blob: a13764c10995ac85ba4ff559a8508ba8e723e892 [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/adaptive_fir_filter.h"
// Defines WEBRTC_ARCH_X86_FAMILY, used below.
#include <math.h>
#include <algorithm>
#include <numeric>
#include <string>
#include "rtc_base/system/arch.h"
#if defined(WEBRTC_ARCH_X86_FAMILY)
#include <emmintrin.h>
#endif
#include "modules/audio_processing/aec3/adaptive_fir_filter_erl.h"
#include "modules/audio_processing/aec3/aec3_fft.h"
#include "modules/audio_processing/aec3/aec_state.h"
#include "modules/audio_processing/aec3/coarse_filter_update_gain.h"
#include "modules/audio_processing/aec3/render_delay_buffer.h"
#include "modules/audio_processing/aec3/render_signal_analyzer.h"
#include "modules/audio_processing/logging/apm_data_dumper.h"
#include "modules/audio_processing/test/echo_canceller_test_tools.h"
#include "modules/audio_processing/utility/cascaded_biquad_filter.h"
#include "rtc_base/arraysize.h"
#include "rtc_base/numerics/safe_minmax.h"
#include "rtc_base/random.h"
#include "rtc_base/strings/string_builder.h"
#include "system_wrappers/include/cpu_features_wrapper.h"
#include "test/gtest.h"
namespace webrtc {
namespace aec3 {
namespace {
std::string ProduceDebugText(size_t num_render_channels, size_t delay) {
rtc::StringBuilder ss;
ss << "delay: " << delay << ", ";
ss << "num_render_channels:" << num_render_channels;
return ss.Release();
}
} // namespace
class AdaptiveFirFilterOneTwoFourEightRenderChannels
: public ::testing::Test,
public ::testing::WithParamInterface<size_t> {};
INSTANTIATE_TEST_SUITE_P(MultiChannel,
AdaptiveFirFilterOneTwoFourEightRenderChannels,
::testing::Values(1, 2, 4, 8));
#if defined(WEBRTC_HAS_NEON)
// Verifies that the optimized methods for filter adaptation are similar to
// their reference counterparts.
TEST_P(AdaptiveFirFilterOneTwoFourEightRenderChannels,
FilterAdaptationNeonOptimizations) {
const size_t num_render_channels = GetParam();
for (size_t num_partitions : {2, 5, 12, 30, 50}) {
constexpr int kSampleRateHz = 48000;
constexpr size_t kNumBands = NumBandsForRate(kSampleRateHz);
std::unique_ptr<RenderDelayBuffer> render_delay_buffer(
RenderDelayBuffer::Create(EchoCanceller3Config(), kSampleRateHz,
num_render_channels));
Random random_generator(42U);
Block x(kNumBands, num_render_channels);
FftData S_C;
FftData S_Neon;
FftData G;
Aec3Fft fft;
std::vector<std::vector<FftData>> H_C(
num_partitions, std::vector<FftData>(num_render_channels));
std::vector<std::vector<FftData>> H_Neon(
num_partitions, std::vector<FftData>(num_render_channels));
for (size_t p = 0; p < num_partitions; ++p) {
for (size_t ch = 0; ch < num_render_channels; ++ch) {
H_C[p][ch].Clear();
H_Neon[p][ch].Clear();
}
}
for (int k = 0; k < 30; ++k) {
for (int band = 0; band < x.NumBands(); ++band) {
for (int ch = 0; ch < x.NumChannels(); ++ch) {
RandomizeSampleVector(&random_generator, x.View(band, ch));
}
}
render_delay_buffer->Insert(x);
if (k == 0) {
render_delay_buffer->Reset();
}
render_delay_buffer->PrepareCaptureProcessing();
}
auto* const render_buffer = render_delay_buffer->GetRenderBuffer();
for (size_t j = 0; j < G.re.size(); ++j) {
G.re[j] = j / 10001.f;
}
for (size_t j = 1; j < G.im.size() - 1; ++j) {
G.im[j] = j / 20001.f;
}
G.im[0] = 0.f;
G.im[G.im.size() - 1] = 0.f;
AdaptPartitions_Neon(*render_buffer, G, num_partitions, &H_Neon);
AdaptPartitions(*render_buffer, G, num_partitions, &H_C);
AdaptPartitions_Neon(*render_buffer, G, num_partitions, &H_Neon);
AdaptPartitions(*render_buffer, G, num_partitions, &H_C);
for (size_t p = 0; p < num_partitions; ++p) {
for (size_t ch = 0; ch < num_render_channels; ++ch) {
for (size_t j = 0; j < H_C[p][ch].re.size(); ++j) {
EXPECT_FLOAT_EQ(H_C[p][ch].re[j], H_Neon[p][ch].re[j]);
EXPECT_FLOAT_EQ(H_C[p][ch].im[j], H_Neon[p][ch].im[j]);
}
}
}
ApplyFilter_Neon(*render_buffer, num_partitions, H_Neon, &S_Neon);
ApplyFilter(*render_buffer, num_partitions, H_C, &S_C);
for (size_t j = 0; j < S_C.re.size(); ++j) {
EXPECT_NEAR(S_C.re[j], S_Neon.re[j], fabs(S_C.re[j] * 0.00001f));
EXPECT_NEAR(S_C.im[j], S_Neon.im[j], fabs(S_C.re[j] * 0.00001f));
}
}
}
// Verifies that the optimized method for frequency response computation is
// bitexact to the reference counterpart.
