/* * Copyright (c) 2012 The WebRTC project authors. All Rights Reserved. * * Use of this source code is governed by a BSD-style license * that can be found in the LICENSE file in the root of the source * tree. An additional intellectual property rights grant can be found * in the file PATENTS. All contributing project authors may * be found in the AUTHORS file in the root of the source tree. */ #include "modules/audio_coding/neteq/expand.h" #include #include // memset #include // min, max #include // numeric_limits #include "common_audio/signal_processing/include/signal_processing_library.h" #include "modules/audio_coding/neteq/audio_multi_vector.h" #include "modules/audio_coding/neteq/background_noise.h" #include "modules/audio_coding/neteq/cross_correlation.h" #include "modules/audio_coding/neteq/dsp_helper.h" #include "modules/audio_coding/neteq/random_vector.h" #include "modules/audio_coding/neteq/statistics_calculator.h" #include "modules/audio_coding/neteq/sync_buffer.h" #include "rtc_base/numerics/safe_conversions.h" namespace webrtc { Expand::Expand(BackgroundNoise* background_noise, SyncBuffer* sync_buffer, RandomVector* random_vector, StatisticsCalculator* statistics, int fs, size_t num_channels) : random_vector_(random_vector), sync_buffer_(sync_buffer), first_expand_(true), fs_hz_(fs), num_channels_(num_channels), consecutive_expands_(0), background_noise_(background_noise), statistics_(statistics), overlap_length_(5 * fs / 8000), lag_index_direction_(0), current_lag_index_(0), stop_muting_(false), expand_duration_samples_(0), channel_parameters_(new ChannelParameters[num_channels_]) { assert(fs == 8000 || fs == 16000 || fs == 32000 || fs == 48000); assert(fs <= static_cast(kMaxSampleRate)); // Should not be possible. assert(num_channels_ > 0); memset(expand_lags_, 0, sizeof(expand_lags_)); Reset(); } Expand::~Expand() = default; 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 size_t 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; expand_duration_samples_ = 0; } else { // This is not the first expansion, parameters are already estimated. // Extract a noise segment. size_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()); parameters.expand_vector0.CopyTo(temp_length, expansion_vector_position, voiced_vector_storage); } else if (current_lag_index_ == 1) { std::unique_ptr temp_0(new int16_t[temp_length]); parameters.expand_vector0.CopyTo(temp_length, expansion_vector_position, temp_0.get()); std::unique_ptr temp_1(new int16_t[temp_length]); parameters.expand_vector1.CopyTo(temp_length, expansion_vector_position, temp_1.get()); // Mix 3/4 of expand_vector0 with 1/4 of expand_vector1. WebRtcSpl_ScaleAndAddVectorsWithRound(temp_0.get(), 3, temp_1.get(), 1, 2, voiced_vector_storage, 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()); std::unique_ptr temp_0(new int16_t[temp_length]); parameters.expand_vector0.CopyTo(temp_length, expansion_vector_position, temp_0.get()); std::unique_ptr temp_1(new int16_t[temp_length]); parameters.expand_vector1.CopyTo(temp_length, expansion_vector_position, temp_1.get()); WebRtcSpl_ScaleAndAddVectorsWithRound(temp_0.get(), 1, temp_1.get(), 1, 1, voiced_vector_storage, 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, current_lag); WebRtcSpl_FilterARFastQ12(scaled_random_vector, unvoiced_vector, parameters.ar_filter, kUnvoicedLpcOrder + 1, 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(rtc::dchecked_cast(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_length = (parameters.current_voice_mix_factor - parameters.voice_mix_factor) >> temp_shift; temp_length = std::min(temp_length, current_lag); DspHelper::CrossFade(voiced_vector, unvoiced_vector, temp_length, ¶meters.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_length < current_lag) { if (mix_factor_increment != 0) { parameters.current_voice_mix_factor = parameters.voice_mix_factor; } int16_t temp_scale = 16384 - parameters.current_voice_mix_factor; WebRtcSpl_ScaleAndAddVectorsWithRound( voiced_vector + temp_length, parameters.current_voice_mix_factor, unvoiced_vector + temp_length, temp_scale, 14, temp_data + temp_length, current_lag - temp_length); } // 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, 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, 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, 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( 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. background_noise_->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); } (*output)[channel_ix].OverwriteAt(temp_data, current_lag, 0); } // Increase call number and cap