889 lines
38 KiB
C++
889 lines
38 KiB
C++
/*
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* Copyright (c) 2012 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_coding/neteq/expand.h"
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#include <assert.h>
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#include <string.h> // memset
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#include <algorithm> // min, max
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#include <limits> // numeric_limits<T>
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#include "common_audio/signal_processing/include/signal_processing_library.h"
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#include "modules/audio_coding/neteq/audio_multi_vector.h"
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#include "modules/audio_coding/neteq/background_noise.h"
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#include "modules/audio_coding/neteq/cross_correlation.h"
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#include "modules/audio_coding/neteq/dsp_helper.h"
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#include "modules/audio_coding/neteq/random_vector.h"
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#include "modules/audio_coding/neteq/statistics_calculator.h"
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#include "modules/audio_coding/neteq/sync_buffer.h"
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#include "rtc_base/numerics/safe_conversions.h"
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namespace webrtc {
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Expand::Expand(BackgroundNoise* background_noise,
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SyncBuffer* sync_buffer,
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RandomVector* random_vector,
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StatisticsCalculator* statistics,
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int fs,
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size_t num_channels)
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: random_vector_(random_vector),
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sync_buffer_(sync_buffer),
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first_expand_(true),
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fs_hz_(fs),
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num_channels_(num_channels),
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consecutive_expands_(0),
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background_noise_(background_noise),
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statistics_(statistics),
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overlap_length_(5 * fs / 8000),
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lag_index_direction_(0),
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current_lag_index_(0),
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stop_muting_(false),
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expand_duration_samples_(0),
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channel_parameters_(new ChannelParameters[num_channels_]) {
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assert(fs == 8000 || fs == 16000 || fs == 32000 || fs == 48000);
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assert(fs <= static_cast<int>(kMaxSampleRate)); // Should not be possible.
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assert(num_channels_ > 0);
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memset(expand_lags_, 0, sizeof(expand_lags_));
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Reset();
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}
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Expand::~Expand() = default;
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void Expand::Reset() {
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first_expand_ = true;
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consecutive_expands_ = 0;
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max_lag_ = 0;
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for (size_t ix = 0; ix < num_channels_; ++ix) {
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channel_parameters_[ix].expand_vector0.Clear();
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channel_parameters_[ix].expand_vector1.Clear();
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}
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}
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int Expand::Process(AudioMultiVector* output) {
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int16_t random_vector[kMaxSampleRate / 8000 * 120 + 30];
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int16_t scaled_random_vector[kMaxSampleRate / 8000 * 125];
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static const int kTempDataSize = 3600;
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int16_t temp_data[kTempDataSize]; // TODO(hlundin) Remove this.
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int16_t* voiced_vector_storage = temp_data;
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int16_t* voiced_vector = &voiced_vector_storage[overlap_length_];
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static const size_t kNoiseLpcOrder = BackgroundNoise::kMaxLpcOrder;
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int16_t unvoiced_array_memory[kNoiseLpcOrder + kMaxSampleRate / 8000 * 125];
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int16_t* unvoiced_vector = unvoiced_array_memory + kUnvoicedLpcOrder;
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int16_t* noise_vector = unvoiced_array_memory + kNoiseLpcOrder;
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int fs_mult = fs_hz_ / 8000;
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if (first_expand_) {
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// Perform initial setup if this is the first expansion since last reset.
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AnalyzeSignal(random_vector);
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first_expand_ = false;
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expand_duration_samples_ = 0;
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} else {
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// This is not the first expansion, parameters are already estimated.
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// Extract a noise segment.
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size_t rand_length = max_lag_;
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// This only applies to SWB where length could be larger than 256.
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assert(rand_length <= kMaxSampleRate / 8000 * 120 + 30);
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GenerateRandomVector(2, rand_length, random_vector);
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}
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// Generate signal.
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UpdateLagIndex();
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// Voiced part.
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// Generate a weighted vector with the current lag.
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size_t expansion_vector_length = max_lag_ + overlap_length_;
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size_t current_lag = expand_lags_[current_lag_index_];
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// Copy lag+overlap data.
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size_t expansion_vector_position =
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expansion_vector_length - current_lag - overlap_length_;
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size_t temp_length = current_lag + overlap_length_;
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for (size_t channel_ix = 0; channel_ix < num_channels_; ++channel_ix) {
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ChannelParameters& parameters = channel_parameters_[channel_ix];
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if (current_lag_index_ == 0) {
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// Use only expand_vector0.
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assert(expansion_vector_position + temp_length <=
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parameters.expand_vector0.Size());
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parameters.expand_vector0.CopyTo(temp_length, expansion_vector_position,
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voiced_vector_storage);
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} else if (current_lag_index_ == 1) {
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std::unique_ptr<int16_t[]> temp_0(new int16_t[temp_length]);
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parameters.expand_vector0.CopyTo(temp_length, expansion_vector_position,
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temp_0.get());
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std::unique_ptr<int16_t[]> temp_1(new int16_t[temp_length]);
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parameters.expand_vector1.CopyTo(temp_length, expansion_vector_position,
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temp_1.get());
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// Mix 3/4 of expand_vector0 with 1/4 of expand_vector1.
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WebRtcSpl_ScaleAndAddVectorsWithRound(temp_0.get(), 3, temp_1.get(), 1, 2,
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voiced_vector_storage, temp_length);
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} else if (current_lag_index_ == 2) {
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// Mix 1/2 of expand_vector0 with 1/2 of expand_vector1.