TEST_P(AdaptiveFirFilterOneTwoFourEightRenderChannels,
ComputeFrequencyResponseNeonOptimization) {
const size_t num_render_channels = GetParam();
for (size_t num_partitions : {2, 5, 12, 30, 50}) {
std::vector<std::vector<FftData>> H(
num_partitions, std::vector<FftData>(num_render_channels));
std::vector<std::array<float, kFftLengthBy2Plus1>> H2(num_partitions);
std::vector<std::array<float, kFftLengthBy2Plus1>> H2_Neon(num_partitions);
for (size_t p = 0; p < num_partitions; ++p) {
for (size_t ch = 0; ch < num_render_channels; ++ch) {
for (size_t k = 0; k < H[p][ch].re.size(); ++k) {
H[p][ch].re[k] = k + p / 3.f + ch;
H[p][ch].im[k] = p + k / 7.f - ch;
}
}
}
ComputeFrequencyResponse(num_partitions, H, &H2);
ComputeFrequencyResponse_Neon(num_partitions, H, &H2_Neon);
for (size_t p = 0; p < num_partitions; ++p) {
for (size_t k = 0; k < H2[p].size(); ++k) {
EXPECT_FLOAT_EQ(H2[p][k], H2_Neon[p][k]);
}
}
}
}
#endif
#if defined(WEBRTC_ARCH_X86_FAMILY)
// Verifies that the optimized methods for filter adaptation are bitexact to
// their reference counterparts.
TEST_P(AdaptiveFirFilterOneTwoFourEightRenderChannels,
FilterAdaptationSse2Optimizations) {
const size_t num_render_channels = GetParam();
constexpr int kSampleRateHz = 48000;
constexpr size_t kNumBands = NumBandsForRate(kSampleRateHz);
bool use_sse2 = (GetCPUInfo(kSSE2) != 0);
if (use_sse2) {
for (size_t num_partitions : {2, 5, 12, 30, 50}) {
std::unique_ptr<RenderDelayBuffer> render_delay_buffer(
RenderDelayBuffer::Create(EchoCanceller3Config(), kSampleRateHz,
num_render_channels));
Random random_generator(42U);
Block x(kNumBands, num_render_channels);
FftData S_C;
FftData S_Sse2;
FftData G;
Aec3Fft fft;
std::vector<std::vector<FftData>> H_C(
num_partitions, std::vector<FftData>(num_render_channels));
std::vector<std::vector<FftData>> H_Sse2(
num_partitions, std::vector<FftData>(num_render_channels));
for (size_t p = 0; p < num_partitions; ++p) {
for (size_t ch = 0; ch < num_render_channels; ++ch) {
H_C[p][ch].Clear();
H_Sse2[p][ch].Clear();
}
}
for (size_t k = 0; k < 500; ++k) {
for (int band = 0; band < x.NumBands(); ++band) {
for (int ch = 0; ch < x.NumChannels(); ++ch) {
RandomizeSampleVector(&random_generator, x.View(band, ch));
}
}
render_delay_buffer->Insert(x);
if (k == 0) {
render_delay_buffer->Reset();
}
render_delay_buffer->PrepareCaptureProcessing();
auto* const render_buffer = render_delay_buffer->GetRenderBuffer();
ApplyFilter_Sse2(*render_buffer, num_partitions, H_Sse2, &S_Sse2);
ApplyFilter(*render_buffer, num_partitions, H_C, &S_C);
for (size_t j = 0; j < S_C.re.size(); ++j) {
EXPECT_FLOAT_EQ(S_C.re[j], S_Sse2.re[j]);
EXPECT_FLOAT_EQ(S_C.im[j], S_Sse2.im[j]);
}
std::for_each(G.re.begin(), G.re.end(),
[&](float& a) { a = random_generator.Rand<float>(); });
std::for_each(G.im.begin(), G.im.end(),
[&](float& a) { a = random_generator.Rand<float>(); });
