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session-android/jni/webrtc/modules/audio_coding/neteq/expand.cc
Moxie Marlinspike d83a3d71bc Support for Signal calls. 
Merge in RedPhone

// FREEBIE
2015-09-30 14:30:09 -07:00

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/*
* 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 "webrtc/modules/audio_coding/neteq/expand.h"
#include <assert.h>
#include <string.h> // memset
#include <algorithm> // min, max
#include <limits> // numeric_limits<T>
#include "webrtc/common_audio/signal_processing/include/signal_processing_library.h"
#include "webrtc/modules/audio_coding/neteq/background_noise.h"
#include "webrtc/modules/audio_coding/neteq/dsp_helper.h"
#include "webrtc/modules/audio_coding/neteq/random_vector.h"
#include "webrtc/modules/audio_coding/neteq/sync_buffer.h"
namespace webrtc {
void Expand::Reset() {
first_expand_ = true;
consecutive_expands_ = 0;
max_lag_ = 0;
for (size_t ix = 0; ix < num_channels_; ++ix) {
channel_parameters_[ix].expand_vector0.Clear();
channel_parameters_[ix].expand_vector1.Clear();
}
}
int Expand::Process(AudioMultiVector* output) {
int16_t random_vector[kMaxSampleRate / 8000 * 120 + 30];
int16_t scaled_random_vector[kMaxSampleRate / 8000 * 125];
static const int kTempDataSize = 3600;
int16_t temp_data[kTempDataSize]; // TODO(hlundin) Remove this.
int16_t* voiced_vector_storage = temp_data;
int16_t* voiced_vector = &voiced_vector_storage[overlap_length_];
static const int kNoiseLpcOrder = BackgroundNoise::kMaxLpcOrder;
int16_t unvoiced_array_memory[kNoiseLpcOrder + kMaxSampleRate / 8000 * 125];
int16_t* unvoiced_vector = unvoiced_array_memory + kUnvoicedLpcOrder;
int16_t* noise_vector = unvoiced_array_memory + kNoiseLpcOrder;
int fs_mult = fs_hz_ / 8000;
if (first_expand_) {
// Perform initial setup if this is the first expansion since last reset.
AnalyzeSignal(random_vector);
first_expand_ = false;
} else {
// This is not the first expansion, parameters are already estimated.
// Extract a noise segment.
int16_t rand_length = max_lag_;
// This only applies to SWB where length could be larger than 256.
assert(rand_length <= kMaxSampleRate / 8000 * 120 + 30);
GenerateRandomVector(2, rand_length, random_vector);
}
// Generate signal.
UpdateLagIndex();
// Voiced part.
// Generate a weighted vector with the current lag.
size_t expansion_vector_length = max_lag_ + overlap_length_;
size_t current_lag = expand_lags_[current_lag_index_];
// Copy lag+overlap data.
size_t expansion_vector_position = expansion_vector_length - current_lag -
overlap_length_;
size_t temp_length = current_lag + overlap_length_;
for (size_t channel_ix = 0; channel_ix < num_channels_; ++channel_ix) {
ChannelParameters& parameters = channel_parameters_[channel_ix];
if (current_lag_index_ == 0) {
// Use only expand_vector0.
assert(expansion_vector_position + temp_length <=
parameters.expand_vector0.Size());
memcpy(voiced_vector_storage,
&parameters.expand_vector0[expansion_vector_position],
sizeof(int16_t) * temp_length);
} else if (current_lag_index_ == 1) {
// Mix 3/4 of expand_vector0 with 1/4 of expand_vector1.