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assert(expansion_vector_position + temp_length <=
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parameters.expand_vector0.Size());
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assert(expansion_vector_position + temp_length <=
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parameters.expand_vector1.Size());
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std::unique_ptr<int16_t[]> temp_0(new int16_t[temp_length]);
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parameters.expand_vector0.CopyTo(temp_length, expansion_vector_position,
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temp_0.get());
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std::unique_ptr<int16_t[]> temp_1(new int16_t[temp_length]);
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parameters.expand_vector1.CopyTo(temp_length, expansion_vector_position,
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temp_1.get());
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WebRtcSpl_ScaleAndAddVectorsWithRound(temp_0.get(), 1, temp_1.get(), 1, 1,
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voiced_vector_storage, temp_length);
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}
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// Get tapering window parameters. Values are in Q15.
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int16_t muting_window, muting_window_increment;
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int16_t unmuting_window, unmuting_window_increment;
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if (fs_hz_ == 8000) {
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muting_window = DspHelper::kMuteFactorStart8kHz;
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muting_window_increment = DspHelper::kMuteFactorIncrement8kHz;
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unmuting_window = DspHelper::kUnmuteFactorStart8kHz;
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unmuting_window_increment = DspHelper::kUnmuteFactorIncrement8kHz;
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} else if (fs_hz_ == 16000) {
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muting_window = DspHelper::kMuteFactorStart16kHz;
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muting_window_increment = DspHelper::kMuteFactorIncrement16kHz;
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unmuting_window = DspHelper::kUnmuteFactorStart16kHz;
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unmuting_window_increment = DspHelper::kUnmuteFactorIncrement16kHz;
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} else if (fs_hz_ == 32000) {
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muting_window = DspHelper::kMuteFactorStart32kHz;
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muting_window_increment = DspHelper::kMuteFactorIncrement32kHz;
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unmuting_window = DspHelper::kUnmuteFactorStart32kHz;
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unmuting_window_increment = DspHelper::kUnmuteFactorIncrement32kHz;
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} else { // fs_ == 48000
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muting_window = DspHelper::kMuteFactorStart48kHz;
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muting_window_increment = DspHelper::kMuteFactorIncrement48kHz;
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unmuting_window = DspHelper::kUnmuteFactorStart48kHz;
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unmuting_window_increment = DspHelper::kUnmuteFactorIncrement48kHz;
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}
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// Smooth the expanded if it has not been muted to a low amplitude and
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// |current_voice_mix_factor| is larger than 0.5.
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if ((parameters.mute_factor > 819) &&
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(parameters.current_voice_mix_factor > 8192)) {
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size_t start_ix = sync_buffer_->Size() - overlap_length_;
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for (size_t i = 0; i < overlap_length_; i++) {
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// Do overlap add between new vector and overlap.
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(*sync_buffer_)[channel_ix][start_ix + i] =
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(((*sync_buffer_)[channel_ix][start_ix + i] * muting_window) +
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(((parameters.mute_factor * voiced_vector_storage[i]) >> 14) *
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unmuting_window) +
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16384) >>
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15;
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muting_window += muting_window_increment;
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unmuting_window += unmuting_window_increment;
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}
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} else if (parameters.mute_factor == 0) {
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// The expanded signal will consist of only comfort noise if
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// mute_factor = 0. Set the output length to 15 ms for best noise
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// production.
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// TODO(hlundin): This has been disabled since the length of
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// parameters.expand_vector0 and parameters.expand_vector1 no longer
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// match with expand_lags_, causing invalid reads and writes. Is it a good
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// idea to enable this again, and solve the vector size problem?
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// max_lag_ = fs_mult * 120;
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// expand_lags_[0] = fs_mult * 120;
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// expand_lags_[1] = fs_mult * 120;
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// expand_lags_[2] = fs_mult * 120;
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}
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// Unvoiced part.
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// Filter |scaled_random_vector| through |ar_filter_|.
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memcpy(unvoiced_vector - kUnvoicedLpcOrder, parameters.ar_filter_state,
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sizeof(int16_t) * kUnvoicedLpcOrder);
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int32_t add_constant = 0;
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if (parameters.ar_gain_scale > 0) {
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add_constant = 1 << (parameters.ar_gain_scale - 1);
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}
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WebRtcSpl_AffineTransformVector(scaled_random_vector, random_vector,
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parameters.ar_gain, add_constant,
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parameters.ar_gain_scale, current_lag);
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WebRtcSpl_FilterARFastQ12(scaled_random_vector, unvoiced_vector,
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parameters.ar_filter, kUnvoicedLpcOrder + 1,
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current_lag);
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memcpy(parameters.ar_filter_state,
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&(unvoiced_vector[current_lag - kUnvoicedLpcOrder]),
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sizeof(int16_t) * kUnvoicedLpcOrder);
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// Combine voiced and unvoiced contributions.
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// Set a suitable cross-fading slope.
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// For lag =
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// <= 31 * fs_mult => go from 1 to 0 in about 8 ms;
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// (>= 31 .. <= 63) * fs_mult => go from 1 to 0 in about 16 ms;
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// >= 64 * fs_mult => go from 1 to 0 in about 32 ms.
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// temp_shift = getbits(max_lag_) - 5.
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int temp_shift =
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(31 - WebRtcSpl_NormW32(rtc::dchecked_cast<int32_t>(max_lag_))) - 5;
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int16_t mix_factor_increment = 256 >> temp_shift;
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if (stop_muting_) {
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mix_factor_increment = 0;
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}
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// Create combined signal by shifting in more and more of unvoiced part.
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temp_shift = 8 - temp_shift; // = getbits(mix_factor_increment).
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size_t temp_length =
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(parameters.current_voice_mix_factor - parameters.voice_mix_factor) >>
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temp_shift;
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temp_length = std::min(temp_length, current_lag);
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DspHelper::CrossFade(voiced_vector, unvoiced_vector, temp_length,
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¶meters.current_voice_mix_factor,
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mix_factor_increment, temp_data);
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// End of cross-fading period was reached before end of expanded signal
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// path. Mix the rest with a fixed mixing factor.
