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/*
* 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 "webrtc/modules/audio_processing/aec3/suppression_filter.h"
#include <math.h>
#include <algorithm>
#include <cstring>
#include <functional>
#include <numeric>
#include "webrtc/modules/audio_processing/utility/ooura_fft.h"
#include "webrtc/rtc_base/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(int sample_rate_hz)
: sample_rate_hz_(sample_rate_hz),
fft_(),
e_output_old_(NumBandsForRate(sample_rate_hz_)) {
RTC_DCHECK(ValidFullBandRate(sample_rate_hz_));
e_input_old_.fill(0.f);
std::for_each(e_output_old_.begin(), e_output_old_.end(),
[](std::array<float, kFftLengthBy2>& a) { a.fill(0.f); });
}
SuppressionFilter::~SuppressionFilter() = default;
void SuppressionFilter::ApplyGain(
const FftData& comfort_noise,
const FftData& comfort_noise_high_band,
const std::array<float, kFftLengthBy2Plus1>& suppression_gain,
float high_bands_gain,
std::vector<std::vector<float>>* e) {
RTC_DCHECK(e);
RTC_DCHECK_EQ(e->size(), NumBandsForRate(sample_rate_hz_));
FftData E;
std::array<float, kFftLength> e_extended;
constexpr float kIfftNormalization = 2.f / kFftLength;
// Analysis filterbank.
std::transform(e_input_old_.begin(), e_input_old_.end(),
std::begin(kSqrtHanning), e_extended.begin(),
std::multiplies<float>());
std::transform((*e)[0].begin(), (*e)[0].end(),
std::begin(kSqrtHanning) + kFftLengthBy2,
e_extended.begin() + kFftLengthBy2, std::multiplies<float>());
std::copy((*e)[0].begin(), (*e)[0].end(), e_input_old_.begin());
fft_.Fft(&e_extended, &E);
// Apply gain.
std::transform(suppression_gain.begin(), suppression_gain.end(), E.re.begin(),
E.re.begin(), std::multiplies<float>());
std::transform(suppression_gain.begin(), suppression_gain.end(), E.im.begin(),
E.im.begin(), std::multiplies<float>());
// Compute and add the comfort noise.
std::array<float, kFftLengthBy2Plus1> scaled_comfort_noise;
std::transform(suppression_gain.begin(), suppression_gain.end(),
comfort_noise.re.begin(), scaled_comfort_noise.begin(),
[](float a, float b) { return std::max(1.f - a, 0.f) * b; });
std::transform(scaled_comfort_noise.begin(), scaled_comfort_noise.end(),
E.re.begin(), E.re.begin(), std::plus<float>());
std::transform(suppression_gain.begin(), suppression_gain.end(),
comfort_noise.im.begin(), scaled_comfort_noise.begin(),
[](float a, float b) { return std::max(1.f - a, 0.f) * b; });
std::transform(scaled_comfort_noise.begin(), scaled_comfort_noise.end(),
E.im.begin(), E.im.begin(), std::plus<float>());
// Synthesis filterbank.
fft_.Ifft(E, &e_extended);
std::transform(e_output_old_[0].begin(), e_output_old_[0].end(),
std::begin(kSqrtHanning) + kFftLengthBy2, (*e)[0].begin(),
[&](float a, float b) { return kIfftNormalization * a * b; });
std::transform(e_extended.begin(), e_extended.begin() + kFftLengthBy2,
std::begin(kSqrtHanning), e_extended.begin(),
[&](float a, float b) { return kIfftNormalization * a * b; });
std::transform((*e)[0].begin(), (*e)[0].end(), e_extended.begin(),
(*e)[0].begin(), std::plus<float>());
std::for_each((*e)[0].begin(), (*e)[0].end(), [](float& x_k) {
x_k = rtc::SafeClamp(x_k, -32768.f, 32767.f);
});
std::copy(e_extended.begin() + kFftLengthBy2, e_extended.begin() + kFftLength,
std::begin(e_output_old_[0]));
if (e->size() > 1) {
// Form time-domain high-band noise.
std::array<float, kFftLength> time_domain_high_band_noise;
std::transform(comfort_noise_high_band.re.begin(),
comfort_noise_high_band.re.end(), E.re.begin(),
[&](float a) { return kIfftNormalization * a; });
std::transform(comfort_noise_high_band.im.begin(),
comfort_noise_high_band.im.end(), E.im.begin(),
[&](float a) { return kIfftNormalization * a; });
fft_.Ifft(E, &time_domain_high_band_noise);
// Scale and apply the noise to the signals.
const float high_bands_noise_scaling =
0.4f * std::max(1.f - high_bands_gain, 0.f);
std::transform(
(*e)[1].begin(), (*e)[1].end(), time_domain_high_band_noise.begin(),
(*e)[1].begin(), [&](float a, float b) {
return std::max(
std::min(b * high_bands_noise_scaling + high_bands_gain * a,
32767.0f),
-32768.0f);
});
if (e->size() > 2) {
RTC_DCHECK_EQ(3, e->size());
std::for_each((*e)[2].begin(), (*e)[2].end(), [&](float& a) {
a = rtc::SafeClamp(a * high_bands_gain, -32768.f, 32767.f);
});
}
std::array<float, kFftLengthBy2> tmp;
for (size_t k = 1; k < e->size(); ++k) {
std::copy((*e)[k].begin(), (*e)[k].end(), tmp.begin());
std::copy(e_output_old_[k].begin(), e_output_old_[k].end(),
(*e)[k].begin());
std::copy(tmp.begin(), tmp.end(), e_output_old_[k].begin());
}
}
}
} // namespace webrtc