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 /* * Copyright (c) 2014 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/rms_level.h" #include #include #include #include "rtc_base/checks.h" namespace webrtc { namespace { static constexpr float kMaxSquaredLevel = 32768 * 32768; // kMinLevel is the level corresponding to kMinLevelDb, that is 10^(-127/10). static constexpr float kMinLevel = 1.995262314968883e-13f; // Calculates the normalized RMS value from a mean square value. The input // should be the sum of squared samples divided by the number of samples. The // value will be normalized to full range before computing the RMS, wich is // returned as a negated dBfs. That is, 0 is full amplitude while 127 is very // faint. int ComputeRms(float mean_square) { if (mean_square <= kMinLevel * kMaxSquaredLevel) { // Very faint; simply return the minimum value. return RmsLevel::kMinLevelDb; } // Normalize by the max level. const float mean_square_norm = mean_square / kMaxSquaredLevel; RTC_DCHECK_GT(mean_square_norm, kMinLevel); // 20log_10(x^0.5) = 10log_10(x) const float rms = 10.f * std::log10(mean_square_norm); RTC_DCHECK_LE(rms, 0.f); RTC_DCHECK_GT(rms, -RmsLevel::kMinLevelDb); // Return the negated value. return static_cast(-rms + 0.5f); } } // namespace RmsLevel::RmsLevel() { Reset(); } RmsLevel::~RmsLevel() = default; void RmsLevel::Reset() { sum_square_ = 0.f; sample_count_ = 0; max_sum_square_ = 0.f; block_size_ = absl::nullopt; } void RmsLevel::Analyze(rtc::ArrayView data) { if (data.empty()) { return; } CheckBlockSize(data.size()); const float sum_square = std::accumulate(data.begin(), data.end(), 0.f, [](float a, int16_t b) { return a + b * b; }); RTC_DCHECK_GE(sum_square, 0.f); sum_square_ += sum_square; sample_count_ += data.size(); max_sum_square_ = std::max(max_sum_square_, sum_square); } void RmsLevel::Analyze(rtc::ArrayView data) { if (data.empty()) { return; } CheckBlockSize(data.size()); float sum_square = 0.f; for (float data_k : data) { int16_t tmp = static_cast(std::min(std::max(data_k, -32768.f), 32767.f)); sum_square += tmp * tmp; } RTC_DCHECK_GE(sum_square, 0.f); sum_square_ += sum_square; sample_count_ += data.size(); max_sum_square_ = std::max(max_sum_square_, sum_square); } void RmsLevel::AnalyzeMuted(size_t length) { CheckBlockSize(length); sample_count_ += length; } int RmsLevel::Average() { int rms = (sample_count_ == 0) ? RmsLevel::kMinLevelDb : ComputeRms(sum_square_ / sample_count_); Reset(); return rms; } RmsLevel::Levels RmsLevel::AverageAndPeak() { // Note that block_size_ should by design always be non-empty when // sample_count_ != 0. Also, the * operator of absl::optional enforces this // with a DCHECK. Levels levels = (sample_count_ == 0) ? Levels{RmsLevel::kMinLevelDb, RmsLevel::kMinLevelDb} : Levels{ComputeRms(sum_square_ / sample_count_), ComputeRms(max_sum_square_ / *block_size_)}; Reset(); return levels; } void RmsLevel::CheckBlockSize(size_t block_size) { if (block_size_ != block_size) { Reset(); block_size_ = block_size; } } } // namespace webrtc