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if (temp_length < current_lag) {
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if (mix_factor_increment != 0) {
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parameters.current_voice_mix_factor = parameters.voice_mix_factor;
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}
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int16_t temp_scale = 16384 - parameters.current_voice_mix_factor;
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WebRtcSpl_ScaleAndAddVectorsWithRound(
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voiced_vector + temp_length, parameters.current_voice_mix_factor,
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unvoiced_vector + temp_length, temp_scale, 14,
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temp_data + temp_length, current_lag - temp_length);
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}
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// Select muting slope depending on how many consecutive expands we have
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// done.
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if (consecutive_expands_ == 3) {
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// Let the mute factor decrease from 1.0 to 0.95 in 6.25 ms.
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// mute_slope = 0.0010 / fs_mult in Q20.
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parameters.mute_slope = std::max(parameters.mute_slope, 1049 / fs_mult);
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}
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if (consecutive_expands_ == 7) {
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// Let the mute factor decrease from 1.0 to 0.90 in 6.25 ms.
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// mute_slope = 0.0020 / fs_mult in Q20.
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parameters.mute_slope = std::max(parameters.mute_slope, 2097 / fs_mult);
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}
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// Mute segment according to slope value.
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if ((consecutive_expands_ != 0) || !parameters.onset) {
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// Mute to the previous level, then continue with the muting.
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WebRtcSpl_AffineTransformVector(
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temp_data, temp_data, parameters.mute_factor, 8192, 14, current_lag);
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if (!stop_muting_) {
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DspHelper::MuteSignal(temp_data, parameters.mute_slope, current_lag);
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// Shift by 6 to go from Q20 to Q14.
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// TODO(hlundin): Adding 8192 before shifting 6 steps seems wrong.
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// Legacy.
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int16_t gain = static_cast<int16_t>(
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16384 - (((current_lag * parameters.mute_slope) + 8192) >> 6));
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gain = ((gain * parameters.mute_factor) + 8192) >> 14;
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// Guard against getting stuck with very small (but sometimes audible)
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// gain.
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if ((consecutive_expands_ > 3) && (gain >= parameters.mute_factor)) {
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parameters.mute_factor = 0;
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} else {
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parameters.mute_factor = gain;
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}
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}
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}
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// Background noise part.
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background_noise_->GenerateBackgroundNoise(
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random_vector, channel_ix, channel_parameters_[channel_ix].mute_slope,
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TooManyExpands(), current_lag, unvoiced_array_memory);
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// Add background noise to the combined voiced-unvoiced signal.
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for (size_t i = 0; i < current_lag; i++) {
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temp_data[i] = temp_data[i] + noise_vector[i];
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}
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if (channel_ix == 0) {
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output->AssertSize(current_lag);
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} else {
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assert(output->Size() == current_lag);
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}
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(*output)[channel_ix].OverwriteAt(temp_data, current_lag, 0);
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}
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// Increase call number and cap it.
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consecutive_expands_ = consecutive_expands_ >= kMaxConsecutiveExpands
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? kMaxConsecutiveExpands
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: consecutive_expands_ + 1;
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expand_duration_samples_ += output->Size();
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// Clamp the duration counter at 2 seconds.
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expand_duration_samples_ = std::min(expand_duration_samples_,
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rtc::dchecked_cast<size_t>(fs_hz_ * 2));
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return 0;
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}
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void Expand::SetParametersForNormalAfterExpand() {
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current_lag_index_ = 0;
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lag_index_direction_ = 0;
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stop_muting_ = true; // Do not mute signal any more.
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statistics_->LogDelayedPacketOutageEvent(expand_duration_samples_, fs_hz_);
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statistics_->EndExpandEvent(fs_hz_);
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}
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void Expand::SetParametersForMergeAfterExpand() {
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current_lag_index_ = -1; /* out of the 3 possible ones */
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lag_index_direction_ = 1; /* make sure we get the "optimal" lag */
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stop_muting_ = true;
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statistics_->EndExpandEvent(fs_hz_);
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}
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bool Expand::Muted() const {
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if (first_expand_ || stop_muting_)
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return false;
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RTC_DCHECK(channel_parameters_);
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for (size_t ch = 0; ch < num_channels_; ++ch) {
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if (channel_parameters_[ch].mute_factor != 0)
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return false;
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}
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return true;
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}
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size_t Expand::overlap_length() const {
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return overlap_length_;
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}
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void Expand::InitializeForAnExpandPeriod() {
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lag_index_direction_ = 1;
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current_lag_index_ = -1;
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stop_muting_ = false;
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random_vector_->set_seed_increment(1);
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consecutive_expands_ = 0;
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for (size_t ix = 0; ix < num_channels_; ++ix) {
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channel_parameters_[ix].current_voice_mix_factor = 16384; // 1.0 in Q14.
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channel_parameters_[ix].mute_factor = 16384; // 1.0 in Q14.
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// Start with 0 gain for background noise.
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background_noise_->SetMuteFactor(ix, 0);
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}
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}
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bool Expand::TooManyExpands() {
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return consecutive_expands_ >= kMaxConsecutiveExpands;
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}
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void Expand::AnalyzeSignal(int16_t* random_vector) {
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int32_t auto_correlation[kUnvoicedLpcOrder + 1];
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int16_t reflection_coeff[kUnvoicedLpcOrder];
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int16_t correlation_vector[kMaxSampleRate / 8000 * 102];
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size_t best_correlation_index[kNumCorrelationCandidates];
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int16_t best_correlation[kNumCorrelationCandidates];
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size_t best_distortion_index[kNumCorrelationCandidates];
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int16_t best_distortion[kNumCorrelationCandidates];
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int32_t correlation_vector2[(99 * kMaxSampleRate / 8000) + 1];
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int32_t best_distortion_w32[kNumCorrelationCandidates];
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static const size_t kNoiseLpcOrder = BackgroundNoise::kMaxLpcOrder;
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int16_t unvoiced_array_memory[kNoiseLpcOrder + kMaxSampleRate / 8000 * 125];
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int16_t* unvoiced_vector = unvoiced_array_memory + kUnvoicedLpcOrder;
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int fs_mult = fs_hz_ / 8000;
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// Pre-calculate common multiplications with fs_mult.
