AGC2 VAD probability: instant decay / slow attack

Feature added to gain robustness to occasional VAD speech probability
spikes. In such a case, the attack process reduces the chance that the
smoothed values are greater than the speech threshold.

Bug: webrtc:7494
Change-Id: I6babe5afe30ea3dea021181a19d86bb74b33a98c
Reviewed-on: https://webrtc-review.googlesource.com/c/src/+/185046
Commit-Queue: Alessio Bazzica <alessiob@webrtc.org>
Reviewed-by: Gustaf Ullberg <gustaf@webrtc.org>
Cr-Commit-Position: refs/heads/master@{#32198}
This commit is contained in:
Alessio Bazzica
2020-09-25 14:31:17 +02:00
committed by Commit Bot
parent f2969fa868
commit c1ece012cb
5 changed files with 145 additions and 16 deletions

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@ -95,6 +95,7 @@ rtc_library("common") {
"../../../rtc_base:rtc_base_approved",
"../../../system_wrappers:field_trial",
]
absl_deps = [ "//third_party/abseil-cpp/absl/types:optional" ]
}
rtc_library("fixed_digital") {
@ -168,6 +169,7 @@ rtc_library("rnn_vad_with_level") {
"vad_with_level.h",
]
deps = [
":common",
"..:audio_frame_view",
"../../../api:array_view",
"../../../common_audio",
@ -265,9 +267,12 @@ rtc_library("rnn_vad_with_level_unittests") {
testonly = true
sources = [ "vad_with_level_unittest.cc" ]
deps = [
":common",
":rnn_vad_with_level",
"..:audio_frame_view",
"../../../rtc_base:gunit_helpers",
"../../../rtc_base:safe_compare",
"../../../test:test_support",
]
}

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@ -49,6 +49,9 @@ constexpr float kFullBufferLeakFactor = 1.f - 1.f / kFullBufferSizeMs;
constexpr float kInitialSpeechLevelEstimateDbfs = -30.f;
// Robust VAD probability and speech decisions.
constexpr float kDefaultSmoothedVadProbabilityAttack = 1.f;
// Saturation Protector settings.
float GetInitialSaturationMarginDb();
float GetExtraSaturationMarginOffsetDb();

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@ -17,6 +17,7 @@
#include "api/array_view.h"
#include "common_audio/include/audio_util.h"
#include "common_audio/resampler/include/push_resampler.h"
#include "modules/audio_processing/agc2/agc2_common.h"
#include "modules/audio_processing/agc2/rnn_vad/common.h"
#include "modules/audio_processing/agc2/rnn_vad/features_extraction.h"
#include "modules/audio_processing/agc2/rnn_vad/rnn.h"
@ -61,12 +62,32 @@ class Vad : public VoiceActivityDetector {
rnn_vad::RnnBasedVad rnn_vad_;
};
// Returns an updated version of `p_old` by using instant decay and the given
// `attack` on a new VAD probability value `p_new`.
float SmoothedVadProbability(float p_old, float p_new, float attack) {
RTC_DCHECK_GT(attack, 0.f);
RTC_DCHECK_LE(attack, 1.f);
if (p_new < p_old || attack == 1.f) {
// Instant decay (or no smoothing).
return p_new;
} else {
// Attack phase.
return attack * p_new + (1.f - attack) * p_old;
}
}
} // namespace
VadLevelAnalyzer::VadLevelAnalyzer() : vad_(std::make_unique<Vad>()) {}
VadLevelAnalyzer::VadLevelAnalyzer()
: VadLevelAnalyzer(kDefaultSmoothedVadProbabilityAttack,
std::make_unique<Vad>()) {}
VadLevelAnalyzer::VadLevelAnalyzer(std::unique_ptr<VoiceActivityDetector> vad)
: vad_(std::move(vad)) {
VadLevelAnalyzer::VadLevelAnalyzer(float vad_probability_attack)
: VadLevelAnalyzer(vad_probability_attack, std::make_unique<Vad>()) {}
VadLevelAnalyzer::VadLevelAnalyzer(float vad_probability_attack,
std::unique_ptr<VoiceActivityDetector> vad)
: vad_(std::move(vad)), vad_probability_attack_(vad_probability_attack) {
RTC_DCHECK(vad_);
}
@ -74,13 +95,18 @@ VadLevelAnalyzer::~VadLevelAnalyzer() = default;
VadLevelAnalyzer::Result VadLevelAnalyzer::AnalyzeFrame(
AudioFrameView<const float> frame) {
// Compute levels.
float peak = 0.f;
float rms = 0.f;
for (const auto& x : frame.channel(0)) {
peak = std::max(std::fabs(x), peak);
rms += x * x;
}
return {vad_->ComputeProbability(frame),
// Compute smoothed speech probability.
vad_probability_ = SmoothedVadProbability(
/*p_old=*/vad_probability_, /*p_new=*/vad_->ComputeProbability(frame),
vad_probability_attack_);
return {vad_probability_,
FloatS16ToDbfs(std::sqrt(rms / frame.samples_per_channel())),
FloatS16ToDbfs(peak)};
}

