webrtc/modules/audio_processing/aec3/echo_remover_metrics_unittest.cc
Per Åhgren d20639f1f6 Correct the FFT windowing when computing the AEC NLP gain
This CL adds an nonwindowed spectrum of the linear filter error
to use in the NLP computation.

Bug: webrtc:8661
Change-Id: I45bc9bb3eb8eeac0c5d6adb414638eb12b635a27
Reviewed-on: https://webrtc-review.googlesource.com/38701
Reviewed-by: Gustaf Ullberg <gustaf@webrtc.org>
Commit-Queue: Per Åhgren <peah@webrtc.org>
Cr-Commit-Position: refs/heads/master@{#21583}
2018-01-11 14:41:11 +00:00

158 lines
5.5 KiB
C++

/*
* 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/echo_remover_metrics.h"
#include <math.h>
#include "modules/audio_processing/aec3/aec_state.h"
#include "modules/audio_processing/aec3/aec3_fft.h"
#include "test/gtest.h"
namespace webrtc {
#if RTC_DCHECK_IS_ON && GTEST_HAS_DEATH_TEST && !defined(WEBRTC_ANDROID)
// Verifies the check for non-null input.
TEST(UpdateDbMetric, NullValue) {
std::array<float, kFftLengthBy2Plus1> value;
value.fill(0.f);
EXPECT_DEATH(aec3::UpdateDbMetric(value, nullptr), "");
}
#endif
// Verifies the updating functionality of UpdateDbMetric.
TEST(UpdateDbMetric, Updating) {
std::array<float, kFftLengthBy2Plus1> value;
std::array<EchoRemoverMetrics::DbMetric, 2> statistic;
statistic.fill(EchoRemoverMetrics::DbMetric(0.f, 100.f, -100.f));
constexpr float kValue0 = 10.f;
constexpr float kValue1 = 20.f;
std::fill(value.begin(), value.begin() + 32, kValue0);
std::fill(value.begin() + 32, value.begin() + 64, kValue1);
aec3::UpdateDbMetric(value, &statistic);
EXPECT_FLOAT_EQ(kValue0, statistic[0].sum_value);
EXPECT_FLOAT_EQ(kValue0, statistic[0].ceil_value);
EXPECT_FLOAT_EQ(kValue0, statistic[0].floor_value);
EXPECT_FLOAT_EQ(kValue1, statistic[1].sum_value);
EXPECT_FLOAT_EQ(kValue1, statistic[1].ceil_value);
EXPECT_FLOAT_EQ(kValue1, statistic[1].floor_value);
aec3::UpdateDbMetric(value, &statistic);
EXPECT_FLOAT_EQ(2.f * kValue0, statistic[0].sum_value);
EXPECT_FLOAT_EQ(kValue0, statistic[0].ceil_value);
EXPECT_FLOAT_EQ(kValue0, statistic[0].floor_value);
EXPECT_FLOAT_EQ(2.f * kValue1, statistic[1].sum_value);
EXPECT_FLOAT_EQ(kValue1, statistic[1].ceil_value);
EXPECT_FLOAT_EQ(kValue1, statistic[1].floor_value);
}
// Verifies that the TransformDbMetricForReporting method produces the desired
// output for values for dBFS.
TEST(TransformDbMetricForReporting, DbFsScaling) {
std::array<float, kBlockSize> x;
FftData X;
std::array<float, kFftLengthBy2Plus1> X2;
Aec3Fft fft;
x.fill(1000.f);
fft.ZeroPaddedFft(x, Aec3Fft::Window::kRectangular, &X);
X.Spectrum(Aec3Optimization::kNone, X2);
float offset = -10.f * log10(32768.f * 32768.f);
EXPECT_NEAR(offset, -90.3f, 0.1f);
EXPECT_EQ(
static_cast<int>(30.3f),
aec3::TransformDbMetricForReporting(
