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This CL introduces two related changes 1) It changes the way that the AEC3 determines whether the linear filter is sufficiently good for its output to be used. The new scheme achieves this much earlier than what was done in the legacy scheme. 2) It changes the way that saturated echo is and handled so that the impact of the nearend speech is lower. Bug: webrtc:9835,webrtc:9843,chromium:895435,chromium:895431 Change-Id: I0b493676886e2134205e9992bbe4badac7e414cc Reviewed-on: https://webrtc-review.googlesource.com/c/104380 Commit-Queue: Per Åhgren <peah@webrtc.org> Reviewed-by: Gustaf Ullberg <gustaf@webrtc.org> Cr-Commit-Position: refs/heads/master@{#25208}
218 lines
8 KiB
C++
218 lines
8 KiB
C++
/*
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* Copyright (c) 2017 The WebRTC project authors. All Rights Reserved.
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*
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* Use of this source code is governed by a BSD-style license
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* that can be found in the LICENSE file in the root of the source
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* tree. An additional intellectual property rights grant can be found
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* in the file PATENTS. All contributing project authors may
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* be found in the AUTHORS file in the root of the source tree.
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*/
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#include "modules/audio_processing/aec3/aec_state.h"
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#include "modules/audio_processing/aec3/aec3_fft.h"
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#include "modules/audio_processing/aec3/render_delay_buffer.h"
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#include "modules/audio_processing/logging/apm_data_dumper.h"
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#include "test/gtest.h"
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namespace webrtc {
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// Verify the general functionality of AecState
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TEST(AecState, NormalUsage) {
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ApmDataDumper data_dumper(42);
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EchoCanceller3Config config;
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AecState state(config);
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absl::optional<DelayEstimate> delay_estimate =
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DelayEstimate(DelayEstimate::Quality::kRefined, 10);
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std::unique_ptr<RenderDelayBuffer> render_delay_buffer(
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RenderDelayBuffer::Create2(config, 3));
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std::array<float, kFftLengthBy2Plus1> E2_main = {};
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std::array<float, kFftLengthBy2Plus1> Y2 = {};
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std::vector<std::vector<float>> x(3, std::vector<float>(kBlockSize, 0.f));
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EchoPathVariability echo_path_variability(
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false, EchoPathVariability::DelayAdjustment::kNone, false);
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SubtractorOutput output;
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output.Reset();
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std::array<float, kBlockSize> y;
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Aec3Fft fft;
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output.s_main.fill(100.f);
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output.e_main.fill(100.f);
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y.fill(1000.f);
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std::vector<std::array<float, kFftLengthBy2Plus1>>
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converged_filter_frequency_response(10);
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for (auto& v : converged_filter_frequency_response) {
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v.fill(0.01f);
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}
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std::vector<std::array<float, kFftLengthBy2Plus1>>
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diverged_filter_frequency_response = converged_filter_frequency_response;
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converged_filter_frequency_response[2].fill(100.f);
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converged_filter_frequency_response[2][0] = 1.f;
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std::vector<float> impulse_response(
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GetTimeDomainLength(config.filter.main.length_blocks), 0.f);
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// Verify that linear AEC usability is true when the filter is converged
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std::fill(x[0].begin(), x[0].end(), 101.f);
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for (int k = 0; k < 3000; ++k) {
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render_delay_buffer->Insert(x);
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output.ComputeMetrics(y);
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state.Update(delay_estimate, converged_filter_frequency_response,
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impulse_response, *render_delay_buffer->GetRenderBuffer(),
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E2_main, Y2, output, y);
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}
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EXPECT_TRUE(state.UsableLinearEstimate());
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// Verify that linear AEC usability becomes false after an echo path change is
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// reported
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output.ComputeMetrics(y);
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state.HandleEchoPathChange(EchoPathVariability(
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false, EchoPathVariability::DelayAdjustment::kBufferReadjustment, false));
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state.Update(delay_estimate, converged_filter_frequency_response,
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impulse_response, *render_delay_buffer->GetRenderBuffer(),
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E2_main, Y2, output, y);
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EXPECT_FALSE(state.UsableLinearEstimate());
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// Verify that the active render detection works as intended.
