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e9a7e90625
Specially for devices with high echo path gain, even low render signal can allow the linear filter of the AEC3 to converge. However, the conditions that were used for updating the ERLE avoided to update that estimation. In this commit, we allow adapting the ERLE estimator using even low render signal but the update of the ERLE is constraint in a way that decreases are not allowed. Bug: webrtc:9776 Change-Id: Ic4331efcc47a0b05f394cdea9a88f336292de5a1 Reviewed-on: https://webrtc-review.googlesource.com/101641 Commit-Queue: Jesus de Vicente Pena <devicentepena@webrtc.org> Reviewed-by: Per Åhgren <peah@webrtc.org> Cr-Commit-Position: refs/heads/master@{#24859}
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::Create(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.UpdatePowers(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.UpdatePowers(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.UpdatePowers(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.UpdatePowers(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.UpdatePowers(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.UpdatePowers(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.UpdatePowers(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::Create(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.UpdatePowers(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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