AdaptPartitions_Sse2(*render_buffer, G, num_partitions, &H_Sse2);
AdaptPartitions(*render_buffer, G, num_partitions, &H_C);
for (size_t p = 0; p < num_partitions; ++p) {
for (size_t ch = 0; ch < num_render_channels; ++ch) {
for (size_t j = 0; j < H_C[p][ch].re.size(); ++j) {
EXPECT_FLOAT_EQ(H_C[p][ch].re[j], H_Sse2[p][ch].re[j]);
EXPECT_FLOAT_EQ(H_C[p][ch].im[j], H_Sse2[p][ch].im[j]);
}
}
}
}
}
}
}
// Verifies that the optimized methods for filter adaptation are bitexact to
// their reference counterparts.
TEST_P(AdaptiveFirFilterOneTwoFourEightRenderChannels,
FilterAdaptationAvx2Optimizations) {
const size_t num_render_channels = GetParam();
constexpr int kSampleRateHz = 48000;
constexpr size_t kNumBands = NumBandsForRate(kSampleRateHz);
bool use_avx2 = (GetCPUInfo(kAVX2) != 0);
if (use_avx2) {
for (size_t num_partitions : {2, 5, 12, 30, 50}) {
std::unique_ptr<RenderDelayBuffer> render_delay_buffer(
RenderDelayBuffer::Create(EchoCanceller3Config(), kSampleRateHz,
num_render_channels));
Random random_generator(42U);
Block x(kNumBands, num_render_channels);
FftData S_C;
FftData S_Avx2;
FftData G;
Aec3Fft fft;
std::vector<std::vector<FftData>> H_C(
num_partitions, std::vector<FftData>(num_render_channels));
std::vector<std::vector<FftData>> H_Avx2(
num_partitions, std::vector<FftData>(num_render_channels));
for (size_t p = 0; p < num_partitions; ++p) {
for (size_t ch = 0; ch < num_render_channels; ++ch) {
H_C[p][ch].Clear();
H_Avx2[p][ch].Clear();
}
}
for (size_t k = 0; k < 500; ++k) {
for (int band = 0; band < x.NumBands(); ++band) {
for (int ch = 0; ch < x.NumChannels(); ++ch) {
RandomizeSampleVector(&random_generator, x.View(band, ch));
}
}
render_delay_buffer->Insert(x);
if (k == 0) {
render_delay_buffer->Reset();
}
render_delay_buffer->PrepareCaptureProcessing();
auto* const render_buffer = render_delay_buffer->GetRenderBuffer();
ApplyFilter_Avx2(*render_buffer, num_partitions, H_Avx2, &S_Avx2);
ApplyFilter(*render_buffer, num_partitions, H_C, &S_C);
for (size_t j = 0; j < S_C.re.size(); ++j) {
EXPECT_FLOAT_EQ(S_C.re[j], S_Avx2.re[j]);
EXPECT_FLOAT_EQ(S_C.im[j], S_Avx2.im[j]);
}
std::for_each(G.re.begin(), G.re.end(),
[&](float& a) { a = random_generator.Rand<float>(); });
std::for_each(G.im.begin(), G.im.end(),
[&](float& a) { a = random_generator.Rand<float>(); });
AdaptPartitions_Avx2(*render_buffer, G, num_partitions, &H_Avx2);
AdaptPartitions(*render_buffer, G, num_partitions, &H_C);
for (size_t p = 0; p < num_partitions; ++p) {
for (size_t ch = 0; ch < num_render_channels; ++ch) {
for (size_t j = 0; j < H_C[p][ch].re.size(); ++j) {
EXPECT_FLOAT_EQ(H_C[p][ch].re[j], H_Avx2[p][ch].re[j]);
EXPECT_FLOAT_EQ(H_C[p][ch].im[j], H_Avx2[p][ch].im[j]);
}
}
}
}
}
}
}
// Verifies that the optimized method for frequency response computation is
// bitexact to the reference counterpart.