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size_t fs_mult_4 = static_cast<size_t>(fs_mult * 4);
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size_t fs_mult_20 = static_cast<size_t>(fs_mult * 20);
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size_t fs_mult_120 = static_cast<size_t>(fs_mult * 120);
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size_t fs_mult_dist_len = fs_mult * kDistortionLength;
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size_t fs_mult_lpc_analysis_len = fs_mult * kLpcAnalysisLength;
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const size_t signal_length = static_cast<size_t>(256 * fs_mult);
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const size_t audio_history_position = sync_buffer_->Size() - signal_length;
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std::unique_ptr<int16_t[]> audio_history(new int16_t[signal_length]);
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(*sync_buffer_)[0].CopyTo(signal_length, audio_history_position,
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audio_history.get());
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// Initialize.
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InitializeForAnExpandPeriod();
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// Calculate correlation in downsampled domain (4 kHz sample rate).
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size_t correlation_length = 51; // TODO(hlundin): Legacy bit-exactness.
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// If it is decided to break bit-exactness |correlation_length| should be
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// initialized to the return value of Correlation().
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Correlation(audio_history.get(), signal_length, correlation_vector);
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// Find peaks in correlation vector.
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DspHelper::PeakDetection(correlation_vector, correlation_length,
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kNumCorrelationCandidates, fs_mult,
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best_correlation_index, best_correlation);
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// Adjust peak locations; cross-correlation lags start at 2.5 ms
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// (20 * fs_mult samples).
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best_correlation_index[0] += fs_mult_20;
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best_correlation_index[1] += fs_mult_20;
|
|
best_correlation_index[2] += fs_mult_20;
|
|
|
|
// Calculate distortion around the |kNumCorrelationCandidates| best lags.
|
|
int distortion_scale = 0;
|
|
for (size_t i = 0; i < kNumCorrelationCandidates; i++) {
|
|
size_t min_index =
|
|
std::max(fs_mult_20, best_correlation_index[i] - fs_mult_4);
|
|
size_t max_index =
|
|
std::min(fs_mult_120 - 1, best_correlation_index[i] + fs_mult_4);
|
|
best_distortion_index[i] = DspHelper::MinDistortion(
|
|
&(audio_history[signal_length - fs_mult_dist_len]), min_index,
|
|
max_index, fs_mult_dist_len, &best_distortion_w32[i]);
|
|
distortion_scale = std::max(16 - WebRtcSpl_NormW32(best_distortion_w32[i]),
|
|
distortion_scale);
|
|
}
|
|
// Shift the distortion values to fit in 16 bits.
|
|
WebRtcSpl_VectorBitShiftW32ToW16(best_distortion, kNumCorrelationCandidates,
|
|
best_distortion_w32, distortion_scale);
|
|
|
|
// Find the maximizing index |i| of the cost function
|
|
// f[i] = best_correlation[i] / best_distortion[i].
|
|
int32_t best_ratio = std::numeric_limits<int32_t>::min();
|
|
size_t best_index = std::numeric_limits<size_t>::max();
|
|
for (size_t i = 0; i < kNumCorrelationCandidates; ++i) {
|
|
int32_t ratio;
|
|
if (best_distortion[i] > 0) {
|
|
ratio = (best_correlation[i] * (1 << 16)) / best_distortion[i];
|
|
} else if (best_correlation[i] == 0) {
|
|
ratio = 0; // No correlation set result to zero.
|
|
} else {
|
|
ratio = std::numeric_limits<int32_t>::max(); // Denominator is zero.
|
|
}
|
|
if (ratio > best_ratio) {
|
|
best_index = i;
|
|
best_ratio = ratio;
|
|
}
|
|
}
|
|
|
|
size_t distortion_lag = best_distortion_index[best_index];
|
|
size_t correlation_lag = best_correlation_index[best_index];
|
|
max_lag_ = std::max(distortion_lag, correlation_lag);
|
|
|
|
// Calculate the exact best correlation in the range between
|
|
// |correlation_lag| and |distortion_lag|.
|
|
correlation_length = std::max(std::min(distortion_lag + 10, fs_mult_120),
|
|
static_cast<size_t>(60 * fs_mult));
|
|
|
|
size_t start_index = std::min(distortion_lag, correlation_lag);
|
|
size_t correlation_lags = static_cast<size_t>(
|
|
WEBRTC_SPL_ABS_W16((distortion_lag - correlation_lag)) + 1);
|
|
assert(correlation_lags <= static_cast<size_t>(99 * fs_mult + 1));
|
|
|
|
for (size_t channel_ix = 0; channel_ix < num_channels_; ++channel_ix) {
|
|
ChannelParameters& parameters = channel_parameters_[channel_ix];
|
|
if (channel_ix > 0) {
|
|
// When channel_ix == 0, audio_history contains the correct audio. For the
|
|
// other cases, we will have to copy the correct channel into
|
|
// audio_history.
|
|
(*sync_buffer_)[channel_ix].CopyTo(signal_length, audio_history_position,
|
|
audio_history.get());
|
|
}
|
|
|
|
// Calculate suitable scaling.
