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/*
* Copyright (c) 2016 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/residual_echo_detector.h"
#include <algorithm>
#include <numeric>
#include <optional>
#include "modules/audio_processing/logging/apm_data_dumper.h"
#include "rtc_base/checks.h"
#include "rtc_base/logging.h"
#include "system_wrappers/include/metrics.h"
namespace {
float Power(rtc::ArrayView<const float> input) {
if (input.empty()) {
return 0.f;
}
return std::inner_product(input.begin(), input.end(), input.begin(), 0.f) /
input.size();
}
constexpr size_t kLookbackFrames = 650;
// TODO(ivoc): Verify the size of this buffer.
constexpr size_t kRenderBufferSize = 30;
constexpr float kAlpha = 0.001f;
// 10 seconds of data, updated every 10 ms.
constexpr size_t kAggregationBufferSize = 10 * 100;
} // namespace
namespace webrtc {
std::atomic<int> ResidualEchoDetector::instance_count_(0);
ResidualEchoDetector::ResidualEchoDetector()
: data_dumper_(new ApmDataDumper(instance_count_.fetch_add(1) + 1)),
render_buffer_(kRenderBufferSize),
render_power_(kLookbackFrames),
render_power_mean_(kLookbackFrames),
render_power_std_dev_(kLookbackFrames),
covariances_(kLookbackFrames),
recent_likelihood_max_(kAggregationBufferSize) {}
ResidualEchoDetector::~ResidualEchoDetector() = default;
void ResidualEchoDetector::AnalyzeRenderAudio(
rtc::ArrayView<const float> render_audio) {
// Dump debug data assuming 48 kHz sample rate (if this assumption is not
// valid the dumped audio will need to be converted offline accordingly).
data_dumper_->DumpWav("ed_render", render_audio.size(), render_audio.data(),
48000, 1);
if (render_buffer_.Size() == 0) {
frames_since_zero_buffer_size_ = 0;
} else if (frames_since_zero_buffer_size_ >= kRenderBufferSize) {
// This can happen in a few cases: at the start of a call, due to a glitch
// or due to clock drift. The excess capture value will be ignored.
// TODO(ivoc): Include how often this happens in APM stats.
render_buffer_.Pop();
frames_since_zero_buffer_size_ = 0;
}
++frames_since_zero_buffer_size_;
float power = Power(render_audio);
render_buffer_.Push(power);
}
void ResidualEchoDetector::AnalyzeCaptureAudio(
rtc::ArrayView<const float> capture_audio) {
// Dump debug data assuming 48 kHz sample rate (if this assumption is not
// valid the dumped audio will need to be converted offline accordingly).
data_dumper_->DumpWav("ed_capture", capture_audio.size(),
capture_audio.data(), 48000, 1);
if (first_process_call_) {
// On the first process call (so the start of a call), we must flush the
// render buffer, otherwise the render data will be delayed.
render_buffer_.Clear();
first_process_call_ = false;
}
// Get the next render value.
const std::optional<float> buffered_render_power = render_buffer_.Pop();
if (!buffered_render_power) {
// This can happen in a few cases: at the start of a call, due to a glitch
// or due to clock drift. The excess capture value will be ignored.
// TODO(ivoc): Include how often this happens in APM stats.
return;
}
// Update the render statistics, and store the statistics in circular buffers.
render_statistics_.Update(*buffered_render_power);
RTC_DCHECK_LT(next_insertion_index_, kLookbackFrames);
render_power_[next_insertion_index_] = *buffered_render_power;
render_power_mean_[next_insertion_index_] = render_statistics_.mean();
render_power_std_dev_[next_insertion_index_] =
render_statistics_.std_deviation();
// Get the next capture value, update capture statistics and add the relevant
// values to the buffers.
const float capture_power = Power(capture_audio);
capture_statistics_.Update(capture_power);
const float capture_mean = capture_statistics_.mean();
const float capture_std_deviation = capture_statistics_.std_deviation();
// Update the covariance values and determine the new echo likelihood.