WebRtcSpl_ScaleAndAddVectorsWithRound(
&parameters.expand_vector0[expansion_vector_position], 3,
&parameters.expand_vector1[expansion_vector_position], 1, 2,
voiced_vector_storage, static_cast<int>(temp_length));
} else if (current_lag_index_ == 2) {
// Mix 1/2 of expand_vector0 with 1/2 of expand_vector1.
assert(expansion_vector_position + temp_length <=
parameters.expand_vector0.Size());
assert(expansion_vector_position + temp_length <=
parameters.expand_vector1.Size());
WebRtcSpl_ScaleAndAddVectorsWithRound(
&parameters.expand_vector0[expansion_vector_position], 1,
&parameters.expand_vector1[expansion_vector_position], 1, 1,
voiced_vector_storage, static_cast<int>(temp_length));
}
// Get tapering window parameters. Values are in Q15.
int16_t muting_window, muting_window_increment;
int16_t unmuting_window, unmuting_window_increment;
if (fs_hz_ == 8000) {
muting_window = DspHelper::kMuteFactorStart8kHz;
muting_window_increment = DspHelper::kMuteFactorIncrement8kHz;
unmuting_window = DspHelper::kUnmuteFactorStart8kHz;
unmuting_window_increment = DspHelper::kUnmuteFactorIncrement8kHz;
} else if (fs_hz_ == 16000) {
muting_window = DspHelper::kMuteFactorStart16kHz;
muting_window_increment = DspHelper::kMuteFactorIncrement16kHz;
unmuting_window = DspHelper::kUnmuteFactorStart16kHz;
unmuting_window_increment = DspHelper::kUnmuteFactorIncrement16kHz;
} else if (fs_hz_ == 32000) {
muting_window = DspHelper::kMuteFactorStart32kHz;
muting_window_increment = DspHelper::kMuteFactorIncrement32kHz;
unmuting_window = DspHelper::kUnmuteFactorStart32kHz;
unmuting_window_increment = DspHelper::kUnmuteFactorIncrement32kHz;
} else { // fs_ == 48000
muting_window = DspHelper::kMuteFactorStart48kHz;
muting_window_increment = DspHelper::kMuteFactorIncrement48kHz;
unmuting_window = DspHelper::kUnmuteFactorStart48kHz;
unmuting_window_increment = DspHelper::kUnmuteFactorIncrement48kHz;
}
// Smooth the expanded if it has not been muted to a low amplitude and
// |current_voice_mix_factor| is larger than 0.5.
if ((parameters.mute_factor > 819) &&
(parameters.current_voice_mix_factor > 8192)) {
size_t start_ix = sync_buffer_->Size() - overlap_length_;
for (size_t i = 0; i < overlap_length_; i++) {
// Do overlap add between new vector and overlap.
(*sync_buffer_)[channel_ix][start_ix + i] =
(((*sync_buffer_)[channel_ix][start_ix + i] * muting_window) +
(((parameters.mute_factor * voiced_vector_storage[i]) >> 14) *
unmuting_window) + 16384) >> 15;
muting_window += muting_window_increment;
unmuting_window += unmuting_window_increment;
}
} else if (parameters.mute_factor == 0) {
// The expanded signal will consist of only comfort noise if
// mute_factor = 0. Set the output length to 15 ms for best noise
// production.
// TODO(hlundin): This has been disabled since the length of
// parameters.expand_vector0 and parameters.expand_vector1 no longer
// match with expand_lags_, causing invalid reads and writes. Is it a good
// idea to enable this again, and solve the vector size problem?
// max_lag_ = fs_mult * 120;
// expand_lags_[0] = fs_mult * 120;
// expand_lags_[1] = fs_mult * 120;
// expand_lags_[2] = fs_mult * 120;
}
// Unvoiced part.