|
|
int16_t signal_max = WebRtcSpl_MaxAbsValueW16(
|
|
&audio_history[signal_length - correlation_length - start_index -
|
|
correlation_lags],
|
|
correlation_length + start_index + correlation_lags - 1);
|
|
int correlation_scale =
|
|
(31 - WebRtcSpl_NormW32(signal_max * signal_max)) +
|
|
(31 - WebRtcSpl_NormW32(static_cast<int32_t>(correlation_length))) - 31;
|
|
correlation_scale = std::max(0, correlation_scale);
|
|
|
|
// Calculate the correlation, store in |correlation_vector2|.
|
|
WebRtcSpl_CrossCorrelation(
|
|
correlation_vector2,
|
|
&(audio_history[signal_length - correlation_length]),
|
|
&(audio_history[signal_length - correlation_length - start_index]),
|
|
correlation_length, correlation_lags, correlation_scale, -1);
|
|
|
|
// Find maximizing index.
|
|
best_index = WebRtcSpl_MaxIndexW32(correlation_vector2, correlation_lags);
|
|
int32_t max_correlation = correlation_vector2[best_index];
|
|
// Compensate index with start offset.
|
|
best_index = best_index + start_index;
|
|
|
|
// Calculate energies.
|
|
int32_t energy1 = WebRtcSpl_DotProductWithScale(
|
|
&(audio_history[signal_length - correlation_length]),
|
|
&(audio_history[signal_length - correlation_length]),
|
|
correlation_length, correlation_scale);
|
|
int32_t energy2 = WebRtcSpl_DotProductWithScale(
|
|
&(audio_history[signal_length - correlation_length - best_index]),
|
|
&(audio_history[signal_length - correlation_length - best_index]),
|
|
correlation_length, correlation_scale);
|
|
|
|
// Calculate the correlation coefficient between the two portions of the
|
|
// signal.
|
|
int32_t corr_coefficient;
|
|
if ((energy1 > 0) && (energy2 > 0)) {
|
|
int energy1_scale = std::max(16 - WebRtcSpl_NormW32(energy1), 0);
|
|
int energy2_scale = std::max(16 - WebRtcSpl_NormW32(energy2), 0);
|
|
// Make sure total scaling is even (to simplify scale factor after sqrt).
|
|
if ((energy1_scale + energy2_scale) & 1) {
|
|
// If sum is odd, add 1 to make it even.
|
|
energy1_scale += 1;
|
|
}
|
|
int32_t scaled_energy1 = energy1 >> energy1_scale;
|
|
int32_t scaled_energy2 = energy2 >> energy2_scale;
|
|
int16_t sqrt_energy_product = static_cast<int16_t>(
|
|
WebRtcSpl_SqrtFloor(scaled_energy1 * scaled_energy2));
|
|
// Calculate max_correlation / sqrt(energy1 * energy2) in Q14.
|
|
int cc_shift = 14 - (energy1_scale + energy2_scale) / 2;
|
|
max_correlation = WEBRTC_SPL_SHIFT_W32(max_correlation, cc_shift);
|
|
corr_coefficient =
|
|
WebRtcSpl_DivW32W16(max_correlation, sqrt_energy_product);
|
|
// Cap at 1.0 in Q14.
|
|
corr_coefficient = std::min(16384, corr_coefficient);
|
|
} else {
|
|
corr_coefficient = 0;
|
|
}
|
|
|
|
// Extract the two vectors expand_vector0 and expand_vector1 from
|
|
// |audio_history|.
|
|
size_t expansion_length = max_lag_ + overlap_length_;
|
|
const int16_t* vector1 = &(audio_history[signal_length - expansion_length]);
|
|
const int16_t* vector2 = vector1 - distortion_lag;
|
|
// Normalize the second vector to the same energy as the first.
|
|
energy1 = WebRtcSpl_DotProductWithScale(vector1, vector1, expansion_length,
|
|
correlation_scale);
|
|
energy2 = WebRtcSpl_DotProductWithScale(vector2, vector2, expansion_length,
|
|
correlation_scale);
|
|
// Confirm that amplitude ratio sqrt(energy1 / energy2) is within 0.5 - 2.0,
|
|
// i.e., energy1 / energy2 is within 0.25 - 4.
|
|
int16_t amplitude_ratio;
|
|
if ((energy1 / 4 < energy2) && (energy1 > energy2 / 4)) {
|
|
// Energy constraint fulfilled. Use both vectors and scale them
|
|
// accordingly.
|
|
int32_t scaled_energy2 = std::max(16 - WebRtcSpl_NormW32(energy2), 0);
|
|
int32_t scaled_energy1 = scaled_energy2 - 13;
|
|
// Calculate scaled_energy1 / scaled_energy2 in Q13.
|
|
int32_t energy_ratio =
|
|
WebRtcSpl_DivW32W16(WEBRTC_SPL_SHIFT_W32(energy1, -scaled_energy1),
|
|
static_cast<int16_t>(energy2 >> scaled_energy2));
|
|
// Calculate sqrt ratio in Q13 (sqrt of en1/en2 in Q26).
|
|
amplitude_ratio =
|
|
static_cast<int16_t>(WebRtcSpl_SqrtFloor(energy_ratio << 13));
|
|
// Copy the two vectors and give them the same energy.
|
|
parameters.expand_vector0.Clear();
|
|
parameters.expand_vector0.PushBack(vector1, expansion_length);
|
|
parameters.expand_vector1.Clear();
|
|
if (parameters.expand_vector1.Size() < expansion_length) {
|
|
parameters.expand_vector1.Extend(expansion_length -
|
|
parameters.expand_vector1.Size());
|
|
}
|
|
std::unique_ptr<int16_t[]> temp_1(new int16_t[expansion_length]);
|
|
WebRtcSpl_AffineTransformVector(
|
|
temp_1.get(), const_cast<int16_t*>(vector2), amplitude_ratio, 4096,
|
|
13, expansion_length);
|
|
parameters.expand_vector1.OverwriteAt(temp_1.get(), expansion_length, 0);
|
|
} else {
|
|
// Energy change constraint not fulfilled. Only use last vector.
