| /* |
| * Copyright (c) 2018 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/agc2/noise_level_estimator.h" |
| |
| #include <array> |
| #include <cmath> |
| #include <functional> |
| #include <limits> |
| |
| #include "api/function_view.h" |
| #include "modules/audio_processing/agc2/agc2_testing_common.h" |
| #include "modules/audio_processing/agc2/vector_float_frame.h" |
| #include "modules/audio_processing/logging/apm_data_dumper.h" |
| #include "rtc_base/gunit.h" |
| |
| namespace webrtc { |
| namespace { |
| |
| constexpr int kNumIterations = 200; |
| constexpr int kFramesPerSecond = 100; |
| |
| // Runs the noise estimator on audio generated by 'sample_generator' |
| // for kNumIterations. Returns the last noise level estimate. |
| float RunEstimator(rtc::FunctionView<float()> sample_generator, |
| NoiseLevelEstimator& estimator, |
| int sample_rate_hz) { |
| const int samples_per_channel = |
| rtc::CheckedDivExact(sample_rate_hz, kFramesPerSecond); |
| VectorFloatFrame signal(1, samples_per_channel, 0.0f); |
| for (int i = 0; i < kNumIterations; ++i) { |
| AudioFrameView<float> frame_view = signal.float_frame_view(); |
| for (int j = 0; j < samples_per_channel; ++j) { |
| frame_view.channel(0)[j] = sample_generator(); |
| } |
| estimator.Analyze(frame_view); |
| } |
| return estimator.Analyze(signal.float_frame_view()); |
| } |
| |
| class NoiseEstimatorParametrization : public ::testing::TestWithParam<int> { |
| protected: |
| int sample_rate_hz() const { return GetParam(); } |
| }; |
| |
| // White random noise is stationary, but does not trigger the detector |
| // every frame due to the randomness. |
| TEST_P(NoiseEstimatorParametrization, StationaryNoiseEstimatorWithRandomNoise) { |
| ApmDataDumper data_dumper(0); |
| auto estimator = CreateStationaryNoiseEstimator(&data_dumper); |
| |
| test::WhiteNoiseGenerator gen(/*min_amplitude=*/test::kMinS16, |
| /*max_amplitude=*/test::kMaxS16); |
| const float noise_level_dbfs = |
| RunEstimator(gen, *estimator, sample_rate_hz()); |
| EXPECT_NEAR(noise_level_dbfs, -5.5f, 1.0f); |
| } |
| |
| // Sine curves are (very) stationary. They trigger the detector all |
| // the time. Except for a few initial frames. |
| TEST_P(NoiseEstimatorParametrization, StationaryNoiseEstimatorWithSineTone) { |
| ApmDataDumper data_dumper(0); |
| auto estimator = CreateStationaryNoiseEstimator(&data_dumper); |
| |
| test::SineGenerator gen(/*amplitude=*/test::kMaxS16, /*frequency_hz=*/600.0f, |
| sample_rate_hz()); |
| const float noise_level_dbfs = |
| RunEstimator(gen, *estimator, sample_rate_hz()); |
| EXPECT_NEAR(noise_level_dbfs, -3.0f, 1.0f); |
| } |
| |
| // Pulses are transient if they are far enough apart. They shouldn't |
| // trigger the noise detector. |
| TEST_P(NoiseEstimatorParametrization, StationaryNoiseEstimatorWithPulseTone) { |
| ApmDataDumper data_dumper(0); |
| auto estimator = CreateStationaryNoiseEstimator(&data_dumper); |
| |
| test::PulseGenerator gen(/*pulse_amplitude=*/test::kMaxS16, |
| /*no_pulse_amplitude=*/10.0f, /*frequency_hz=*/20.0f, |
| sample_rate_hz()); |
| const int noise_level_dbfs = RunEstimator(gen, *estimator, sample_rate_hz()); |
| EXPECT_NEAR(noise_level_dbfs, -79.0f, 1.0f); |
| } |
| |
| // Checks that full scale white noise maps to about -5.5 dBFS. |
| TEST_P(NoiseEstimatorParametrization, NoiseFloorEstimatorWithRandomNoise) { |
| ApmDataDumper data_dumper(0); |
| auto estimator = CreateNoiseFloorEstimator(&data_dumper); |
| |
| test::WhiteNoiseGenerator gen(/*min_amplitude=*/test::kMinS16, |
| /*max_amplitude=*/test::kMaxS16); |
| const float noise_level_dbfs = |
| RunEstimator(gen, *estimator, sample_rate_hz()); |
| EXPECT_NEAR(noise_level_dbfs, -5.5f, 0.5f); |
| } |
| |
| // Checks that a full scale sine wave maps to about -3 dBFS. |
| TEST_P(NoiseEstimatorParametrization, NoiseFloorEstimatorWithSineTone) { |
| ApmDataDumper data_dumper(0); |
| auto estimator = CreateNoiseFloorEstimator(&data_dumper); |
| |
| test::SineGenerator gen(/*amplitude=*/test::kMaxS16, /*frequency_hz=*/600.0f, |
| sample_rate_hz()); |
| const float noise_level_dbfs = |
| RunEstimator(gen, *estimator, sample_rate_hz()); |
| EXPECT_NEAR(noise_level_dbfs, -3.0f, 0.1f); |
| } |
| |
| // Check that sufficiently spaced periodic pulses do not raise the estimated |
| // noise floor, which is determined by the amplitude of the non-pulse samples. |
| TEST_P(NoiseEstimatorParametrization, NoiseFloorEstimatorWithPulseTone) { |
| ApmDataDumper data_dumper(0); |
| auto estimator = CreateNoiseFloorEstimator(&data_dumper); |
| |
| constexpr float kNoPulseAmplitude = 10.0f; |
| test::PulseGenerator gen(/*pulse_amplitude=*/test::kMaxS16, kNoPulseAmplitude, |
| /*frequency_hz=*/20.0f, sample_rate_hz()); |
| const int noise_level_dbfs = RunEstimator(gen, *estimator, sample_rate_hz()); |
| const float expected_noise_floor_dbfs = |
| 20.0f * std::log10f(kNoPulseAmplitude / test::kMaxS16); |
| EXPECT_NEAR(noise_level_dbfs, expected_noise_floor_dbfs, 0.5f); |
| } |
| |
| INSTANTIATE_TEST_SUITE_P(GainController2NoiseEstimator, |
| NoiseEstimatorParametrization, |
| ::testing::Values(8000, 16000, 32000, 48000)); |
| |
| } // namespace |
| } // namespace webrtc |