blob: ef057071421bf97902ed81963362a5c7b988f256 [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/aec_state.h"
#include "modules/audio_processing/aec3/aec3_fft.h"
#include "modules/audio_processing/aec3/render_delay_buffer.h"
#include "modules/audio_processing/logging/apm_data_dumper.h"
#include "test/gtest.h"
namespace webrtc {
// Verify the general functionality of AecState
TEST(AecState, NormalUsage) {
ApmDataDumper data_dumper(42);
EchoCanceller3Config config;
AecState state(config);
absl::optional<DelayEstimate> delay_estimate =
DelayEstimate(DelayEstimate::Quality::kRefined, 10);
std::unique_ptr<RenderDelayBuffer> render_delay_buffer(
RenderDelayBuffer::Create(config, 3));
std::array<float, kFftLengthBy2Plus1> E2_main = {};
std::array<float, kFftLengthBy2Plus1> Y2 = {};
std::vector<std::vector<float>> x(3, std::vector<float>(kBlockSize, 0.f));
EchoPathVariability echo_path_variability(
false, EchoPathVariability::DelayAdjustment::kNone, false);
SubtractorOutput output;
std::array<float, kBlockSize> y;
Aec3Fft fft;
output.s_main.fill(100.f);
output.e_main.fill(100.f);
y.fill(1000.f);
std::vector<std::array<float, kFftLengthBy2Plus1>>
converged_filter_frequency_response(10);
for (auto& v : converged_filter_frequency_response) {
v.fill(0.01f);
}
std::vector<std::array<float, kFftLengthBy2Plus1>>
diverged_filter_frequency_response = converged_filter_frequency_response;
converged_filter_frequency_response[2].fill(100.f);
converged_filter_frequency_response[2][0] = 1.f;
std::vector<float> impulse_response(
GetTimeDomainLength(config.filter.main.length_blocks), 0.f);
// Verify that linear AEC usability is false when the filter is diverged.
state.Update(delay_estimate, diverged_filter_frequency_response,
impulse_response, *render_delay_buffer->GetRenderBuffer(),
E2_main, Y2, output, y);
EXPECT_FALSE(state.UsableLinearEstimate());
// Verify that linear AEC usability is true when the filter is converged
std::fill(x[0].begin(), x[0].end(), 101.f);
for (int k = 0; k < 3000; ++k) {
render_delay_buffer->Insert(x);
state.Update(delay_estimate, converged_filter_frequency_response,
impulse_response, *render_delay_buffer->GetRenderBuffer(),
E2_main, Y2, output, y);
}
EXPECT_TRUE(state.UsableLinearEstimate());
// Verify that linear AEC usability becomes false after an echo path change is
// reported
state.HandleEchoPathChange(EchoPathVariability(
false, EchoPathVariability::DelayAdjustment::kBufferReadjustment, false));
state.Update(delay_estimate, converged_filter_frequency_response,
impulse_response, *render_delay_buffer->GetRenderBuffer(),
E2_main, Y2, output, y);
EXPECT_FALSE(state.UsableLinearEstimate());
// Verify that the active render detection works as intended.
std::fill(x[0].begin(), x[0].end(), 101.f);
render_delay_buffer->Insert(x);
state.HandleEchoPathChange(EchoPathVariability(
true, EchoPathVariability::DelayAdjustment::kNewDetectedDelay, false));
state.Update(delay_estimate, converged_filter_frequency_response,
impulse_response, *render_delay_buffer->GetRenderBuffer(),
E2_main, Y2, output, y);
EXPECT_FALSE(state.ActiveRender());
for (int k = 0; k < 1000; ++k) {
render_delay_buffer->Insert(x);
state.Update(delay_estimate, converged_filter_frequency_response,
impulse_response, *render_delay_buffer->GetRenderBuffer(),
E2_main, Y2, output, y);
}
EXPECT_TRUE(state.ActiveRender());
// Verify that the ERL is properly estimated
for (auto& x_k : x) {
x_k = std::vector<float>(kBlockSize, 0.f);
}
x[0][0] = 5000.f;
for (size_t k = 0;
