| /* |
| * Copyright (c) 2012 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/agc/agc.h" |
| |
| #include <cmath> |
| #include <cstdlib> |
| |
| #include <algorithm> |
| #include <vector> |
| |
| #include "modules/audio_processing/agc/loudness_histogram.h" |
| #include "modules/audio_processing/agc/utility.h" |
| #include "modules/include/module_common_types.h" |
| #include "rtc_base/checks.h" |
| |
| namespace webrtc { |
| namespace { |
| |
| const int kDefaultLevelDbfs = -18; |
| const int kNumAnalysisFrames = 100; |
| const double kActivityThreshold = 0.3; |
| |
| } // namespace |
| |
| Agc::Agc() |
| : target_level_loudness_(Dbfs2Loudness(kDefaultLevelDbfs)), |
| target_level_dbfs_(kDefaultLevelDbfs), |
| histogram_(LoudnessHistogram::Create(kNumAnalysisFrames)), |
| inactive_histogram_(LoudnessHistogram::Create()) {} |
| |
| Agc::~Agc() {} |
| |
| float Agc::AnalyzePreproc(const int16_t* audio, size_t length) { |
| RTC_DCHECK_GT(length, 0); |
| size_t num_clipped = 0; |
| for (size_t i = 0; i < length; ++i) { |
| if (audio[i] == 32767 || audio[i] == -32768) |
| ++num_clipped; |
| } |
| return 1.0f * num_clipped / length; |
| } |
| |
| int Agc::Process(const int16_t* audio, size_t length, int sample_rate_hz) { |
| vad_.ProcessChunk(audio, length, sample_rate_hz); |
| const std::vector<double>& rms = vad_.chunkwise_rms(); |
| const std::vector<double>& probabilities = |
| vad_.chunkwise_voice_probabilities(); |
| RTC_DCHECK_EQ(rms.size(), probabilities.size()); |
| for (size_t i = 0; i < rms.size(); ++i) { |
| histogram_->Update(rms[i], probabilities[i]); |
| } |
| return 0; |
| } |
| |
| bool Agc::GetRmsErrorDb(int* error) { |
| if (!error) { |
| RTC_NOTREACHED(); |
| return false; |
| } |
| |
| if (histogram_->num_updates() < kNumAnalysisFrames) { |
| // We haven't yet received enough frames. |
| return false; |
| } |
| |
| if (histogram_->AudioContent() < kNumAnalysisFrames * kActivityThreshold) { |
| // We are likely in an inactive segment. |
| return false; |
| } |
| |
| double loudness = Linear2Loudness(histogram_->CurrentRms()); |
| *error = std::floor(Loudness2Db(target_level_loudness_ - loudness) + 0.5); |
| histogram_->Reset(); |
| return true; |
| } |
| |
| void Agc::Reset() { |
| histogram_->Reset(); |
| } |
| |
| int Agc::set_target_level_dbfs(int level) { |
| // TODO(turajs): just some arbitrary sanity check. We can come up with better |
| // limits. The upper limit should be chosen such that the risk of clipping is |
| // low. The lower limit should not result in a too quiet signal. |
| if (level >= 0 || level <= -100) |
| return -1; |
| target_level_dbfs_ = level; |
| target_level_loudness_ = Dbfs2Loudness(level); |
| return 0; |
| } |
| |
| int Agc::target_level_dbfs() const { |
| return target_level_dbfs_; |
| } |
| |
| float Agc::voice_probability() const { |
| return vad_.last_voice_probability(); |
| } |
| |
| } // namespace webrtc |