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/*
* 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/adaptive_mode_level_estimator.h"
#include "modules/audio_processing/agc2/agc2_common.h"
#include "modules/audio_processing/logging/apm_data_dumper.h"
#include "rtc_base/checks.h"
#include "rtc_base/logging.h"
#include "rtc_base/numerics/safe_minmax.h"
namespace webrtc {
namespace {
using LevelEstimatorType =
AudioProcessing::Config::GainController2::LevelEstimator;
float ClampLevelEstimateDbfs(float level_estimate_dbfs) {
return rtc::SafeClamp<float>(level_estimate_dbfs, -90.f, 30.f);
}
} // namespace
bool AdaptiveModeLevelEstimator::LevelEstimatorState::operator==(
const AdaptiveModeLevelEstimator::LevelEstimatorState& b) const {
return time_to_confidence_ms == b.time_to_confidence_ms &&
level_dbfs.numerator == b.level_dbfs.numerator &&
level_dbfs.denominator == b.level_dbfs.denominator;
}
float AdaptiveModeLevelEstimator::LevelEstimatorState::Ratio::GetRatio() const {
RTC_DCHECK_NE(denominator, 0.f);
return numerator / denominator;
}
AdaptiveModeLevelEstimator::AdaptiveModeLevelEstimator(
ApmDataDumper* apm_data_dumper)
: AdaptiveModeLevelEstimator(
apm_data_dumper,
kDefaultLevelEstimatorAdjacentSpeechFramesThreshold) {}
AdaptiveModeLevelEstimator::AdaptiveModeLevelEstimator(
ApmDataDumper* apm_data_dumper,
int adjacent_speech_frames_threshold)
: apm_data_dumper_(apm_data_dumper),
adjacent_speech_frames_threshold_(adjacent_speech_frames_threshold),
level_dbfs_(ClampLevelEstimateDbfs(kInitialSpeechLevelEstimateDbfs)) {
RTC_DCHECK(apm_data_dumper_);
RTC_DCHECK_GE(adjacent_speech_frames_threshold_, 1);
Reset();
}
void AdaptiveModeLevelEstimator::Update(
const VadLevelAnalyzer::Result& vad_level) {
RTC_DCHECK_GT(vad_level.rms_dbfs, -150.f);
RTC_DCHECK_LT(vad_level.rms_dbfs, 50.f);
RTC_DCHECK_GT(vad_level.peak_dbfs, -150.f);
RTC_DCHECK_LT(vad_level.peak_dbfs, 50.f);
RTC_DCHECK_GE(vad_level.speech_probability, 0.f);
RTC_DCHECK_LE(vad_level.speech_probability, 1.f);
if (vad_level.speech_probability < kVadConfidenceThreshold) {
// Not a speech frame.
if (adjacent_speech_frames_threshold_ > 1) {
// When two or more adjacent speech frames are required in order to update
// the state, we need to decide whether to discard or confirm the updates
// based on the speech sequence length.
if (num_adjacent_speech_frames_ >= adjacent_speech_frames_threshold_) {
// First non-speech frame after a long enough sequence of speech frames.
// Update the reliable state.
reliable_state_ = preliminary_state_;
} else if (num_adjacent_speech_frames_ > 0) {
// First non-speech frame after a too short sequence of speech frames.
// Reset to the last reliable state.
preliminary_state_ = reliable_state_;
}
}
num_adjacent_speech_frames_ = 0;
} else {
// Speech frame observed.
num_adjacent_speech_frames_++;
// Update preliminary level estimate.
RTC_DCHECK_GE(preliminary_state_.time_to_confidence_ms, 0);
const bool buffer_is_full = preliminary_state_.time_to_confidence_ms == 0;
if (!buffer_is_full) {
preliminary_state_.time_to_confidence_ms -= kFrameDurationMs;
}
// Weighted average of levels with speech probability as weight.
RTC_DCHECK_GT(vad_level.speech_probability, 0.f);
const float leak_factor = buffer_is_full ? kLevelEstimatorLeakFactor : 1.f;
preliminary_state_.level_dbfs.numerator =
preliminary_state_.level_dbfs.numerator * leak_factor +
vad_level.rms_dbfs * vad_level.speech_probability;
preliminary_state_.level_dbfs.denominator =
preliminary_state_.level_dbfs.denominator * leak_factor +
vad_level.speech_probability;
const float level_dbfs = preliminary_state_.level_dbfs.GetRatio();
if (num_adjacent_speech_frames_ >= adjacent_speech_frames_threshold_) {
// `preliminary_state_` is now reliable. Update the last level estimation.
level_dbfs_ = ClampLevelEstimateDbfs(level_dbfs);
}
}
DumpDebugData();
}
bool AdaptiveModeLevelEstimator::IsConfident() const {
if (adjacent_speech_frames_threshold_ == 1) {
// Ignore `reliable_state_` when a single frame is enough to update the
// level estimate (because it is not used).
return preliminary_state_.time_to_confidence_ms == 0;
}
// Once confident, it remains confident.
RTC_DCHECK(reliable_state_.time_to_confidence_ms != 0 ||
preliminary_state_.time_to_confidence_ms == 0);
// During the first long enough speech sequence, `reliable_state_` must be
// ignored since `preliminary_state_` is used.
return reliable_state_.time_to_confidence_ms == 0 ||
(num_adjacent_speech_frames_ >= adjacent_speech_frames_threshold_ &&
preliminary_state_.time_to_confidence_ms == 0);
}
void AdaptiveModeLevelEstimator::Reset() {
ResetLevelEstimatorState(preliminary_state_);
ResetLevelEstimatorState(reliable_state_);
level_dbfs_ = ClampLevelEstimateDbfs(kInitialSpeechLevelEstimateDbfs);
num_adjacent_speech_frames_ = 0;
}
void AdaptiveModeLevelEstimator::ResetLevelEstimatorState(
LevelEstimatorState& state) const {
state.time_to_confidence_ms = kLevelEstimatorTimeToConfidenceMs;
state.level_dbfs.numerator = kInitialSpeechLevelEstimateDbfs;
state.level_dbfs.denominator = 1.0f;
}
void AdaptiveModeLevelEstimator::DumpDebugData() const {
apm_data_dumper_->DumpRaw(
"agc2_adaptive_level_estimator_num_adjacent_speech_frames",
num_adjacent_speech_frames_);
apm_data_dumper_->DumpRaw(
"agc2_adaptive_level_estimator_preliminary_level_estimate_num",
preliminary_state_.level_dbfs.numerator);
apm_data_dumper_->DumpRaw(
"agc2_adaptive_level_estimator_preliminary_level_estimate_den",
preliminary_state_.level_dbfs.denominator);
apm_data_dumper_->DumpRaw(
"agc2_adaptive_level_estimator_preliminary_time_to_confidence_ms",
preliminary_state_.time_to_confidence_ms);
apm_data_dumper_->DumpRaw(
"agc2_adaptive_level_estimator_reliable_time_to_confidence_ms",
reliable_state_.time_to_confidence_ms);
}
} // namespace webrtc