Update a ton of audio code to use size_t more correctly and in general reduce

webrtc/modules/audio_coding/neteq/expand.cc

 /*
  *  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.
  */
 
@@ skipping 29 matching lines @@
       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 <= kMaxSampleRate);  // Should not be possible.
+  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 int kNoiseLpcOrder = BackgroundNoise::kMaxLpcOrder;
+  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.
-    int16_t rand_length = max_lag_;
+    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.
@@ skipping 11 matching lines @@
       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));
+          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());
       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));
+          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;
@@ skipping 46 matching lines @@
     // 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));
+                                    current_lag);
     WebRtcSpl_FilterARFastQ12(scaled_random_vector, unvoiced_vector,
                               parameters.ar_filter, kUnvoicedLpcOrder + 1,
-                              static_cast<int>(current_lag));
+                              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;
+    int temp_shift =
+        (31 - WebRtcSpl_NormW32(rtc::checked_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,
                          &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_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, static_cast<int>(current_lag - temp_length));
+          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, static_cast<int>(current_lag));
+                                      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;
@@ skipping 72 matching lines @@
 }
 
 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];
+  size_t best_correlation_index[kNumCorrelationCandidates];
   int16_t best_correlation[kNumCorrelationCandidates];
-  int16_t best_distortion_index[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 int kNoiseLpcOrder = BackgroundNoise::kMaxLpcOrder;
+  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.
-  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;
+  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 = 256 * fs_mult;
+  const size_t signal_length = static_cast<size_t>(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).
   int correlation_scale;
-  int correlation_length = 51;  // TODO(hlundin): Legacy bit-exactness.
+  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, 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);
+  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();
-  int best_index = std::numeric_limits<int>::max();
-  for (int i = 0; i < kNumCorrelationCandidates; ++i) {
+  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] << 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];
+  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), 60 * fs_mult);
+      std::max(std::min(distortion_lag + 10, fs_mult_120),
+               static_cast<size_t>(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.
+  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);
     correlation_scale = (31 - WebRtcSpl_NormW32(signal_max * signal_max)) +
-        (31 - WebRtcSpl_NormW32(correlation_length)) - 31;
+        (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);
+    best_index = static_cast<size_t>(
+        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(
@@ skipping 22 matching lines @@
       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|.
-    int16_t expansion_length = static_cast<int16_t>(max_lag_ + overlap_length_);
+    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 / 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.
       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),
-          energy2 >> scaled_energy2);
+          static_cast<int16_t>(energy2 >> scaled_energy2));
       // Calculate sqrt ratio in Q13 (sqrt of en1/en2 in Q26).
-      amplitude_ratio = WebRtcSpl_SqrtFloor(energy_ratio << 13);
+      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() <
-          static_cast<size_t>(expansion_length)) {
+      if (parameters.expand_vector1.Size() < 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 {
@@ skipping 70 matching lines @@
       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;
+      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
@@ skipping 121 matching lines @@
   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,
                          int* output_scale) const {
   // Set parameters depending on sample rate.
   const int16_t* filter_coefficients;
-  int16_t num_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 int kCorrelationStartLag = 10;
-  static const int kNumCorrelationLags = 54;
-  static const int kCorrelationLength = 60;
+  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 int kDownsampledLength = kCorrelationStartLag
+  static const size_t kDownsampledLength = kCorrelationStartLag
       + kNumCorrelationLags + kCorrelationLength;
   int16_t downsampled_input[kDownsampledLength];
-  static const int kFilterDelay = 0;
+  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);
@@ skipping 41 matching lines @@
                     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 int kNoiseLpcOrder = BackgroundNoise::kMaxLpcOrder;
+  static const size_t kNoiseLpcOrder = BackgroundNoise::kMaxLpcOrder;
   int16_t scaled_random_vector[kMaxSampleRate / 8000 * 125];
-  assert(num_noise_samples <= static_cast<size_t>(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),
-        static_cast<int>(num_noise_samples));
+        num_noise_samples);
 
     WebRtcSpl_FilterARFastQ12(scaled_random_vector, noise_samples,
                               background_noise_->Filter(channel),
                               kNoiseLpcOrder + 1,
-                              static_cast<int>(num_noise_samples));
+                              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 &&
@@ skipping 26 matching lines @@
                                 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));
+                                        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