TEST_P(AdaptiveFirFilterOneTwoFourEightRenderChannels,
ComputeFrequencyResponseSse2Optimization) {
const size_t num_render_channels = GetParam();
bool use_sse2 = (GetCPUInfo(kSSE2) != 0);
if (use_sse2) {
for (size_t num_partitions : {2, 5, 12, 30, 50}) {
std::vector<std::vector<FftData>> H(
num_partitions, std::vector<FftData>(num_render_channels));
std::vector<std::array<float, kFftLengthBy2Plus1>> H2(num_partitions);
std::vector<std::array<float, kFftLengthBy2Plus1>> H2_Sse2(
num_partitions);
for (size_t p = 0; p < num_partitions; ++p) {
for (size_t ch = 0; ch < num_render_channels; ++ch) {
for (size_t k = 0; k < H[p][ch].re.size(); ++k) {
H[p][ch].re[k] = k + p / 3.f + ch;
H[p][ch].im[k] = p + k / 7.f - ch;
}
}
}
ComputeFrequencyResponse(num_partitions, H, &H2);
ComputeFrequencyResponse_Sse2(num_partitions, H, &H2_Sse2);
for (size_t p = 0; p < num_partitions; ++p) {
for (size_t k = 0; k < H2[p].size(); ++k) {
EXPECT_FLOAT_EQ(H2[p][k], H2_Sse2[p][k]);
}
}
}
}
}
// Verifies that the optimized method for frequency response computation is
// bitexact to the reference counterpart.
TEST_P(AdaptiveFirFilterOneTwoFourEightRenderChannels,
ComputeFrequencyResponseAvx2Optimization) {
const size_t num_render_channels = GetParam();
bool use_avx2 = (GetCPUInfo(kAVX2) != 0);
if (use_avx2) {
for (size_t num_partitions : {2, 5, 12, 30, 50}) {
std::vector<std::vector<FftData>> H(
num_partitions, std::vector<FftData>(num_render_channels));
std::vector<std::array<float, kFftLengthBy2Plus1>> H2(num_partitions);
std::vector<std::array<float, kFftLengthBy2Plus1>> H2_Avx2(
num_partitions);
for (size_t p = 0; p < num_partitions; ++p) {
for (size_t ch = 0; ch < num_render_channels; ++ch) {
for (size_t k = 0; k < H[p][ch].re.size(); ++k) {
H[p][ch].re[k] = k + p / 3.f + ch;
H[p][ch].im[k] = p + k / 7.f - ch;
}
}
}
ComputeFrequencyResponse(num_partitions, H, &H2);
ComputeFrequencyResponse_Avx2(num_partitions, H, &H2_Avx2);
for (size_t p = 0; p < num_partitions; ++p) {
for (size_t k = 0; k < H2[p].size(); ++k) {
EXPECT_FLOAT_EQ(H2[p][k], H2_Avx2[p][k]);
}
}
}
}
}
#endif
#if RTC_DCHECK_IS_ON && GTEST_HAS_DEATH_TEST && !defined(WEBRTC_ANDROID)
// Verifies that the check for non-null data dumper works.
TEST(AdaptiveFirFilterDeathTest, NullDataDumper) {
EXPECT_DEATH(AdaptiveFirFilter(9, 9, 250, 1, DetectOptimization(), nullptr),
"");
}
// Verifies that the check for non-null filter output works.
TEST(AdaptiveFirFilterDeathTest, NullFilterOutput) {
ApmDataDumper data_dumper(42);
AdaptiveFirFilter filter(9, 9, 250, 1, DetectOptimization(), &data_dumper);
std::unique_ptr<RenderDelayBuffer> render_delay_buffer(
RenderDelayBuffer::Create(EchoCanceller3Config(), 48000, 1));
EXPECT_DEATH(filter.Filter(*render_delay_buffer->GetRenderBuffer(), nullptr),
"");
}
#endif
// Verifies that the filter statistics can be accessed when filter statistics
// are turned on.