|
|
parameters.expand_vector0.Clear();
|
|
parameters.expand_vector0.PushBack(vector1, expansion_length);
|
|
// Copy from expand_vector0 to expand_vector1.
|
|
parameters.expand_vector0.CopyTo(¶meters.expand_vector1);
|
|
// Set the energy_ratio since it is used by muting slope.
|
|
if ((energy1 / 4 < energy2) || (energy2 == 0)) {
|
|
amplitude_ratio = 4096; // 0.5 in Q13.
|
|
} else {
|
|
amplitude_ratio = 16384; // 2.0 in Q13.
|
|
}
|
|
}
|
|
|
|
// Set the 3 lag values.
|
|
if (distortion_lag == correlation_lag) {
|
|
expand_lags_[0] = distortion_lag;
|
|
expand_lags_[1] = distortion_lag;
|
|
expand_lags_[2] = distortion_lag;
|
|
} else {
|
|
// |distortion_lag| and |correlation_lag| are not equal; use different
|
|
// combinations of the two.
|
|
// First lag is |distortion_lag| only.
|
|
expand_lags_[0] = distortion_lag;
|
|
// Second lag is the average of the two.
|
|
expand_lags_[1] = (distortion_lag + correlation_lag) / 2;
|
|
// Third lag is the average again, but rounding towards |correlation_lag|.
|
|
if (distortion_lag > correlation_lag) {
|
|
expand_lags_[2] = (distortion_lag + correlation_lag - 1) / 2;
|
|
} else {
|
|
expand_lags_[2] = (distortion_lag + correlation_lag + 1) / 2;
|
|
}
|
|
}
|
|
|
|
// Calculate the LPC and the gain of the filters.
|
|
|
|
// Calculate kUnvoicedLpcOrder + 1 lags of the auto-correlation function.
|
|
size_t temp_index =
|
|
signal_length - fs_mult_lpc_analysis_len - kUnvoicedLpcOrder;
|
|
// Copy signal to temporary vector to be able to pad with leading zeros.
|
|
int16_t* temp_signal =
|
|
new int16_t[fs_mult_lpc_analysis_len + kUnvoicedLpcOrder];
|
|
memset(temp_signal, 0,
|
|
sizeof(int16_t) * (fs_mult_lpc_analysis_len + kUnvoicedLpcOrder));
|
|
memcpy(&temp_signal[kUnvoicedLpcOrder],
|
|
&audio_history[temp_index + kUnvoicedLpcOrder],
|
|
sizeof(int16_t) * fs_mult_lpc_analysis_len);
|
|
CrossCorrelationWithAutoShift(
|
|
&temp_signal[kUnvoicedLpcOrder], &temp_signal[kUnvoicedLpcOrder],
|
|
fs_mult_lpc_analysis_len, kUnvoicedLpcOrder + 1, -1, auto_correlation);
|
|
delete[] temp_signal;
|
|
|
|
// Verify that variance is positive.
|
|
if (auto_correlation[0] > 0) {
|
|
// Estimate AR filter parameters using Levinson-Durbin algorithm;
|
|
// kUnvoicedLpcOrder + 1 filter coefficients.
|
|
int16_t stability =
|
|
WebRtcSpl_LevinsonDurbin(auto_correlation, parameters.ar_filter,
|
|
reflection_coeff, kUnvoicedLpcOrder);
|
|
|
|
// Keep filter parameters only if filter is stable.
|
|
if (stability != 1) {
|
|
// Set first coefficient to 4096 (1.0 in Q12).
|
|
parameters.ar_filter[0] = 4096;
|
|
// Set remaining |kUnvoicedLpcOrder| coefficients to zero.
|
|
WebRtcSpl_MemSetW16(parameters.ar_filter + 1, 0, kUnvoicedLpcOrder);
|
|
}
|
|
}
|
|
|
|
if (channel_ix == 0) {
|
|
// Extract a noise segment.
|
|
size_t noise_length;
|
|
if (distortion_lag < 40) {
|
|
noise_length = 2 * distortion_lag + 30;
|
|
} else {
|
|
noise_length = distortion_lag + 30;
|
|
}
|
|
if (noise_length <= RandomVector::kRandomTableSize) {
|
|
memcpy(random_vector, RandomVector::kRandomTable,
|
|
sizeof(int16_t) * noise_length);
|
|
} else {
|
|
// Only applies to SWB where length could be larger than
|
|
// |kRandomTableSize|.
|
|
memcpy(random_vector, RandomVector::kRandomTable,
|
|
sizeof(int16_t) * RandomVector::kRandomTableSize);
|
|
assert(noise_length <= kMaxSampleRate / 8000 * 120 + 30);
|
|
random_vector_->IncreaseSeedIncrement(2);
|
|
random_vector_->Generate(
|
|
noise_length - RandomVector::kRandomTableSize,
|
|
&random_vector[RandomVector::kRandomTableSize]);
|
|
}
|
|
}
|
|
|
|
// Set up state vector and calculate scale factor for unvoiced filtering.
