| /* |
| * 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 |