Finalization of the first version of EchoCanceller 3

webrtc/modules/audio_processing/aec3/comfort_noise_generator.cc

+/*
+ *  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
+
+#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; });
+}
+
+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; });
+      }
+    }
+  }
+
+  // Choose N2 estimate to use.
+  const std::array<float, kFftLengthBy2Plus1>& N2 =
+      N2_initial_ ? *N2_initial_ : N2_;
+
+  if (optimization_ == Aec3Optimization::kNone) {
+    EstimateComfortNoise(N2, &seed_, lower_band_noise, upper_band_noise);
+  }
+#if defined(WEBRTC_ARCH_X86_FAMILY)
+  if (optimization_ == Aec3Optimization::kSse2) {
+    EstimateComfortNoise_SSE2(N2, &seed_, lower_band_noise, upper_band_noise);
+  }
+#endif
+}
+
+}  // namespace webrtc