129 lines
3.6 KiB
C++
129 lines
3.6 KiB
C++
/*
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* Copyright (c) 2014 The WebRTC project authors. All Rights Reserved.
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*
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* Use of this source code is governed by a BSD-style license
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* that can be found in the LICENSE file in the root of the source
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* tree. An additional intellectual property rights grant can be found
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* in the file PATENTS. All contributing project authors may
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* be found in the AUTHORS file in the root of the source tree.
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*/
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#include "modules/audio_processing/rms_level.h"
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#include <algorithm>
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#include <cmath>
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#include <numeric>
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#include "rtc_base/checks.h"
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namespace webrtc {
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namespace {
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static constexpr float kMaxSquaredLevel = 32768 * 32768;
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// kMinLevel is the level corresponding to kMinLevelDb, that is 10^(-127/10).
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static constexpr float kMinLevel = 1.995262314968883e-13f;
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// Calculates the normalized RMS value from a mean square value. The input
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// should be the sum of squared samples divided by the number of samples. The
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// value will be normalized to full range before computing the RMS, wich is
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// returned as a negated dBfs. That is, 0 is full amplitude while 127 is very
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// faint.
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int ComputeRms(float mean_square) {
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if (mean_square <= kMinLevel * kMaxSquaredLevel) {
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// Very faint; simply return the minimum value.
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return RmsLevel::kMinLevelDb;
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}
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// Normalize by the max level.
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const float mean_square_norm = mean_square / kMaxSquaredLevel;
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RTC_DCHECK_GT(mean_square_norm, kMinLevel);
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// 20log_10(x^0.5) = 10log_10(x)
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const float rms = 10.f * std::log10(mean_square_norm);
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RTC_DCHECK_LE(rms, 0.f);
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RTC_DCHECK_GT(rms, -RmsLevel::kMinLevelDb);
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// Return the negated value.
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return static_cast<int>(-rms + 0.5f);
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}
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} // namespace
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RmsLevel::RmsLevel() {
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Reset();
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}
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RmsLevel::~RmsLevel() = default;
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void RmsLevel::Reset() {
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sum_square_ = 0.f;
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sample_count_ = 0;
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max_sum_square_ = 0.f;
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block_size_ = absl::nullopt;
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}
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void RmsLevel::Analyze(rtc::ArrayView<const int16_t> data) {
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if (data.empty()) {
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return;
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}
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CheckBlockSize(data.size());
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const float sum_square =
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std::accumulate(data.begin(), data.end(), 0.f,
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[](float a, int16_t b) { return a + b * b; });
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RTC_DCHECK_GE(sum_square, 0.f);
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sum_square_ += sum_square;
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sample_count_ += data.size();
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max_sum_square_ = std::max(max_sum_square_, sum_square);
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}
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void RmsLevel::Analyze(rtc::ArrayView<const float> data) {
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if (data.empty()) {
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return;
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}
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CheckBlockSize(data.size());
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float sum_square = 0.f;
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for (float data_k : data) {
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int16_t tmp =
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static_cast<int16_t>(std::min(std::max(data_k, -32768.f), 32767.f));
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sum_square += tmp * tmp;
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}
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RTC_DCHECK_GE(sum_square, 0.f);
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sum_square_ += sum_square;
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sample_count_ += data.size();
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max_sum_square_ = std::max(max_sum_square_, sum_square);
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}
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void RmsLevel::AnalyzeMuted(size_t length) {
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CheckBlockSize(length);
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sample_count_ += length;
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}
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int RmsLevel::Average() {
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int rms = (sample_count_ == 0) ? RmsLevel::kMinLevelDb
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: ComputeRms(sum_square_ / sample_count_);
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Reset();
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return rms;
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}
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RmsLevel::Levels RmsLevel::AverageAndPeak() {
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// Note that block_size_ should by design always be non-empty when
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// sample_count_ != 0. Also, the * operator of absl::optional enforces this
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// with a DCHECK.
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Levels levels = (sample_count_ == 0)
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? Levels{RmsLevel::kMinLevelDb, RmsLevel::kMinLevelDb}
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: Levels{ComputeRms(sum_square_ / sample_count_),
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ComputeRms(max_sum_square_ / *block_size_)};
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Reset();
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return levels;
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}
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void RmsLevel::CheckBlockSize(size_t block_size) {
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if (block_size_ != block_size) {
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Reset();
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block_size_ = block_size;
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}
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}
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} // namespace webrtc
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