k < render_delay_buffer->GetRenderBuffer()->GetFftBuffer().size(); ++k) {
render_delay_buffer->Insert(x);
if (k == 0) {
render_delay_buffer->Reset();
}
render_delay_buffer->PrepareCaptureProcessing();
}
Y2.fill(10.f * 10000.f * 10000.f);
for (size_t k = 0; k < 1000; ++k) {
state.Update(delay_estimate, converged_filter_frequency_response,
impulse_response, *render_delay_buffer->GetRenderBuffer(),
E2_main, Y2, output, y);
}
ASSERT_TRUE(state.UsableLinearEstimate());
const std::array<float, kFftLengthBy2Plus1>& erl = state.Erl();
EXPECT_EQ(erl[0], erl[1]);
for (size_t k = 1; k < erl.size() - 1; ++k) {
EXPECT_NEAR(k % 2 == 0 ? 10.f : 1000.f, erl[k], 0.1);
}
EXPECT_EQ(erl[erl.size() - 2], erl[erl.size() - 1]);
// Verify that the ERLE is properly estimated
E2_main.fill(1.f * 10000.f * 10000.f);
Y2.fill(10.f * E2_main[0]);
for (size_t k = 0; k < 1000; ++k) {
state.Update(delay_estimate, converged_filter_frequency_response,
impulse_response, *render_delay_buffer->GetRenderBuffer(),
E2_main, Y2, output, y);
}
ASSERT_TRUE(state.UsableLinearEstimate());
{
const auto& erle = state.Erle();
EXPECT_EQ(erle[0], erle[1]);
constexpr size_t kLowFrequencyLimit = 32;
for (size_t k = 1; k < kLowFrequencyLimit; ++k) {
EXPECT_NEAR(k % 2 == 0 ? 4.f : 1.f, erle[k], 0.1);
}
for (size_t k = kLowFrequencyLimit; k < erle.size() - 1; ++k) {
EXPECT_NEAR(k % 2 == 0 ? 1.5f : 1.f, erle[k], 0.1);
}
EXPECT_EQ(erle[erle.size() - 2], erle[erle.size() - 1]);
}
E2_main.fill(1.f * 10000.f * 10000.f);
Y2.fill(5.f * E2_main[0]);
for (size_t k = 0; k < 1000; ++k) {
state.Update(delay_estimate, converged_filter_frequency_response,
impulse_response, *render_delay_buffer->GetRenderBuffer(),
E2_main, Y2, output, y);
}
ASSERT_TRUE(state.UsableLinearEstimate());
{
const auto& erle = state.Erle();
EXPECT_EQ(erle[0], erle[1]);
constexpr size_t kLowFrequencyLimit = 32;
for (size_t k = 1; k < kLowFrequencyLimit; ++k) {
EXPECT_NEAR(k % 2 == 0 ? 4.f : 1.f, erle[k], 0.1);
}
for (size_t k = kLowFrequencyLimit; k < erle.size() - 1; ++k) {
EXPECT_NEAR(k % 2 == 0 ? 1.5f : 1.f, erle[k], 0.1);
}
EXPECT_EQ(erle[erle.size() - 2], erle[erle.size() - 1]);
}
}
// Verifies the delay for a converged filter is correctly identified.
TEST(AecState, ConvergedFilterDelay) {
constexpr int kFilterLengthBlocks = 10;
EchoCanceller3Config config;
AecState state(config);
std::unique_ptr<RenderDelayBuffer> render_delay_buffer(
RenderDelayBuffer::Create(config, 3));
absl::optional<DelayEstimate> delay_estimate;
std::array<float, kFftLengthBy2Plus1> E2_main;
std::array<float, kFftLengthBy2Plus1> Y2;
std::array<float, kBlockSize> x;
EchoPathVariability echo_path_variability(
false, EchoPathVariability::DelayAdjustment::kNone, false);
SubtractorOutput output;
std::array<float, kBlockSize> y;
output.s_main.fill(100.f);
x.fill(0.f);
y.fill(0.f);
std::vector<std::array<float, kFftLengthBy2Plus1>> frequency_response(
kFilterLengthBlocks);
for (auto& v : frequency_response) {
v.fill(0.01f);
}
std::vector<float> impulse_response(
GetTimeDomainLength(config.filter.main.length_blocks), 0.f);
// Verify that the filter delay for a converged filter is properly identified.
for (int k = 0; k < kFilterLengthBlocks; ++k) {
std::fill(impulse_response.begin(), impulse_response.end(), 0.f);
impulse_response[k * kBlockSize + 1] = 1.f;
state.HandleEchoPathChange(echo_path_variability);
state.Update(delay_estimate, frequency_response, impulse_response,
*render_delay_buffer->GetRenderBuffer(), E2_main, Y2, output,
y);
}
}
} // namespace webrtc