| /* |
| * 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/cross_correlation.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/statistics_calculator.h" |
| #include "webrtc/modules/audio_coding/neteq/sync_buffer.h" |
| #include "webrtc/rtc_base/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<int>(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<int16_t[]> temp_0(new int16_t[temp_length]); |
| parameters.expand_vector0.CopyTo(temp_length, expansion_vector_position, |
| temp_0.get()); |
| std::unique_ptr<int16_t[]> 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<int16_t[]> temp_0(new int16_t[temp_length]); |
| parameters.expand_vector0.CopyTo(temp_length, expansion_vector_position, |
| temp_0.get()); |
| std::unique_ptr<int16_t[]> 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<int32_t>(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<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); |
| } |
| (*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<size_t>(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( |
| rtc::dchecked_cast<int>(expand_duration_samples_) / (fs_hz_ / 1000)); |
| } |
| |
| 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; |
| } |
| |
| 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<size_t>(fs_mult * 4); |
| size_t fs_mult_20 = static_cast<size_t>(fs_mult * 20); |
| size_t fs_mult_120 = static_cast<size_t>(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<size_t>(256 * fs_mult); |
| |
| const size_t audio_history_position = sync_buffer_->Size() - signal_length; |
| std::unique_ptr<int16_t[]> 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<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]; |
| // 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. |
| int temp_ratio = WebRtcSpl_DivW32W16( |
| (slope - 8192) << 12, |
| static_cast<int16_t>((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) * 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; |
| // 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<int16_t>( |
| 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); |
| } |
| |
| // TODO(turajs): This can be moved to BackgroundNoise class. |
| void Expand::GenerateBackgroundNoise(int16_t* random_vector, |
| size_t channel, |
| int mute_slope, |
| bool too_many_expands, |
| size_t num_noise_samples, |
| int16_t* buffer) { |
| static const size_t kNoiseLpcOrder = BackgroundNoise::kMaxLpcOrder; |
| int16_t scaled_random_vector[kMaxSampleRate / 8000 * 125]; |
| assert(num_noise_samples <= (kMaxSampleRate / 8000 * 125)); |
| 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), |
| num_noise_samples); |
| |
| WebRtcSpl_FilterARFastQ12(scaled_random_vector, noise_samples, |
| background_noise_->Filter(channel), |
| kNoiseLpcOrder + 1, |
| 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. |
| int 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, |
| 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(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 |
