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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/comfort_noise_generator.h"
#include "webrtc/typedefs.h"
#if defined(WEBRTC_ARCH_X86_FAMILY)
#include <emmintrin.h>
#endif
#include <math.h>
#include <algorithm>
#include <array>
#include <functional>
#include <numeric>
#include "webrtc/common_audio/signal_processing/include/signal_processing_library.h"
namespace webrtc {
namespace {
// Creates an array of uniformly distributed variables.
void TableRandomValue(int16_t* vector, int16_t vector_length, uint32_t* seed) {
for (int i = 0; i < vector_length; i++) {
seed[0] = (seed[0] * ((int32_t)69069) + 1) & (0x80000000 - 1);
vector[i] = (int16_t)(seed[0] >> 16);
}
}
} // namespace
namespace aec3 {
#if defined(WEBRTC_ARCH_X86_FAMILY)
void EstimateComfortNoise_SSE2(const std::array<float, kFftLengthBy2Plus1>& N2,
uint32_t* seed,
FftData* lower_band_noise,
FftData* upper_band_noise) {
FftData* N_low = lower_band_noise;
FftData* N_high = upper_band_noise;
// Compute square root spectrum.
std::array<float, kFftLengthBy2Plus1> N;
for (size_t k = 0; k < kFftLengthBy2; k += 4) {
__m128 v = _mm_loadu_ps(&N2[k]);
v = _mm_sqrt_ps(v);
_mm_storeu_ps(&N[k], v);
}
N[kFftLengthBy2] = sqrtf(N2[kFftLengthBy2]);
// Compute the noise level for the upper bands.
constexpr float kOneByNumBands = 1.f / (kFftLengthBy2Plus1 / 2 + 1);
constexpr int kFftLengthBy2Plus1By2 = kFftLengthBy2Plus1 / 2;
const float high_band_noise_level =
std::accumulate(N.begin() + kFftLengthBy2Plus1By2, N.end(), 0.f) *
kOneByNumBands;
// Generate complex noise.
std::array<int16_t, kFftLengthBy2 - 1> random_values_int;
TableRandomValue(random_values_int.data(), random_values_int.size(), seed);
std::array<float, kFftLengthBy2 - 1> sin;
std::array<float, kFftLengthBy2 - 1> cos;
constexpr float kScale = 6.28318530717959f / 32768.0f;
std::transform(random_values_int.begin(), random_values_int.end(),
sin.begin(), [&](int16_t a) { return -sinf(kScale * a); });
std::transform(random_values_int.begin(), random_values_int.end(),
cos.begin(), [&](int16_t a) { return cosf(kScale * a); });
// Form low-frequency noise via spectral shaping.
N_low->re[0] = N_low->re[kFftLengthBy2] = N_high->re[0] =
N_high->re[kFftLengthBy2] = 0.f;
std::transform(cos.begin(), cos.end(), N.begin() + 1, N_low->re.begin() + 1,
std::multiplies<float>());
std::transform(sin.begin(), sin.end(), N.begin() + 1, N_low->im.begin() + 1,
std::multiplies<float>());
// Form the high-frequency noise via simple levelling.
std::transform(cos.begin(), cos.end(), N_high->re.begin() + 1,
[&](float a) { return high_band_noise_level * a; });
std::transform(sin.begin(), sin.end(), N_high->im.begin() + 1,
[&](float a) { return high_band_noise_level * a; });
}
#endif
void EstimateComfortNoise(const std::array<float, kFftLengthBy2Plus1>& N2,
uint32_t* seed,
FftData* lower_band_noise,
FftData* upper_band_noise) {
FftData* N_low = lower_band_noise;
FftData* N_high = upper_band_noise;
// Compute square root spectrum.
std::array<float, kFftLengthBy2Plus1> N;
std::transform(N2.begin(), N2.end(), N.begin(),
[](float a) { return sqrtf(a); });
// Compute the noise level for the upper bands.
constexpr float kOneByNumBands = 1.f / (kFftLengthBy2Plus1 / 2 + 1);
constexpr int kFftLengthBy2Plus1By2 = kFftLengthBy2Plus1 / 2;
const float high_band_noise_level =
std::accumulate(N.begin() + kFftLengthBy2Plus1By2, N.end(), 0.f) *
kOneByNumBands;
// Generate complex noise.