// Filter |scaled_random_vector| through |ar_filter_|.
memcpy(unvoiced_vector - kUnvoicedLpcOrder, parameters.ar_filter_state,
sizeof(int16_t) * kUnvoicedLpcOrder);
int32_t add_constant = 0;
if (parameters.ar_gain_scale > 0) {
add_constant = 1 << (parameters.ar_gain_scale - 1);
}
WebRtcSpl_AffineTransformVector(scaled_random_vector, random_vector,
parameters.ar_gain, add_constant,
parameters.ar_gain_scale,
static_cast<int>(current_lag));
WebRtcSpl_FilterARFastQ12(scaled_random_vector, unvoiced_vector,
parameters.ar_filter, kUnvoicedLpcOrder + 1,
static_cast<int>(current_lag));
memcpy(parameters.ar_filter_state,
&(unvoiced_vector[current_lag - kUnvoicedLpcOrder]),
sizeof(int16_t) * kUnvoicedLpcOrder);
// Combine voiced and unvoiced contributions.
// Set a suitable cross-fading slope.
// For lag =
// <= 31 * fs_mult => go from 1 to 0 in about 8 ms;
// (>= 31 .. <= 63) * fs_mult => go from 1 to 0 in about 16 ms;
// >= 64 * fs_mult => go from 1 to 0 in about 32 ms.
// temp_shift = getbits(max_lag_) - 5.
int temp_shift = (31 - WebRtcSpl_NormW32(max_lag_)) - 5;
int16_t mix_factor_increment = 256 >> temp_shift;
if (stop_muting_) {
mix_factor_increment = 0;
}
// Create combined signal by shifting in more and more of unvoiced part.
temp_shift = 8 - temp_shift; // = getbits(mix_factor_increment).
size_t temp_lenght = (parameters.current_voice_mix_factor -
parameters.voice_mix_factor) >> temp_shift;
temp_lenght = std::min(temp_lenght, current_lag);
DspHelper::CrossFade(voiced_vector, unvoiced_vector, temp_lenght,
&parameters.current_voice_mix_factor,
mix_factor_increment, temp_data);
// End of cross-fading period was reached before end of expanded signal
// path. Mix the rest with a fixed mixing factor.
if (temp_lenght < current_lag) {
if (mix_factor_increment != 0) {
parameters.current_voice_mix_factor = parameters.voice_mix_factor;
}
int temp_scale = 16384 - parameters.current_voice_mix_factor;
WebRtcSpl_ScaleAndAddVectorsWithRound(
voiced_vector + temp_lenght, parameters.current_voice_mix_factor,
unvoiced_vector + temp_lenght, temp_scale, 14,
temp_data + temp_lenght, static_cast<int>(current_lag - temp_lenght));
}
// Select muting slope depending on how many consecutive expands we have
// done.
if (consecutive_expands_ == 3) {
// Let the mute factor decrease from 1.0 to 0.95 in 6.25 ms.
// mute_slope = 0.0010 / fs_mult in Q20.
parameters.mute_slope = std::max(parameters.mute_slope,
static_cast<int16_t>(1049 / fs_mult));
}
if (consecutive_expands_ == 7) {
// Let the mute factor decrease from 1.0 to 0.90 in 6.25 ms.
// mute_slope = 0.0020 / fs_mult in Q20.
parameters.mute_slope = std::max(parameters.mute_slope,
static_cast<int16_t>(2097 / fs_mult));
}
// Mute segment according to slope value.
if ((consecutive_expands_ != 0) || !parameters.onset) {
// Mute to the previous level, then continue with the muting.
WebRtcSpl_AffineTransformVector(temp_data, temp_data,
parameters.mute_factor, 8192,
14, static_cast<int>(current_lag));
if (!stop_muting_) {
DspHelper::MuteSignal(temp_data, parameters.mute_slope, current_lag);
// Shift by 6 to go from Q20 to Q14.
// TODO(hlundin): Adding 8192 before shifting 6 steps seems wrong.
// Legacy.
int16_t gain = static_cast<int16_t>(16384 -
(((current_lag * parameters.mute_slope) + 8192) >> 6));
gain = ((gain * parameters.mute_factor) + 8192) >> 14;
// Guard against getting stuck with very small (but sometimes audible)
// gain.
if ((consecutive_expands_ > 3) && (gain >= parameters.mute_factor)) {
parameters.mute_factor = 0;
} else {
parameters.mute_factor = gain;
}
}
}
// Background noise part.