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std::fill(x[0].begin(), x[0].end(), 101.f);
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render_delay_buffer->Insert(x);
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output.ComputeMetrics(y);
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state.HandleEchoPathChange(EchoPathVariability(
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true, EchoPathVariability::DelayAdjustment::kNewDetectedDelay, false));
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state.Update(delay_estimate, converged_filter_frequency_response,
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impulse_response, *render_delay_buffer->GetRenderBuffer(),
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E2_main, Y2, output, y);
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EXPECT_FALSE(state.ActiveRender());
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for (int k = 0; k < 1000; ++k) {
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render_delay_buffer->Insert(x);
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output.ComputeMetrics(y);
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state.Update(delay_estimate, converged_filter_frequency_response,
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impulse_response, *render_delay_buffer->GetRenderBuffer(),
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E2_main, Y2, output, y);
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}
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EXPECT_TRUE(state.ActiveRender());
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// Verify that the ERL is properly estimated
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for (auto& x_k : x) {
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x_k = std::vector<float>(kBlockSize, 0.f);
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}
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x[0][0] = 5000.f;
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for (size_t k = 0;
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k < render_delay_buffer->GetRenderBuffer()->GetFftBuffer().size(); ++k) {
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render_delay_buffer->Insert(x);
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if (k == 0) {
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render_delay_buffer->Reset();
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}
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render_delay_buffer->PrepareCaptureProcessing();
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}
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Y2.fill(10.f * 10000.f * 10000.f);
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for (size_t k = 0; k < 1000; ++k) {
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output.ComputeMetrics(y);
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state.Update(delay_estimate, converged_filter_frequency_response,
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impulse_response, *render_delay_buffer->GetRenderBuffer(),
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E2_main, Y2, output, y);
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}
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ASSERT_TRUE(state.UsableLinearEstimate());
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const std::array<float, kFftLengthBy2Plus1>& erl = state.Erl();
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EXPECT_EQ(erl[0], erl[1]);
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for (size_t k = 1; k < erl.size() - 1; ++k) {
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EXPECT_NEAR(k % 2 == 0 ? 10.f : 1000.f, erl[k], 0.1);
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}
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EXPECT_EQ(erl[erl.size() - 2], erl[erl.size() - 1]);
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// Verify that the ERLE is properly estimated
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E2_main.fill(1.f * 10000.f * 10000.f);
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Y2.fill(10.f * E2_main[0]);
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for (size_t k = 0; k < 1000; ++k) {
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output.ComputeMetrics(y);
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state.Update(delay_estimate, converged_filter_frequency_response,
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impulse_response, *render_delay_buffer->GetRenderBuffer(),
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E2_main, Y2, output, y);
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}
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ASSERT_TRUE(state.UsableLinearEstimate());
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{
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// Note that the render spectrum is built so it does not have energy in the
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// odd bands but just in the even bands.
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const auto& erle = state.Erle();
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EXPECT_EQ(erle[0], erle[1]);
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constexpr size_t kLowFrequencyLimit = 32;
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for (size_t k = 2; k < kLowFrequencyLimit; k = k + 2) {
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EXPECT_NEAR(4.f, erle[k], 0.1);
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}
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for (size_t k = kLowFrequencyLimit; k < erle.size() - 1; k = k + 2) {
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EXPECT_NEAR(1.5f, erle[k], 0.1);
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}
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EXPECT_EQ(erle[erle.size() - 2], erle[erle.size() - 1]);
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}
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E2_main.fill(1.f * 10000.f * 10000.f);
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Y2.fill(5.f * E2_main[0]);
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for (size_t k = 0; k < 1000; ++k) {
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output.ComputeMetrics(y);
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state.Update(delay_estimate, converged_filter_frequency_response,
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impulse_response, *render_delay_buffer->GetRenderBuffer(),
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E2_main, Y2, output, y);
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}
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ASSERT_TRUE(state.UsableLinearEstimate());
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{
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const auto& erle = state.Erle();
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EXPECT_EQ(erle[0], erle[1]);
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constexpr size_t kLowFrequencyLimit = 32;
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for (size_t k = 1; k < kLowFrequencyLimit; ++k) {
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EXPECT_NEAR(k % 2 == 0 ? 4.f : 1.f, erle[k], 0.1);
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}
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for (size_t k = kLowFrequencyLimit; k < erle.size() - 1; ++k) {
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EXPECT_NEAR(k % 2 == 0 ? 1.5f : 1.f, erle[k], 0.1);
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}
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EXPECT_EQ(erle[erle.size() - 2], erle[erle.size() - 1]);
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}
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}
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// Verifies the delay for a converged filter is correctly identified.
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TEST(AecState, ConvergedFilterDelay) {
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constexpr int kFilterLengthBlocks = 10;
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EchoCanceller3Config config;
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AecState state(config);
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std::unique_ptr<RenderDelayBuffer> render_delay_buffer(
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RenderDelayBuffer::Create2(config, 3));
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absl::optional<DelayEstimate> delay_estimate;
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std::array<float, kFftLengthBy2Plus1> E2_main;
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std::array<float, kFftLengthBy2Plus1> Y2;
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std::array<float, kBlockSize> x;
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EchoPathVariability echo_path_variability(
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false, EchoPathVariability::DelayAdjustment::kNone, false);
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SubtractorOutput output;
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output.Reset();
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std::array<float, kBlockSize> y;
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output.s_main.fill(100.f);
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x.fill(0.f);
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y.fill(0.f);
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std::vector<std::array<float, kFftLengthBy2Plus1>> frequency_response(
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kFilterLengthBlocks);
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for (auto& v : frequency_response) {
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v.fill(0.01f);
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}
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std::vector<float> impulse_response(
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GetTimeDomainLength(config.filter.main.length_blocks), 0.f);
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// Verify that the filter delay for a converged filter is properly identified.
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for (int k = 0; k < kFilterLengthBlocks; ++k) {
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std::fill(impulse_response.begin(), impulse_response.end(), 0.f);
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impulse_response[k * kBlockSize + 1] = 1.f;
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state.HandleEchoPathChange(echo_path_variability);
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output.ComputeMetrics(y);
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state.Update(delay_estimate, frequency_response, impulse_response,
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*render_delay_buffer->GetRenderBuffer(), E2_main, Y2, output,
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y);
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}
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}
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} // namespace webrtc
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