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The current noise level estimator has a bug due to which the estimated level decays to the lower bound in a few seconds when speech is observed. Instead of fixing the current implementation, which is based on a stationarity classifier, an alternative, lightweight, noise floor estimator has been added and tuned for AGC2. Tested on several AEC dumps including HW mute, music and fast talking. Bug: webrtc:7494 Change-Id: Iae4cff9fc955a716878f830957e893cd5bc59446 Reviewed-on: https://webrtc-review.googlesource.com/c/src/+/214133 Commit-Queue: Alessio Bazzica <alessiob@webrtc.org> Reviewed-by: Per Åhgren <peah@webrtc.org> Cr-Commit-Position: refs/heads/master@{#33733}
136 lines
5.4 KiB
C++
136 lines
5.4 KiB
C++
/*
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* Copyright (c) 2018 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/agc2/noise_level_estimator.h"
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#include <array>
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#include <cmath>
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#include <functional>
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#include <limits>
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#include "api/function_view.h"
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#include "modules/audio_processing/agc2/agc2_testing_common.h"
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#include "modules/audio_processing/agc2/vector_float_frame.h"
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#include "modules/audio_processing/logging/apm_data_dumper.h"
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#include "rtc_base/gunit.h"
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namespace webrtc {
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namespace {
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constexpr int kNumIterations = 200;
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constexpr int kFramesPerSecond = 100;
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// Runs the noise estimator on audio generated by 'sample_generator'
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// for kNumIterations. Returns the last noise level estimate.
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float RunEstimator(rtc::FunctionView<float()> sample_generator,
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NoiseLevelEstimator& estimator,
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int sample_rate_hz) {
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const int samples_per_channel =
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rtc::CheckedDivExact(sample_rate_hz, kFramesPerSecond);
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VectorFloatFrame signal(1, samples_per_channel, 0.0f);
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for (int i = 0; i < kNumIterations; ++i) {
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AudioFrameView<float> frame_view = signal.float_frame_view();
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for (int j = 0; j < samples_per_channel; ++j) {
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frame_view.channel(0)[j] = sample_generator();
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}
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estimator.Analyze(frame_view);
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}
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return estimator.Analyze(signal.float_frame_view());
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}
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class NoiseEstimatorParametrization : public ::testing::TestWithParam<int> {
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protected:
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int sample_rate_hz() const { return GetParam(); }
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};
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// White random noise is stationary, but does not trigger the detector
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// every frame due to the randomness.
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TEST_P(NoiseEstimatorParametrization, StationaryNoiseEstimatorWithRandomNoise) {
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ApmDataDumper data_dumper(0);
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auto estimator = CreateStationaryNoiseEstimator(&data_dumper);
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test::WhiteNoiseGenerator gen(/*min_amplitude=*/test::kMinS16,
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/*max_amplitude=*/test::kMaxS16);
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const float noise_level_dbfs =
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RunEstimator(gen, *estimator, sample_rate_hz());
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EXPECT_NEAR(noise_level_dbfs, -5.5f, 1.0f);
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}
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// Sine curves are (very) stationary. They trigger the detector all
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// the time. Except for a few initial frames.
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TEST_P(NoiseEstimatorParametrization, StationaryNoiseEstimatorWithSineTone) {
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ApmDataDumper data_dumper(0);
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auto estimator = CreateStationaryNoiseEstimator(&data_dumper);
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test::SineGenerator gen(/*amplitude=*/test::kMaxS16, /*frequency_hz=*/600.0f,
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sample_rate_hz());
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const float noise_level_dbfs =
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RunEstimator(gen, *estimator, sample_rate_hz());
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EXPECT_NEAR(noise_level_dbfs, -3.0f, 1.0f);
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}
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// Pulses are transient if they are far enough apart. They shouldn't
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// trigger the noise detector.
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TEST_P(NoiseEstimatorParametrization, StationaryNoiseEstimatorWithPulseTone) {
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ApmDataDumper data_dumper(0);
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auto estimator = CreateStationaryNoiseEstimator(&data_dumper);
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test::PulseGenerator gen(/*pulse_amplitude=*/test::kMaxS16,
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/*no_pulse_amplitude=*/10.0f, /*frequency_hz=*/20.0f,
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sample_rate_hz());
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const int noise_level_dbfs = RunEstimator(gen, *estimator, sample_rate_hz());
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EXPECT_NEAR(noise_level_dbfs, -79.0f, 1.0f);
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}
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// Checks that full scale white noise maps to about -5.5 dBFS.
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TEST_P(NoiseEstimatorParametrization, NoiseFloorEstimatorWithRandomNoise) {
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ApmDataDumper data_dumper(0);
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auto estimator = CreateNoiseFloorEstimator(&data_dumper);
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test::WhiteNoiseGenerator gen(/*min_amplitude=*/test::kMinS16,
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/*max_amplitude=*/test::kMaxS16);
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const float noise_level_dbfs =
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RunEstimator(gen, *estimator, sample_rate_hz());
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EXPECT_NEAR(noise_level_dbfs, -5.5f, 0.5f);
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}
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// Checks that a full scale sine wave maps to about -3 dBFS.
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TEST_P(NoiseEstimatorParametrization, NoiseFloorEstimatorWithSineTone) {
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ApmDataDumper data_dumper(0);
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auto estimator = CreateNoiseFloorEstimator(&data_dumper);
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test::SineGenerator gen(/*amplitude=*/test::kMaxS16, /*frequency_hz=*/600.0f,
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sample_rate_hz());
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const float noise_level_dbfs =
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RunEstimator(gen, *estimator, sample_rate_hz());
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EXPECT_NEAR(noise_level_dbfs, -3.0f, 0.1f);
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}
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// Check that sufficiently spaced periodic pulses do not raise the estimated
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// noise floor, which is determined by the amplitude of the non-pulse samples.
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TEST_P(NoiseEstimatorParametrization, NoiseFloorEstimatorWithPulseTone) {
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ApmDataDumper data_dumper(0);
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auto estimator = CreateNoiseFloorEstimator(&data_dumper);
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constexpr float kNoPulseAmplitude = 10.0f;
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test::PulseGenerator gen(/*pulse_amplitude=*/test::kMaxS16, kNoPulseAmplitude,
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/*frequency_hz=*/20.0f, sample_rate_hz());
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const int noise_level_dbfs = RunEstimator(gen, *estimator, sample_rate_hz());
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const float expected_noise_floor_dbfs =
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20.0f * std::log10f(kNoPulseAmplitude / test::kMaxS16);
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EXPECT_NEAR(noise_level_dbfs, expected_noise_floor_dbfs, 0.5f);
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}
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INSTANTIATE_TEST_SUITE_P(GainController2NoiseEstimator,
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NoiseEstimatorParametrization,
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::testing::Values(8000, 16000, 32000, 48000));
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} // namespace
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} // namespace webrtc
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