std::array<int16_t, kFftLengthBy2 - 1> random_values_int;
TableRandomValue(random_values_int.data(), random_values_int.size(), seed);
std::array<float, kFftLengthBy2 - 1> sin;
std::array<float, kFftLengthBy2 - 1> cos;
constexpr float kScale = 6.28318530717959f / 32768.0f;
std::transform(random_values_int.begin(), random_values_int.end(),
sin.begin(), [&](int16_t a) { return -sinf(kScale * a); });
std::transform(random_values_int.begin(), random_values_int.end(),
cos.begin(), [&](int16_t a) { return cosf(kScale * a); });
// Form low-frequency noise via spectral shaping.
N_low->re[0] = N_low->re[kFftLengthBy2] = N_high->re[0] =
N_high->re[kFftLengthBy2] = 0.f;
std::transform(cos.begin(), cos.end(), N.begin() + 1, N_low->re.begin() + 1,
std::multiplies<float>());
std::transform(sin.begin(), sin.end(), N.begin() + 1, N_low->im.begin() + 1,
std::multiplies<float>());
// Form the high-frequency noise via simple levelling.
std::transform(cos.begin(), cos.end(), N_high->re.begin() + 1,
[&](float a) { return high_band_noise_level * a; });
std::transform(sin.begin(), sin.end(), N_high->im.begin() + 1,
[&](float a) { return high_band_noise_level * a; });
}
} // namespace aec3
ComfortNoiseGenerator::ComfortNoiseGenerator(Aec3Optimization optimization)
: optimization_(optimization),
seed_(42),
N2_initial_(new std::array<float, kFftLengthBy2Plus1>()) {
N2_initial_->fill(0.f);
Y2_smoothed_.fill(0.f);
N2_.fill(1.0e6f);
}
ComfortNoiseGenerator::~ComfortNoiseGenerator() = default;
void ComfortNoiseGenerator::Compute(
const AecState& aec_state,
const std::array<float, kFftLengthBy2Plus1>& capture_spectrum,
FftData* lower_band_noise,
FftData* upper_band_noise) {
RTC_DCHECK(lower_band_noise);
RTC_DCHECK(upper_band_noise);
const auto& Y2 = capture_spectrum;
if (!aec_state.SaturatedCapture()) {
// Smooth Y2.
std::transform(Y2_smoothed_.begin(), Y2_smoothed_.end(), Y2.begin(),
Y2_smoothed_.begin(),
[](float a, float b) { return a + 0.1f * (b - a); });
if (N2_counter_ > 50) {
// Update N2 from Y2_smoothed.
std::transform(N2_.begin(), N2_.end(), Y2_smoothed_.begin(), N2_.begin(),
[](float a, float b) {
return b < a ? (0.9f * b + 0.1f * a) * 1.0002f
: a * 1.0002f;
});
}
if (N2_initial_) {
if (++N2_counter_ == 1000) {
N2_initial_.reset();
} else {
// Compute the N2_initial from N2.
std::transform(
N2_.begin(), N2_.end(), N2_initial_->begin(), N2_initial_->begin(),
[](float a, float b) { return a > b ? b + 0.001f * (a - b) : a; });
}
}
}
// Limit the noise to a floor of -96 dBFS.
constexpr float kNoiseFloor = 440.f;
for (auto& n : N2_) {
n = std::max(n, kNoiseFloor);
}
if (N2_initial_) {
for (auto& n : *N2_initial_) {
n = std::max(n, kNoiseFloor);
}
}
// Choose N2 estimate to use.
const std::array<float, kFftLengthBy2Plus1>& N2 =
N2_initial_ ? *N2_initial_ : N2_;
switch (optimization_) {
#if defined(WEBRTC_ARCH_X86_FAMILY)
case Aec3Optimization::kSse2:
aec3::EstimateComfortNoise_SSE2(N2, &seed_, lower_band_noise,
upper_band_noise);
break;
#endif
default:
aec3::EstimateComfortNoise(N2, &seed_, lower_band_noise,
upper_band_noise);
}
}
} // namespace webrtc