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@ -36,8 +36,10 @@ class VadLevelAnalyzer {
// Ctor. Uses the default VAD.
VadLevelAnalyzer();
explicit VadLevelAnalyzer(float vad_probability_attack);
// Ctor. Uses a custom `vad`.
explicit VadLevelAnalyzer(std::unique_ptr<VoiceActivityDetector> vad);
VadLevelAnalyzer(float vad_probability_attack,
std::unique_ptr<VoiceActivityDetector> vad);
VadLevelAnalyzer(const VadLevelAnalyzer&) = delete;
VadLevelAnalyzer& operator=(const VadLevelAnalyzer&) = delete;
~VadLevelAnalyzer();
@ -47,6 +49,8 @@ class VadLevelAnalyzer {
private:
std::unique_ptr<VoiceActivityDetector> vad_;
const float vad_probability_attack_;
float vad_probability_ = 0.f;
};
} // namespace webrtc

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@ -10,30 +10,121 @@
#include "modules/audio_processing/agc2/vad_with_level.h"
#include <memory>
#include <vector>
#include "modules/audio_processing/agc2/agc2_common.h"
#include "modules/audio_processing/include/audio_frame_view.h"
#include "rtc_base/gunit.h"
#include "rtc_base/numerics/safe_compare.h"
#include "test/gmock.h"
namespace webrtc {
namespace {
TEST(AutomaticGainController2VadWithLevelEstimator,
PeakLevelGreaterThanRmsLevel) {
constexpr size_t kSampleRateHz = 8000;
using ::testing::AnyNumber;
using ::testing::ReturnRoundRobin;
// 10 ms input frame, constant except for one peak value.
// Handcrafted so that the average is lower than the peak value.
std::array<float, kSampleRateHz / 100> frame;
frame.fill(1000.f);
frame[10] = 2000.f;
float* const channel0 = frame.data();
AudioFrameView<float> frame_view(&channel0, 1, frame.size());
constexpr float kInstantAttack = 1.f;
constexpr float kSlowAttack = 0.1f;
constexpr int kSampleRateHz = 8000;
class MockVad : public VadLevelAnalyzer::VoiceActivityDetector {
public:
MOCK_METHOD(float,
ComputeProbability,
(AudioFrameView<const float> frame),
(override));
};
// Creates a `VadLevelAnalyzer` injecting a mock VAD which repeatedly returns
// the next value from `speech_probabilities` until it reaches the end and will
// restart from the beginning.
std::unique_ptr<VadLevelAnalyzer> CreateVadLevelAnalyzerWithMockVad(
float vad_probability_attack,
const std::vector<float>& speech_probabilities) {
auto vad = std::make_unique<MockVad>();
EXPECT_CALL(*vad, ComputeProbability)
.Times(AnyNumber())
.WillRepeatedly(ReturnRoundRobin(speech_probabilities));
return std::make_unique<VadLevelAnalyzer>(vad_probability_attack,
std::move(vad));
}
// 10 ms mono frame.
struct FrameWithView {
// Ctor. Initializes the frame samples with `value`.
FrameWithView(float value = 0.f)
: channel0(samples.data()),
view(&channel0, /*num_channels=*/1, samples.size()) {
samples.fill(value);
