blob: b54ae564da7d009f73361d3886a2b65c5b56dfc7 [file] [log] [blame]
* 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/vad_with_level.h"
#include <algorithm>
#include <array>
#include <cmath>
#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"
#include "rtc_base/checks.h"
namespace webrtc {
namespace {
using VoiceActivityDetector = VadLevelAnalyzer::VoiceActivityDetector;
// Default VAD that combines a resampler and the RNN VAD.
// Computes the speech probability on the first channel.
class Vad : public VoiceActivityDetector {
explicit Vad(const AvailableCpuFeatures& cpu_features)
: features_extractor_(cpu_features), rnn_vad_(cpu_features) {}
Vad(const Vad&) = delete;
Vad& operator=(const Vad&) = delete;
~Vad() = default;
float ComputeProbability(AudioFrameView<const float> frame) override {
// The source number of channels is 1, because we always use the 1st
// channel.
/*sample_rate_hz=*/static_cast<int>(frame.samples_per_channel() * 100),
std::array<float, rnn_vad::kFrameSize10ms24kHz> work_frame;
// Feed the 1st channel to the resampler.
resampler_.Resample(, frame.samples_per_channel(),, rnn_vad::kFrameSize10ms24kHz);
std::array<float, rnn_vad::kFeatureVectorSize> feature_vector;
const bool is_silence = features_extractor_.CheckSilenceComputeFeatures(
work_frame, feature_vector);
return rnn_vad_.ComputeVadProbability(feature_vector, is_silence);
PushResampler<float> resampler_;
rnn_vad::FeaturesExtractor features_extractor_;
rnn_vad::RnnVad 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(kDefaultSmoothedVadProbabilityAttack,
GetAvailableCpuFeatures()) {}
VadLevelAnalyzer::VadLevelAnalyzer(float vad_probability_attack,
const AvailableCpuFeatures& cpu_features)
: VadLevelAnalyzer(vad_probability_attack,
std::make_unique<Vad>(cpu_features)) {}
VadLevelAnalyzer::VadLevelAnalyzer(float vad_probability_attack,
std::unique_ptr<VoiceActivityDetector> vad)
: vad_(std::move(vad)), vad_probability_attack_(vad_probability_attack) {
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 : {
peak = std::max(std::fabs(x), peak);
rms += x * x;
// Compute smoothed speech probability.
vad_probability_ = SmoothedVadProbability(
/*p_old=*/vad_probability_, /*p_new=*/vad_->ComputeProbability(frame),
return {vad_probability_,
FloatS16ToDbfs(std::sqrt(rms / frame.samples_per_channel())),
} // namespace webrtc