it. consecutive_expands_ = consecutive_expands_ >= kMaxConsecutiveExpands ? kMaxConsecutiveExpands : consecutive_expands_ + 1; expand_duration_samples_ += output->Size(); // Clamp the duration counter at 2 seconds. expand_duration_samples_ = std::min(expand_duration_samples_, rtc::dchecked_cast(fs_hz_ * 2)); return 0; } void Expand::SetParametersForNormalAfterExpand() { current_lag_index_ = 0; lag_index_direction_ = 0; stop_muting_ = true; // Do not mute signal any more. statistics_->LogDelayedPacketOutageEvent(expand_duration_samples_, fs_hz_); statistics_->EndExpandEvent(fs_hz_); } 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; statistics_->EndExpandEvent(fs_hz_); } bool Expand::Muted() const { if (first_expand_ || stop_muting_) return false; RTC_DCHECK(channel_parameters_); for (size_t ch = 0; ch < num_channels_; ++ch) { if (channel_parameters_[ch].mute_factor != 0) return false; } return true; } size_t Expand::overlap_length() const { return overlap_length_; } 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]; size_t best_correlation_index[kNumCorrelationCandidates]; int16_t best_correlation[kNumCorrelationCandidates]; size_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 size_t 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. size_t fs_mult_4 = static_cast(fs_mult * 4); size_t fs_mult_20 = static_cast(fs_mult * 20); size_t fs_mult_120 = static_cast(fs_mult * 120); size_t fs_mult_dist_len = fs_mult * kDistortionLength; size_t fs_mult_lpc_analysis_len = fs_mult * kLpcAnalysisLength; const size_t signal_length = static_cast(256 * fs_mult); const size_t audio_history_position = sync_buffer_->Size() - signal_length; std::unique_ptr audio_history(new int16_t[signal_length]); (*sync_buffer_)[0].CopyTo(signal_length, audio_history_position, audio_history.get()); // Initialize. InitializeForAnExpandPeriod(); // Calculate correlation in downsampled domain (4 kHz sample rate). size_t 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.get(), signal_length, correlation_vector); // 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 (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::min(); size_t best_index = std::numeric_limits::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::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(60 * fs_mult)); size_t start_index = std::min(distortion_lag, correlation_lag); size_t correlation_lags = static_cast( WEBRTC_SPL_ABS_W16((distortion_lag - correlation_lag)) + 1); assert(correlation_lags <= static_cast(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(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( 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(energy2 >> scaled_energy2)); // Calculate sqrt ratio in Q13 (sqrt of en1/en2 in Q26). amplitude_ratio = static_cast(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 temp_1(new int16_t[expansion_length]); WebRtcSpl_AffineTransformVector( temp_1.get(), const_cast(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(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(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(std::min(temp_sum / 4096, 16384)); parameters.voice_mix_factor = std::max(parameters.voice_mix_factor, static_cast(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((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(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; // Downsample to 4 kHz sample rate. static const size_t kDownsampledLength = kCorrelationStartLag + kNumCorrelationLags + kCorrelationLength; int16_t downsampled_input[kDownsampledLength]; static const size_t 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]; CrossCorrelationWithAutoShift( &downsampled_input[kDownsampledLength - kCorrelationLength], &downsampled_input[kDownsampledLength - kCorrelationLength - kCorrelationStartLag], kCorrelationLength, kNumCorrelationLags, -1, correlation); // Normalize and move data from 32-bit to 16-bit vector. int32_t max_correlation = WebRtcSpl_MaxAbsValueW32(correlation, kNumCorrelationLags); int16_t norm_shift2 = static_cast( std::max(18 - WebRtcSpl_NormW32(max_correlation), 0)); WebRtcSpl_VectorBitShiftW32ToW16(output, kNumCorrelationLags, correlation, norm_shift2); } 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, StatisticsCalculator* statistics, int fs, size_t num_channels) const { return new Expand(background_noise, sync_buffer, random_vector, statistics, fs, num_channels); } 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); random_vector_->Generate(rand_length, &random_vector[samples_generated]); samples_generated += rand_length; } } } // namespace webrtc