GenerateBackgroundNoise(random_vector,
channel_ix,
channel_parameters_[channel_ix].mute_slope,
TooManyExpands(),
current_lag,
unvoiced_array_memory);
// Add background noise to the combined voiced-unvoiced signal.
for (size_t i = 0; i < current_lag; i++) {
temp_data[i] = temp_data[i] + noise_vector[i];
}
if (channel_ix == 0) {
output->AssertSize(current_lag);
} else {
assert(output->Size() == current_lag);
}
memcpy(&(*output)[channel_ix][0], temp_data,
sizeof(temp_data[0]) * current_lag);
}
// Increase call number and cap it.
consecutive_expands_ = consecutive_expands_ >= kMaxConsecutiveExpands ?
kMaxConsecutiveExpands : consecutive_expands_ + 1;
return 0;
}
void Expand::SetParametersForNormalAfterExpand() {
current_lag_index_ = 0;
lag_index_direction_ = 0;
stop_muting_ = true; // Do not mute signal any more.
}
void Expand::SetParametersForMergeAfterExpand() {
current_lag_index_ = -1; /* out of the 3 possible ones */
lag_index_direction_ = 1; /* make sure we get the "optimal" lag */
stop_muting_ = true;
}
void Expand::InitializeForAnExpandPeriod() {
lag_index_direction_ = 1;
current_lag_index_ = -1;
stop_muting_ = false;
random_vector_->set_seed_increment(1);
consecutive_expands_ = 0;
for (size_t ix = 0; ix < num_channels_; ++ix) {
channel_parameters_[ix].current_voice_mix_factor = 16384; // 1.0 in Q14.
channel_parameters_[ix].mute_factor = 16384; // 1.0 in Q14.
// Start with 0 gain for background noise.
background_noise_->SetMuteFactor(ix, 0);
}
}
bool Expand::TooManyExpands() {
return consecutive_expands_ >= kMaxConsecutiveExpands;
}
void Expand::AnalyzeSignal(int16_t* random_vector) {
int32_t auto_correlation[kUnvoicedLpcOrder + 1];
int16_t reflection_coeff[kUnvoicedLpcOrder];
int16_t correlation_vector[kMaxSampleRate / 8000 * 102];
int best_correlation_index[kNumCorrelationCandidates];
int16_t best_correlation[kNumCorrelationCandidates];
int16_t best_distortion_index[kNumCorrelationCandidates];
int16_t best_distortion[kNumCorrelationCandidates];
int32_t correlation_vector2[(99 * kMaxSampleRate / 8000) + 1];
int32_t best_distortion_w32[kNumCorrelationCandidates];
static const int kNoiseLpcOrder = BackgroundNoise::kMaxLpcOrder;
int16_t unvoiced_array_memory[kNoiseLpcOrder + kMaxSampleRate / 8000 * 125];
int16_t* unvoiced_vector = unvoiced_array_memory + kUnvoicedLpcOrder;
int fs_mult = fs_hz_ / 8000;
// Pre-calculate common multiplications with fs_mult.
int fs_mult_4 = fs_mult * 4;
int fs_mult_20 = fs_mult * 20;
int fs_mult_120 = fs_mult * 120;
int fs_mult_dist_len = fs_mult * kDistortionLength;
int fs_mult_lpc_analysis_len = fs_mult * kLpcAnalysisLength;
const size_t signal_length = 256 * fs_mult;
const int16_t* audio_history =
&(*sync_buffer_)[0][sync_buffer_->Size() - signal_length];
// Initialize.
InitializeForAnExpandPeriod();
// Calculate correlation in downsampled domain (4 kHz sample rate).
int16_t correlation_scale;
int correlation_length = 51; // TODO(hlundin): Legacy bit-exactness.
// If it is decided to break bit-exactness |correlation_length| should be
// initialized to the return value of Correlation().
