573221f, 0.96377606579544f, 0.97003125319454f, 0.97570213003853f,
0.98078528040323f, 0.98527764238894f, 0.98917650996478f, 0.99247953459871f,
0.99518472667220f, 0.99729045667869f, 0.99879545620517f, 0.99969881869620f,
1.00000000000000f, 0.99969881869620f, 0.99879545620517f, 0.99729045667869f,
0.99518472667220f, 0.99247953459871f, 0.98917650996478f, 0.98527764238894f,
0.98078528040323f, 0.97570213003853f, 0.97003125319454f, 0.96377606579544f,
0.95694033573221f, 0.94952818059304f, 0.94154406518302f, 0.93299279883474f,
0.92387953251129f, 0.91420975570353f, 0.90398929312344f, 0.89322430119552f,
0.88192126434835f, 0.87008699110871f, 0.85772861000027f, 0.84485356524971f,
0.83146961230255f, 0.81758481315158f, 0.80320753148064f, 0.78834642762661f,
0.77301045336274f, 0.75720884650648f, 0.74095112535496f, 0.72424708295147f,
0.70710678118655f, 0.68954054473707f, 0.67155895484702f, 0.65317284295378f,
0.63439328416365f, 0.61523159058063f, 0.59569930449243f, 0.57580819141785f,
0.55557023301960f, 0.53499761988710f, 0.51410274419322f, 0.49289819222978f,
0.47139673682600f, 0.44961132965461f, 0.42755509343028f, 0.40524131400499f,
0.38268343236509f, 0.35989503653499f, 0.33688985339222f, 0.31368174039889f,
0.29028467725446f, 0.26671275747490f, 0.24298017990326f, 0.21910124015687f,
0.19509032201613f, 0.17096188876030f, 0.14673047445536f, 0.12241067519922f,
0.09801714032956f, 0.07356456359967f, 0.04906767432742f, 0.02454122852291f};
} // namespace
SuppressionFilter::SuppressionFilter(Aec3Optimization optimization,
int sample_rate_hz,
size_t num_capture_channels)
: optimization_(optimization),
sample_rate_hz_(sample_rate_hz),
num_capture_channels_(num_capture_channels),
fft_(),
e_output_old_(NumBandsForRate(sample_rate_hz_),
std::vector<std::array<float, kFftLengthBy2>>(
num_capture_channels_)) {
RTC_DCHECK(ValidFullBandRate(sample_rate_hz_));
for (size_t b = 0; b < e_output_old_.size(); ++b) {
for (size_t ch = 0; ch < e_output_old_[b].size(); ++ch) {
e_output_old_[b][ch].fill(0.f);
}
}
}
SuppressionFilter::~SuppressionFilter() = default;
void SuppressionFilter::ApplyGain(
rtc::ArrayView<const FftData> comfort_noise,
rtc::ArrayView<const FftData> comfort_noise_high_band,
const std::array<float, kFftLengthBy2Plus1>& suppression_gain,
float high_bands_gain,
rtc::ArrayView<const FftData> E_lowest_band,
Block* e) {
RTC_DCHECK(e);
RTC_DCHECK_EQ(e->NumBands(), NumBandsForRate(sample_rate_hz_));
// Comfort noise gain is sqrt(1-g^2), where g is the suppression gain.
std::array<float, kFftLengthBy2Plus1> noise_gain;
for (size_t i = 0; i < kFftLengthBy2Plus1; ++i) {
noise_gain[i] = 1.f - suppression_gain[i] * suppression_gain[i];
}
aec3::VectorMath(optimization_).Sqrt(noise_gain);
const float high_bands_noise_scaling =
0.4f * std::sqrt(1.f - high_bands_gain * high_bands_gain);
for (size_t ch = 0; ch < num_capture_channels_; ++ch) {
FftData E;
// Analysis filterbank.
E.Assign(E_lowest_band[ch]);
for (size_t i = 0; i < kFftLengthBy2Plus1; ++i) {
// Apply suppression gains.
float E_real = E.re[i] * suppression_gain[i];
float E_imag = E.im[i] * suppression_gain[i];
// Scale and add the comfort noise.
E.re[i] = E_real + noise_gain[i] * comfort_noise[ch].re[i];
E.im[i] = E_imag + noise_gain[i] * comfort_noise[ch].im[i];
}
// Synthesis filterbank.
std::array<float, kFftLength> e_extended;
constexpr float kIfftNormalization = 2.f / kFftLength;
fft_.Ifft(E, &e_extended);
auto e0 = e->View(/*band=*/0, ch);
float* e0_old = e_output_old_[0][ch].data();
// Window and add the first half of e_extended with the second half of
// e_extended from the previous block.
for (size_t i = 0; i < kFftLengthBy2; ++i) {
float e0_i = e0_old[i] * kSqrtHanning[kFftLengthBy2 + i];
e0_i += e_extended[i] * kSqrtHanning[i];
e0[i] = e0_i * kIfftNormalization;
}
// The second half of e_extended is stored for the succeeding frame.
std::copy(e_extended.begin() + kFftLengthBy2,
e_extended.begin() + kFftLength,
std::begin(e_output_old_[0][ch]));
// Apply suppression gain to upper bands.
for (int b = 1; b < e->NumBands(); ++b) {
auto e_band = e->View(b, ch);
for (size_t i = 0; i < kFftLengthBy2; ++i) {
e_band[i] *= high_bands_gain;
}
}
// Add comfort noise to band 1.
if (e->NumBands() > 1) {
E.Assign(comfort_noise_high_band[ch]);
std::array<float, kFftLength> time_domain_high_band_noise;
fft_.Ifft(E, &time_domain_high_band_noise);
auto e1 = e->View(/*band=*/1, ch);
const float gain = high_bands_noise_scaling * kIfftNormalization;
for (size_t i = 0; i < kFftLengthBy2; ++i) {
e1[i] += time_domain_high_band_noise[i] * gain;
}
}
// Delay upper bands to match the delay of the filter bank.
for (int b = 1; b < e->NumBands(); ++b) {
auto e_band = e->View(b, ch);
float* e_band_old = e_output_old_[b][ch].data();
for (size_t i = 0; i < kFftLengthBy2; ++i) {
std::swap(e_band[i], e_band_old[i]);
}
}
// Clamp output of all bands.
for (int b = 0; b < e->NumBands(); ++b) {
auto e_band = e->View(b, ch);
for (size_t i = 0; i < kFftLengthBy2; ++i) {
e_band[i] = rtc::SafeClamp(e_band[i], -32768.f, 32767.f);
}
}
}
}
} // namespace webrtc