TEST(AdaptiveFirFilterTest, FilterStatisticsAccess) {
ApmDataDumper data_dumper(42);
Aec3Optimization optimization = DetectOptimization();
AdaptiveFirFilter filter(9, 9, 250, 1, optimization, &data_dumper);
std::vector<std::array<float, kFftLengthBy2Plus1>> H2(
filter.max_filter_size_partitions(),
std::array<float, kFftLengthBy2Plus1>());
for (auto& H2_k : H2) {
H2_k.fill(0.f);
}
std::array<float, kFftLengthBy2Plus1> erl;
ComputeErl(optimization, H2, erl);
filter.ComputeFrequencyResponse(&H2);
}
// Verifies that the filter size if correctly repported.
TEST(AdaptiveFirFilterTest, FilterSize) {
ApmDataDumper data_dumper(42);
for (size_t filter_size = 1; filter_size < 5; ++filter_size) {
AdaptiveFirFilter filter(filter_size, filter_size, 250, 1,
DetectOptimization(), &data_dumper);
EXPECT_EQ(filter_size, filter.SizePartitions());
}
}
class AdaptiveFirFilterMultiChannel
: public ::testing::Test,
public ::testing::WithParamInterface<std::tuple<size_t, size_t>> {};
INSTANTIATE_TEST_SUITE_P(MultiChannel,
AdaptiveFirFilterMultiChannel,
::testing::Combine(::testing::Values(1, 4),
::testing::Values(1, 8)));
// Verifies that the filter is being able to properly filter a signal and to
// adapt its coefficients.
TEST_P(AdaptiveFirFilterMultiChannel, FilterAndAdapt) {
const size_t num_render_channels = std::get<0>(GetParam());
const size_t num_capture_channels = std::get<1>(GetParam());
constexpr int kSampleRateHz = 48000;
constexpr size_t kNumBands = NumBandsForRate(kSampleRateHz);
constexpr size_t kNumBlocksToProcessPerRenderChannel = 1000;
ApmDataDumper data_dumper(42);
EchoCanceller3Config config;
if (num_render_channels == 33) {
config.filter.refined = {13, 0.00005f, 0.0005f, 0.0001f, 2.f, 20075344.f};
config.filter.coarse = {13, 0.1f, 20075344.f};
config.filter.refined_initial = {12, 0.005f, 0.5f, 0.001f, 2.f, 20075344.f};
config.filter.coarse_initial = {12, 0.7f, 20075344.f};
}
AdaptiveFirFilter filter(
config.filter.refined.length_blocks, config.filter.refined.length_blocks,
config.filter.config_change_duration_blocks, num_render_channels,
DetectOptimization(), &data_dumper);
std::vector<std::vector<std::array<float, kFftLengthBy2Plus1>>> H2(
num_capture_channels, std::vector<std::array<float, kFftLengthBy2Plus1>>(
filter.max_filter_size_partitions(),
std::array<float, kFftLengthBy2Plus1>()));
std::vector<std::vector<float>> h(
num_capture_channels,
std::vector<float>(
GetTimeDomainLength(filter.max_filter_size_partitions()), 0.f));
Aec3Fft fft;
config.delay.default_delay = 1;
std::unique_ptr<RenderDelayBuffer> render_delay_buffer(
RenderDelayBuffer::Create(config, kSampleRateHz, num_render_channels));
CoarseFilterUpdateGain gain(config.filter.coarse,
config.filter.config_change_duration_blocks);
Random random_generator(42U);
Block x(kNumBands, num_render_channels);
std::vector<float> n(kBlockSize, 0.f);
std::vector<float> y(kBlockSize, 0.f);
AecState aec_state(EchoCanceller3Config{}, num_capture_channels);
RenderSignalAnalyzer render_signal_analyzer(config);
absl::optional<DelayEstimate> delay_estimate;
std::vector<float> e(kBlockSize, 0.f);
std::array<float, kFftLength> s_scratch;
std::vector<SubtractorOutput> output(num_capture_channels);
FftData S;
FftData G;
FftData E;
std::vector<std::array<float, kFftLengthBy2Plus1>> Y2(num_capture_channels);