true, 0.f, 90.f, offset, 1.f / (kBlockSize * kBlockSize), X2[0]));
}
// Verifies that the TransformDbMetricForReporting method is able to properly
// limit the output.
TEST(TransformDbMetricForReporting, Limits) {
EXPECT_EQ(
0,
aec3::TransformDbMetricForReporting(false, 0.f, 10.f, 0.f, 1.f, 0.001f));
EXPECT_EQ(
10,
aec3::TransformDbMetricForReporting(false, 0.f, 10.f, 0.f, 1.f, 100.f));
}
// Verifies that the TransformDbMetricForReporting method is able to properly
// negate output.
TEST(TransformDbMetricForReporting, Negate) {
EXPECT_EQ(
10,
aec3::TransformDbMetricForReporting(true, -20.f, 20.f, 0.f, 1.f, 0.1f));
EXPECT_EQ(
-10,
aec3::TransformDbMetricForReporting(true, -20.f, 20.f, 0.f, 1.f, 10.f));
}
// Verify the Update functionality of DbMetric.
TEST(DbMetric, Update) {
EchoRemoverMetrics::DbMetric metric(0.f, 20.f, -20.f);
constexpr int kNumValues = 100;
constexpr float kValue = 10.f;
for (int k = 0; k < kNumValues; ++k) {
metric.Update(kValue);
}
EXPECT_FLOAT_EQ(kValue * kNumValues, metric.sum_value);
EXPECT_FLOAT_EQ(kValue, metric.ceil_value);
EXPECT_FLOAT_EQ(kValue, metric.floor_value);
}
// Verify the Update functionality of DbMetric.
TEST(DbMetric, UpdateInstant) {
EchoRemoverMetrics::DbMetric metric(0.f, 20.f, -20.f);
constexpr float kMinValue = -77.f;
constexpr float kMaxValue = 33.f;
constexpr float kLastValue = (kMinValue + kMaxValue) / 2.0f;
for (float value = kMinValue; value <= kMaxValue; value++)
metric.UpdateInstant(value);
metric.UpdateInstant(kLastValue);
EXPECT_FLOAT_EQ(kLastValue, metric.sum_value);
EXPECT_FLOAT_EQ(kMaxValue, metric.ceil_value);
EXPECT_FLOAT_EQ(kMinValue, metric.floor_value);
}
// Verify the constructor functionality of DbMetric.
TEST(DbMetric, Constructor) {
EchoRemoverMetrics::DbMetric metric;
EXPECT_FLOAT_EQ(0.f, metric.sum_value);
EXPECT_FLOAT_EQ(0.f, metric.ceil_value);
EXPECT_FLOAT_EQ(0.f, metric.floor_value);
metric = EchoRemoverMetrics::DbMetric(1.f, 2.f, 3.f);
EXPECT_FLOAT_EQ(1.f, metric.sum_value);
EXPECT_FLOAT_EQ(2.f, metric.floor_value);
EXPECT_FLOAT_EQ(3.f, metric.ceil_value);
}
// Verify the general functionality of EchoRemoverMetrics.
TEST(EchoRemoverMetrics, NormalUsage) {
EchoRemoverMetrics metrics;
AecState aec_state(EchoCanceller3Config{});
std::array<float, kFftLengthBy2Plus1> comfort_noise_spectrum;
std::array<float, kFftLengthBy2Plus1> suppressor_gain;
comfort_noise_spectrum.fill(10.f);
suppressor_gain.fill(1.f);
for (int j = 0; j < 3; ++j) {
for (int k = 0; k < kMetricsReportingIntervalBlocks - 1; ++k) {
metrics.Update(aec_state, comfort_noise_spectrum, suppressor_gain);
EXPECT_FALSE(metrics.MetricsReported());
}
metrics.Update(aec_state, comfort_noise_spectrum, suppressor_gain);
EXPECT_TRUE(metrics.MetricsReported());
}
}
} // namespace webrtc