}
std::array<float, kSampleRateHz / 100> samples;
const float* const channel0;
const AudioFrameView<const float> view;
};
TEST(AutomaticGainController2VadLevelAnalyzer, PeakLevelGreaterThanRmsLevel) {
// Handcrafted frame so that the average is lower than the peak value.
FrameWithView frame(1000.f); // Constant frame.
frame.samples[10] = 2000.f; // Except for one peak value.
// Compute audio frame levels (the VAD result is ignored).
VadLevelAnalyzer analyzer;
auto levels_and_vad_prob = analyzer.AnalyzeFrame(frame_view);
auto levels_and_vad_prob = analyzer.AnalyzeFrame(frame.view);
// Compare peak and RMS levels.
EXPECT_LT(levels_and_vad_prob.rms_dbfs, levels_and_vad_prob.peak_dbfs);
}
// Checks that the unprocessed and the smoothed speech probabilities match when
// instant attack is used.
TEST(AutomaticGainController2VadLevelAnalyzer, NoSpeechProbabilitySmoothing) {
const std::vector<float> speech_probabilities{0.709f, 0.484f, 0.882f, 0.167f,
0.44f, 0.525f, 0.858f, 0.314f,
0.653f, 0.965f, 0.413f, 0.f};
auto analyzer =
CreateVadLevelAnalyzerWithMockVad(kInstantAttack, speech_probabilities);
FrameWithView frame;
for (int i = 0; rtc::SafeLt(i, speech_probabilities.size()); ++i) {
SCOPED_TRACE(i);
EXPECT_EQ(speech_probabilities[i],
analyzer->AnalyzeFrame(frame.view).speech_probability);
}
}
// Checks that the smoothed speech probability does not instantly converge to
// the unprocessed one when slow attack is used.
TEST(AutomaticGainController2VadLevelAnalyzer,
SlowAttackSpeechProbabilitySmoothing) {
const std::vector<float> speech_probabilities{0.f, 0.f, 1.f, 1.f, 1.f, 1.f};
auto analyzer =
CreateVadLevelAnalyzerWithMockVad(kSlowAttack, speech_probabilities);
FrameWithView frame;
float prev_probability = 0.f;
for (int i = 0; rtc::SafeLt(i, speech_probabilities.size()); ++i) {
SCOPED_TRACE(i);
const float smoothed_probability =
analyzer->AnalyzeFrame(frame.view).speech_probability;
EXPECT_LT(smoothed_probability, 1.f); // Not enough time to reach 1.
EXPECT_LE(prev_probability, smoothed_probability); // Converge towards 1.
prev_probability = smoothed_probability;
}
}
// Checks that the smoothed speech probability instantly decays to the
// unprocessed one when slow attack is used.
TEST(AutomaticGainController2VadLevelAnalyzer, SpeechProbabilityInstantDecay) {
const std::vector<float> speech_probabilities{1.f, 1.f, 1.f, 1.f, 1.f, 0.f};
auto analyzer =
CreateVadLevelAnalyzerWithMockVad(kSlowAttack, speech_probabilities);
FrameWithView frame;
for (int i = 0; rtc::SafeLt(i, speech_probabilities.size() - 1); ++i) {
analyzer->AnalyzeFrame(frame.view);
}
EXPECT_EQ(0.f, analyzer->AnalyzeFrame(frame.view).speech_probability);
}
} // namespace
} // namespace webrtc