Correlation(audio_history, signal_length, correlation_vector,
&correlation_scale);
// Find peaks in correlation vector.
DspHelper::PeakDetection(correlation_vector, correlation_length,
kNumCorrelationCandidates, fs_mult,
best_correlation_index, best_correlation);
// Adjust peak locations; cross-correlation lags start at 2.5 ms
// (20 * fs_mult samples).
best_correlation_index[0] += fs_mult_20;
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 (int i = 0; i < kNumCorrelationCandidates; i++) {
int16_t min_index = std::max(fs_mult_20,
best_correlation_index[i] - fs_mult_4);
int16_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();
int best_index = -1;
for (int i = 0; i < kNumCorrelationCandidates; ++i) {
int32_t ratio;
if (best_distortion[i] > 0) {
ratio = (best_correlation[i] << 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;
}
}
int distortion_lag = best_distortion_index[best_index];
int 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 = distortion_lag + 10;
correlation_length = std::min(correlation_length, fs_mult_120);
correlation_length = std::max(correlation_length, 60 * fs_mult);
int start_index = std::min(distortion_lag, correlation_lag);
int correlation_lags = WEBRTC_SPL_ABS_W16((distortion_lag-correlation_lag))
+ 1;
assert(correlation_lags <= 99 * fs_mult + 1); // Cannot be larger.
for (size_t channel_ix = 0; channel_ix < num_channels_; ++channel_ix) {
ChannelParameters& parameters = channel_parameters_[channel_ix];
// 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);
correlation_scale = ((31 - WebRtcSpl_NormW32(signal_max * signal_max))
+ (31 - WebRtcSpl_NormW32(correlation_length))) - 31;
correlation_scale = std::max(static_cast<int16_t>(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.
int16_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;
}
int16_t scaled_energy1 = energy1 >> energy1_scale;
int16_t scaled_energy2 = energy2 >> energy2_scale;
int16_t sqrt_energy_product = 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);
corr_coefficient = std::min(static_cast<int16_t>(16384),
corr_coefficient); // Cap at 1.0 in Q14.
} else {
corr_coefficient = 0;
}
// Extract the two vectors expand_vector0 and expand_vector1 from
// |audio_history|.
int16_t expansion_length = static_cast<int16_t>(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 / energy1 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.
int16_t scaled_energy2 = std::max(16 - WebRtcSpl_NormW32(energy2), 0);
int16_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),
WEBRTC_SPL_RSHIFT_W32(energy2, scaled_energy2));
// Calculate sqrt ratio in Q13 (sqrt of en1/en2 in Q26).
amplitude_ratio = 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() <
static_cast<size_t>(expansion_length)) {
parameters.expand_vector1.Extend(
expansion_length - parameters.expand_vector1.Size());
}
WebRtcSpl_AffineTransformVector(&parameters.expand_vector1[0],
const_cast<int16_t*>(vector2),
amplitude_ratio,
4096,
13,
expansion_length);
} 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.CopyFrom(&parameters.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.
int lag_difference = distortion_lag - correlation_lag;
if (lag_difference == 0) {
// |distortion_lag| and |correlation_lag| are equal.
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 (lag_difference > 0) {
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 scale value needed for auto-correlation.
correlation_scale = WebRtcSpl_MaxAbsValueW16(
&(audio_history[signal_length - fs_mult_lpc_analysis_len]),
fs_mult_lpc_analysis_len);
correlation_scale = std::min(16 - WebRtcSpl_NormW32(correlation_scale), 0);
correlation_scale = std::max(correlation_scale * 2 + 7, 0);
// 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);
WebRtcSpl_CrossCorrelation(auto_correlation,
&temp_signal[kUnvoicedLpcOrder],
&temp_signal[kUnvoicedLpcOrder],
fs_mult_lpc_analysis_len, kUnvoicedLpcOrder + 1,
correlation_scale, -1);
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.
int16_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(
const_cast<int16_t*>(&audio_history[signal_length - 128]),
unvoiced_vector, parameters.ar_filter, kUnvoicedLpcOrder + 1, 128);
int16_t unvoiced_prescale;
if (WebRtcSpl_MaxAbsValueW16(unvoiced_vector, 128) > 4000) {
unvoiced_prescale = 4;
} else {
unvoiced_prescale = 0;
}
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);
int32_t unvoiced_gain = 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;
x1 = corr_coefficient; // |corr_coefficient| is in Q14.