std::vector<std::array<float, kFftLengthBy2Plus1>> E2_refined(
num_capture_channels);
std::array<float, kFftLengthBy2Plus1> E2_coarse;
// [B,A] = butter(2,100/8000,'high')
constexpr CascadedBiQuadFilter::BiQuadCoefficients
kHighPassFilterCoefficients = {{0.97261f, -1.94523f, 0.97261f},
{-1.94448f, 0.94598f}};
for (auto& Y2_ch : Y2) {
Y2_ch.fill(0.f);
}
for (auto& E2_refined_ch : E2_refined) {
E2_refined_ch.fill(0.f);
}
E2_coarse.fill(0.f);
for (auto& subtractor_output : output) {
subtractor_output.Reset();
}
constexpr float kScale = 1.0f / kFftLengthBy2;
for (size_t delay_samples : {0, 64, 150, 200, 301}) {
std::vector<DelayBuffer<float>> delay_buffer(
num_render_channels, DelayBuffer<float>(delay_samples));
std::vector<std::unique_ptr<CascadedBiQuadFilter>> x_hp_filter(
num_render_channels);
for (size_t ch = 0; ch < num_render_channels; ++ch) {
x_hp_filter[ch] = std::make_unique<CascadedBiQuadFilter>(
kHighPassFilterCoefficients, 1);
}
CascadedBiQuadFilter y_hp_filter(kHighPassFilterCoefficients, 1);
SCOPED_TRACE(ProduceDebugText(num_render_channels, delay_samples));
const size_t num_blocks_to_process =
kNumBlocksToProcessPerRenderChannel * num_render_channels;
for (size_t j = 0; j < num_blocks_to_process; ++j) {
std::fill(y.begin(), y.end(), 0.f);
for (size_t ch = 0; ch < num_render_channels; ++ch) {
RandomizeSampleVector(&random_generator, x.View(/*band=*/0, ch));
std::array<float, kBlockSize> y_channel;
delay_buffer[ch].Delay(x.View(/*band=*/0, ch), y_channel);
for (size_t k = 0; k < y.size(); ++k) {
y[k] += y_channel[k] / num_render_channels;
}
}
RandomizeSampleVector(&random_generator, n);
const float noise_scaling = 1.f / 100.f / num_render_channels;
for (size_t k = 0; k < y.size(); ++k) {
y[k] += n[k] * noise_scaling;
}
for (size_t ch = 0; ch < num_render_channels; ++ch) {
x_hp_filter[ch]->Process(x.View(/*band=*/0, ch));
}
y_hp_filter.Process(y);
render_delay_buffer->Insert(x);
if (j == 0) {
render_delay_buffer->Reset();
}
render_delay_buffer->PrepareCaptureProcessing();
auto* const render_buffer = render_delay_buffer->GetRenderBuffer();
render_signal_analyzer.Update(*render_buffer,
aec_state.MinDirectPathFilterDelay());
filter.Filter(*render_buffer, &S);
fft.Ifft(S, &s_scratch);
std::transform(y.begin(), y.end(), s_scratch.begin() + kFftLengthBy2,
e.begin(),
[&](float a, float b) { return a - b * kScale; });
std::for_each(e.begin(), e.end(),
[](float& a) { a = rtc::SafeClamp(a, -32768.f, 32767.f); });
fft.ZeroPaddedFft(e, Aec3Fft::Window::kRectangular, &E);
for (auto& o : output) {
for (size_t k = 0; k < kBlockSize; ++k) {
o.s_refined[k] = kScale * s_scratch[k + kFftLengthBy2];
}
}
std::array<float, kFftLengthBy2Plus1> render_power;
render_buffer->SpectralSum(filter.SizePartitions(), &render_power);
gain.Compute(render_power, render_signal_analyzer, E,
filter.SizePartitions(), false, &G);
filter.Adapt(*render_buffer, G, &h[0]);
aec_state.HandleEchoPathChange(EchoPathVariability(
false, EchoPathVariability::DelayAdjustment::kNone, false));
filter.ComputeFrequencyResponse(&H2[0]);
aec_state.Update(delay_estimate, H2, h, *render_buffer, E2_refined, Y2,
output);
}
// Verify that the filter is able to perform well.
EXPECT_LT(1000 * std::inner_product(e.begin(), e.end(), e.begin(), 0.f),
std::inner_product(y.begin(), y.end(), y.begin(), 0.f));
}
}
} // namespace aec3
} // namespace webrtc