|
|
memcpy(parameters.ar_filter_state,
|
|
&(audio_history[signal_length - kUnvoicedLpcOrder]),
|
|
sizeof(int16_t) * kUnvoicedLpcOrder);
|
|
memcpy(unvoiced_vector - kUnvoicedLpcOrder,
|
|
&(audio_history[signal_length - 128 - kUnvoicedLpcOrder]),
|
|
sizeof(int16_t) * kUnvoicedLpcOrder);
|
|
WebRtcSpl_FilterMAFastQ12(&audio_history[signal_length - 128],
|
|
unvoiced_vector, parameters.ar_filter,
|
|
kUnvoicedLpcOrder + 1, 128);
|
|
const int unvoiced_max_abs = [&] {
|
|
const int16_t max_abs = WebRtcSpl_MaxAbsValueW16(unvoiced_vector, 128);
|
|
// Since WebRtcSpl_MaxAbsValueW16 returns 2^15 - 1 when the input contains
|
|
// -2^15, we have to conservatively bump the return value by 1
|
|
// if it is 2^15 - 1.
|
|
return max_abs == WEBRTC_SPL_WORD16_MAX ? max_abs + 1 : max_abs;
|
|
}();
|
|
// Pick the smallest n such that 2^n > unvoiced_max_abs; then the maximum
|
|
// value of the dot product is less than 2^7 * 2^(2*n) = 2^(2*n + 7), so to
|
|
// prevent overflows we want 2n + 7 <= 31, which means we should shift by
|
|
// 2n + 7 - 31 bits, if this value is greater than zero.
|
|
int unvoiced_prescale =
|
|
std::max(0, 2 * WebRtcSpl_GetSizeInBits(unvoiced_max_abs) - 24);
|
|
|
|
int32_t unvoiced_energy = WebRtcSpl_DotProductWithScale(
|
|
unvoiced_vector, unvoiced_vector, 128, unvoiced_prescale);
|
|
|
|
// Normalize |unvoiced_energy| to 28 or 29 bits to preserve sqrt() accuracy.
|
|
int16_t unvoiced_scale = WebRtcSpl_NormW32(unvoiced_energy) - 3;
|
|
// Make sure we do an odd number of shifts since we already have 7 shifts
|
|
// from dividing with 128 earlier. This will make the total scale factor
|
|
// even, which is suitable for the sqrt.
|
|
unvoiced_scale += ((unvoiced_scale & 0x1) ^ 0x1);
|
|
unvoiced_energy = WEBRTC_SPL_SHIFT_W32(unvoiced_energy, unvoiced_scale);
|
|
int16_t unvoiced_gain =
|
|
static_cast<int16_t>(WebRtcSpl_SqrtFloor(unvoiced_energy));
|
|
parameters.ar_gain_scale =
|
|
13 + (unvoiced_scale + 7 - unvoiced_prescale) / 2;
|
|
parameters.ar_gain = unvoiced_gain;
|
|
|
|
// Calculate voice_mix_factor from corr_coefficient.
|
|
// Let x = corr_coefficient. Then, we compute:
|
|
// if (x > 0.48)
|
|
// voice_mix_factor = (-5179 + 19931x - 16422x^2 + 5776x^3) / 4096;
|
|
// else
|
|
// voice_mix_factor = 0;
|
|
if (corr_coefficient > 7875) {
|
|
int16_t x1, x2, x3;
|
|
// |corr_coefficient| is in Q14.
|
|
x1 = static_cast<int16_t>(corr_coefficient);
|
|
x2 = (x1 * x1) >> 14; // Shift 14 to keep result in Q14.
|
|
x3 = (x1 * x2) >> 14;
|
|
static const int kCoefficients[4] = {-5179, 19931, -16422, 5776};
|
|
int32_t temp_sum = kCoefficients[0] * 16384;
|
|
temp_sum += kCoefficients[1] * x1;
|
|
temp_sum += kCoefficients[2] * x2;
|
|
temp_sum += kCoefficients[3] * x3;
|
|
parameters.voice_mix_factor =
|
|
static_cast<int16_t>(std::min(temp_sum / 4096, 16384));
|
|
parameters.voice_mix_factor =
|
|
std::max(parameters.voice_mix_factor, static_cast<int16_t>(0));
|
|
} else {
|
|
parameters.voice_mix_factor = 0;
|
|
}
|
|
|
|
// Calculate muting slope. Reuse value from earlier scaling of
|
|
// |expand_vector0| and |expand_vector1|.
|
|
int16_t slope = amplitude_ratio;
|
|
if (slope > 12288) {
|
|
// slope > 1.5.
|
|
// Calculate (1 - (1 / slope)) / distortion_lag =
|
|
// (slope - 1) / (distortion_lag * slope).
|
|
// |slope| is in Q13, so 1 corresponds to 8192. Shift up to Q25 before
|
|
// the division.
|
|
// Shift the denominator from Q13 to Q5 before the division. The result of
|
|
// the division will then be in Q20.
|
|
int16_t denom =
|
|
rtc::saturated_cast<int16_t>((distortion_lag * slope) >> 8);
|
|
int temp_ratio = WebRtcSpl_DivW32W16((slope - 8192) << 12, denom);
|
|
if (slope > 14746) {
|
|
// slope > 1.8.
|
|
// Divide by 2, with proper rounding.
|
|
parameters.mute_slope = (temp_ratio + 1) / 2;
|
|
} else {
|
|
// Divide by 8, with proper rounding.
|
|
parameters.mute_slope = (temp_ratio + 4) / 8;
|
|
}
|
|
parameters.onset = true;
|
|
} else {
|
|
// Calculate (1 - slope) / distortion_lag.
|
|
// Shift |slope| by 7 to Q20 before the division. The result is in Q20.
|
|
parameters.mute_slope = WebRtcSpl_DivW32W16(
|
|
(8192 - slope) * 128, static_cast<int16_t>(distortion_lag));
|
|
if (parameters.voice_mix_factor <= 13107) {
|
|
// Make sure the mute factor decreases from 1.0 to 0.9 in no more than
|
|
// 6.25 ms.
|
|
// mute_slope >= 0.005 / fs_mult in Q20.