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] << 14;
temp_sum += kCoefficients[1] * x1;
temp_sum += kCoefficients[2] * x2;
temp_sum += kCoefficients[3] * x3;
parameters.voice_mix_factor = temp_sum / 4096;
parameters.voice_mix_factor = std::min(parameters.voice_mix_factor,
static_cast<int16_t>(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 temp_ratio = WebRtcSpl_DivW32W16((slope - 8192) << 12,
(distortion_lag * slope) >> 8);
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) << 7,
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(static_cast<int16_t>(5243 / fs_mult),
parameters.mute_slope);
} else if (slope > 8028) {
parameters.mute_slope = 0;
}
parameters.onset = false;
}
}
}
int16_t Expand::Correlation(const int16_t* input, size_t input_length,
int16_t* output, int16_t* output_scale) const {
// Set parameters depending on sample rate.
const int16_t* filter_coefficients;
int16_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 int kCorrelationStartLag = 10;
static const int kNumCorrelationLags = 54;
static const int kCorrelationLength = 60;
// Downsample to 4 kHz sample rate.
static const int kDownsampledLength = kCorrelationStartLag
+ kNumCorrelationLags + kCorrelationLength;
int16_t downsampled_input[kDownsampledLength];
static const int kFilterDelay = 0;
WebRtcSpl_DownsampleFast(
input + input_length - kDownsampledLength * downsampling_factor,
kDownsampledLength * downsampling_factor, downsampled_input,
kDownsampledLength, filter_coefficients, num_coefficients,
downsampling_factor, kFilterDelay);
// Normalize |downsampled_input| to using all 16 bits.
int16_t max_value = WebRtcSpl_MaxAbsValueW16(downsampled_input,
kDownsampledLength);
int16_t norm_shift = 16 - WebRtcSpl_NormW32(max_value);
WebRtcSpl_VectorBitShiftW16(downsampled_input, kDownsampledLength,
downsampled_input, norm_shift);
int32_t correlation[kNumCorrelationLags];
static const int kCorrelationShift = 6;
WebRtcSpl_CrossCorrelation(
correlation,
&downsampled_input[kDownsampledLength - kCorrelationLength],
&downsampled_input[kDownsampledLength - kCorrelationLength
- kCorrelationStartLag],
kCorrelationLength, kNumCorrelationLags, kCorrelationShift, -1);
// Normalize and move data from 32-bit to 16-bit vector.
int32_t max_correlation = WebRtcSpl_MaxAbsValueW32(correlation,
kNumCorrelationLags);
int16_t norm_shift2 = std::max(18 - WebRtcSpl_NormW32(max_correlation), 0);
WebRtcSpl_VectorBitShiftW32ToW16(output, kNumCorrelationLags, correlation,
norm_shift2);
// Total scale factor (right shifts) of correlation value.
*output_scale = 2 * norm_shift + kCorrelationShift + norm_shift2;
return kNumCorrelationLags;
}
void Expand::UpdateLagIndex() {
current_lag_index_ = current_lag_index_ + lag_index_direction_;
// Change direction if needed.
if (current_lag_index_ <= 0) {
lag_index_direction_ = 1;
}
if (current_lag_index_ >= kNumLags - 1) {
lag_index_direction_ = -1;
}
}
Expand* ExpandFactory::Create(BackgroundNoise* background_noise,
SyncBuffer* sync_buffer,
RandomVector* random_vector,
int fs,
size_t num_channels) const {
return new Expand(background_noise, sync_buffer, random_vector, fs,
num_channels);
}
// TODO(turajs): This can be moved to BackgroundNoise class.