echo_likelihood_ = 0.f;
size_t read_index = next_insertion_index_;
int best_delay = -1;
for (size_t delay = 0; delay < covariances_.size(); ++delay) {
RTC_DCHECK_LT(read_index, render_power_.size());
covariances_[delay].Update(capture_power, capture_mean,
capture_std_deviation, render_power_[read_index],
render_power_mean_[read_index],
render_power_std_dev_[read_index]);
read_index = read_index > 0 ? read_index - 1 : kLookbackFrames - 1;
if (covariances_[delay].normalized_cross_correlation() > echo_likelihood_) {
echo_likelihood_ = covariances_[delay].normalized_cross_correlation();
best_delay = static_cast<int>(delay);
}
}
// This is a temporary log message to help find the underlying cause for echo
// likelihoods > 1.0.
// TODO(ivoc): Remove once the issue is resolved.
if (echo_likelihood_ > 1.1f) {
// Make sure we don't spam the log.
if (log_counter_ < 5 && best_delay != -1) {
size_t read_index = kLookbackFrames + next_insertion_index_ - best_delay;
if (read_index >= kLookbackFrames) {
read_index -= kLookbackFrames;
}
RTC_DCHECK_LT(read_index, render_power_.size());
RTC_LOG_F(LS_ERROR) << "Echo detector internal state: {"
"Echo likelihood: "
<< echo_likelihood_ << ", Best Delay: " << best_delay
<< ", Covariance: "
<< covariances_[best_delay].covariance()
<< ", Last capture power: " << capture_power
<< ", Capture mean: " << capture_mean
<< ", Capture_standard deviation: "
<< capture_std_deviation << ", Last render power: "
<< render_power_[read_index]
<< ", Render mean: " << render_power_mean_[read_index]
<< ", Render standard deviation: "
<< render_power_std_dev_[read_index]
<< ", Reliability: " << reliability_ << "}";
log_counter_++;
}
}
RTC_DCHECK_LT(echo_likelihood_, 1.1f);
reliability_ = (1.0f - kAlpha) * reliability_ + kAlpha * 1.0f;
echo_likelihood_ *= reliability_;
// This is a temporary fix to prevent echo likelihood values > 1.0.
// TODO(ivoc): Find the root cause of this issue and fix it.
echo_likelihood_ = std::min(echo_likelihood_, 1.0f);
int echo_percentage = static_cast<int>(echo_likelihood_ * 100);
RTC_HISTOGRAM_COUNTS("WebRTC.Audio.ResidualEchoDetector.EchoLikelihood",
echo_percentage, 0, 100, 100 /* number of bins */);
// Update the buffer of recent likelihood values.
recent_likelihood_max_.Update(echo_likelihood_);
// Update the next insertion index.
next_insertion_index_ = next_insertion_index_ < (kLookbackFrames - 1)
? next_insertion_index_ + 1
: 0;
}
void ResidualEchoDetector::Initialize(int /*capture_sample_rate_hz*/,
int /*num_capture_channels*/,
int /*render_sample_rate_hz*/,
int /*num_render_channels*/) {
render_buffer_.Clear();
std::fill(render_power_.begin(), render_power_.end(), 0.f);
std::fill(render_power_mean_.begin(), render_power_mean_.end(), 0.f);
std::fill(render_power_std_dev_.begin(), render_power_std_dev_.end(), 0.f);
render_statistics_.Clear();
capture_statistics_.Clear();
recent_likelihood_max_.Clear();
for (auto& cov : covariances_) {
cov.Clear();
}
echo_likelihood_ = 0.f;
next_insertion_index_ = 0;
reliability_ = 0.f;
}
EchoDetector::Metrics ResidualEchoDetector::GetMetrics() const {
EchoDetector::Metrics metrics;
metrics.echo_likelihood = echo_likelihood_;
metrics.echo_likelihood_recent_max = recent_likelihood_max_.max();
return metrics;
}
} // namespace webrtc