|
|
parameters.mute_slope = std::max(5243 / fs_mult, parameters.mute_slope);
|
|
} else if (slope > 8028) {
|
|
parameters.mute_slope = 0;
|
|
}
|
|
parameters.onset = false;
|
|
}
|
|
}
|
|
}
|
|
|
|
Expand::ChannelParameters::ChannelParameters()
|
|
: mute_factor(16384),
|
|
ar_gain(0),
|
|
ar_gain_scale(0),
|
|
voice_mix_factor(0),
|
|
current_voice_mix_factor(0),
|
|
onset(false),
|
|
mute_slope(0) {
|
|
memset(ar_filter, 0, sizeof(ar_filter));
|
|
memset(ar_filter_state, 0, sizeof(ar_filter_state));
|
|
}
|
|
|
|
void Expand::Correlation(const int16_t* input,
|
|
size_t input_length,
|
|
int16_t* output) const {
|
|
// Set parameters depending on sample rate.
|
|
const int16_t* filter_coefficients;
|
|
size_t num_coefficients;
|
|
int16_t downsampling_factor;
|
|
if (fs_hz_ == 8000) {
|
|
num_coefficients = 3;
|
|
downsampling_factor = 2;
|
|
filter_coefficients = DspHelper::kDownsample8kHzTbl;
|
|
} else if (fs_hz_ == 16000) {
|
|
num_coefficients = 5;
|
|
downsampling_factor = 4;
|
|
filter_coefficients = DspHelper::kDownsample16kHzTbl;
|
|
} else if (fs_hz_ == 32000) {
|
|
num_coefficients = 7;
|
|
downsampling_factor = 8;
|
|
filter_coefficients = DspHelper::kDownsample32kHzTbl;
|
|
} else { // fs_hz_ == 48000.
|
|
num_coefficients = 7;
|
|
downsampling_factor = 12;
|
|
filter_coefficients = DspHelper::kDownsample48kHzTbl;
|
|
}
|
|
|
|
// Correlate from lag 10 to lag 60 in downsampled domain.
|
|
// (Corresponds to 20-120 for narrow-band, 40-240 for wide-band, and so on.)
|
|
static const size_t kCorrelationStartLag = 10;
|
|
static const size_t kNumCorrelationLags = 54;
|
|
static const size_t kCorrelationLength = 60;
|
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// Downsample to 4 kHz sample rate.
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static const size_t kDownsampledLength =
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kCorrelationStartLag + kNumCorrelationLags + kCorrelationLength;
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int16_t downsampled_input[kDownsampledLength];
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static const size_t kFilterDelay = 0;
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WebRtcSpl_DownsampleFast(
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input + input_length - kDownsampledLength * downsampling_factor,
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kDownsampledLength * downsampling_factor, downsampled_input,
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kDownsampledLength, filter_coefficients, num_coefficients,
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downsampling_factor, kFilterDelay);
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|
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// Normalize |downsampled_input| to using all 16 bits.
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int16_t max_value =
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WebRtcSpl_MaxAbsValueW16(downsampled_input, kDownsampledLength);
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int16_t norm_shift = 16 - WebRtcSpl_NormW32(max_value);
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WebRtcSpl_VectorBitShiftW16(downsampled_input, kDownsampledLength,
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downsampled_input, norm_shift);
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|
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int32_t correlation[kNumCorrelationLags];
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|
CrossCorrelationWithAutoShift(
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&downsampled_input[kDownsampledLength - kCorrelationLength],
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|
&downsampled_input[kDownsampledLength - kCorrelationLength -
|
|
kCorrelationStartLag],
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|
kCorrelationLength, kNumCorrelationLags, -1, correlation);
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|
|
|
// Normalize and move data from 32-bit to 16-bit vector.
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|
int32_t max_correlation =
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|
WebRtcSpl_MaxAbsValueW32(correlation, kNumCorrelationLags);
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int16_t norm_shift2 = static_cast<int16_t>(
|
|
std::max(18 - WebRtcSpl_NormW32(max_correlation), 0));
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|
WebRtcSpl_VectorBitShiftW32ToW16(output, kNumCorrelationLags, correlation,
|
|
norm_shift2);
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}
|
|
|
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void Expand::UpdateLagIndex() {
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current_lag_index_ = current_lag_index_ + lag_index_direction_;
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|
// Change direction if needed.
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|
if (current_lag_index_ <= 0) {
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|
lag_index_direction_ = 1;
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|
}
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|
if (current_lag_index_ >= kNumLags - 1) {
|
|
lag_index_direction_ = -1;
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|
}
|
|
}
|
|
|
|
Expand* ExpandFactory::Create(BackgroundNoise* background_noise,
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|
SyncBuffer* sync_buffer,
|
|
RandomVector* random_vector,
|
|
StatisticsCalculator* statistics,
|
|
int fs,
|
|
size_t num_channels) const {
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|
return new Expand(background_noise, sync_buffer, random_vector, statistics,
|
|
fs, num_channels);
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|
}
|
|
|
|
void Expand::GenerateRandomVector(int16_t seed_increment,
|
|
size_t length,
|
|
int16_t* random_vector) {
|
|
// TODO(turajs): According to hlundin The loop should not be needed. Should be
|
|
// just as good to generate all of the vector in one call.
|
|
size_t samples_generated = 0;
|
|
const size_t kMaxRandSamples = RandomVector::kRandomTableSize;
|
|
while (samples_generated < length) {
|
|
size_t rand_length = std::min(length - samples_generated, kMaxRandSamples);
|
|
random_vector_->IncreaseSeedIncrement(seed_increment);
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|
random_vector_->Generate(rand_length, &random_vector[samples_generated]);
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|
samples_generated += rand_length;
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|
}
|
|
}
|
|
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|
} // namespace webrtc
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