void Expand::GenerateBackgroundNoise(int16_t* random_vector,
size_t channel,
int16_t mute_slope,
bool too_many_expands,
size_t num_noise_samples,
int16_t* buffer) {
static const int kNoiseLpcOrder = BackgroundNoise::kMaxLpcOrder;
int16_t scaled_random_vector[kMaxSampleRate / 8000 * 125];
assert(static_cast<size_t>(kMaxSampleRate / 8000 * 125) >= num_noise_samples);
int16_t* noise_samples = &buffer[kNoiseLpcOrder];
if (background_noise_->initialized()) {
// Use background noise parameters.
memcpy(noise_samples - kNoiseLpcOrder,
background_noise_->FilterState(channel),
sizeof(int16_t) * kNoiseLpcOrder);
int dc_offset = 0;
if (background_noise_->ScaleShift(channel) > 1) {
dc_offset = 1 << (background_noise_->ScaleShift(channel) - 1);
}
// Scale random vector to correct energy level.
WebRtcSpl_AffineTransformVector(
scaled_random_vector, random_vector,
background_noise_->Scale(channel), dc_offset,
background_noise_->ScaleShift(channel),
static_cast<int>(num_noise_samples));
WebRtcSpl_FilterARFastQ12(scaled_random_vector, noise_samples,
background_noise_->Filter(channel),
kNoiseLpcOrder + 1,
static_cast<int>(num_noise_samples));
background_noise_->SetFilterState(
channel,
&(noise_samples[num_noise_samples - kNoiseLpcOrder]),
kNoiseLpcOrder);
// Unmute the background noise.
int16_t bgn_mute_factor = background_noise_->MuteFactor(channel);
NetEq::BackgroundNoiseMode bgn_mode = background_noise_->mode();
if (bgn_mode == NetEq::kBgnFade && too_many_expands &&
bgn_mute_factor > 0) {
// Fade BGN to zero.
// Calculate muting slope, approximately -2^18 / fs_hz.
int16_t mute_slope;
if (fs_hz_ == 8000) {
mute_slope = -32;
} else if (fs_hz_ == 16000) {
mute_slope = -16;
} else if (fs_hz_ == 32000) {
mute_slope = -8;
} else {
mute_slope = -5;
}
// Use UnmuteSignal function with negative slope.
// |bgn_mute_factor| is in Q14. |mute_slope| is in Q20.
DspHelper::UnmuteSignal(noise_samples,
num_noise_samples,
&bgn_mute_factor,
mute_slope,
noise_samples);
} else if (bgn_mute_factor < 16384) {
// If mode is kBgnOn, or if kBgnFade has started fading,
// use regular |mute_slope|.
if (!stop_muting_ && bgn_mode != NetEq::kBgnOff &&
!(bgn_mode == NetEq::kBgnFade && too_many_expands)) {
DspHelper::UnmuteSignal(noise_samples,
static_cast<int>(num_noise_samples),
&bgn_mute_factor,
mute_slope,
noise_samples);
} else {
// kBgnOn and stop muting, or
// kBgnOff (mute factor is always 0), or
// kBgnFade has reached 0.
WebRtcSpl_AffineTransformVector(noise_samples, noise_samples,
bgn_mute_factor, 8192, 14,
static_cast<int>(num_noise_samples));
}
}
// Update mute_factor in BackgroundNoise class.
background_noise_->SetMuteFactor(channel, bgn_mute_factor);
} else {
// BGN parameters have not been initialized; use zero noise.
memset(noise_samples, 0, sizeof(int16_t) * num_noise_samples);
}
}
void Expand::GenerateRandomVector(int 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);
random_vector_->Generate(rand_length, &random_vector[samples_generated]);
samples_generated += rand_length;
}
}
} // namespace webrtc
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