Using the NS noise estimate for the IE

webrtc/modules/audio_processing/intelligibility/intelligibility_enhancer.cc

 /*
  *  Copyright (c) 2014 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 21 matching lines @@
 
 const size_t kErbResolution = 2;
 const int kWindowSizeMs = 2;
 const int kChunkSizeMs = 10;  // Size provided by APM.
 const float kClipFreq = 200.0f;
 const float kConfigRho = 0.02f;  // Default production and interpretation SNR.
 const float kKbdAlpha = 1.5f;
 const float kLambdaBot = -1.0f;      // Extreme values in bisection
 const float kLambdaTop = -10e-18f;  // search for lamda.
 
+// Returns dot product of vectors |a| and |b| with size |length|.
+float DotProduct(const float* a, const float* b, size_t length) {
+  float ret = 0.f;
+  for (size_t i = 0; i < length; ++i) {
+    ret = fmaf(a[i], b[i], ret);
+  }
+  return ret;
+}
+
+// Computes the power across ERB filters from the power spectral density |var|.
+// Stores it in |result|.
+void FilterVariance(const float* var,

[turaj, 2016/02/10 15:30:40]

I wish this was called something else (I know you just copied it here). This, in
fact, is a mapping rather than a filter, or maybe I'm missing something.
Especially that we also have filtering of the norm of DFT coeffs over time
(frames) to compute average power.  

[aluebs-webrtc, 2016/02/10 18:43:29]

This method is going to be renamed in my next CL anyways, so I will do that
there, if you agree.

+                    const std::vector<std::vector<float>>& filter_bank,
+                    float* result) {
+  for (size_t i = 0; i < filter_bank.size(); ++i) {
+    RTC_DCHECK_GT(filter_bank[i].size(), 0u);
+    result[i] = DotProduct(&filter_bank[i][0], var, filter_bank[i].size());
+  }
+}
+
 }  // namespace
 
 using std::complex;
 using std::max;
 using std::min;
 using VarianceType = intelligibility::VarianceArray::StepType;
 
 IntelligibilityEnhancer::TransformCallback::TransformCallback(
-    IntelligibilityEnhancer* parent,
-    IntelligibilityEnhancer::AudioSource source)
-    : parent_(parent), source_(source) {
+    IntelligibilityEnhancer* parent)
+    : parent_(parent) {
 }
 
 void IntelligibilityEnhancer::TransformCallback::ProcessAudioBlock(
     const complex<float>* const* in_block,
     size_t in_channels,
     size_t frames,
     size_t /* out_channels */,
     complex<float>* const* out_block) {
   RTC_DCHECK_EQ(parent_->freqs_, frames);
   for (size_t i = 0; i < in_channels; ++i) {
-    parent_->DispatchAudio(source_, in_block[i], out_block[i]);
+    parent_->ProcessClearBlock(in_block[i], out_block[i]);
   }
 }
 
 IntelligibilityEnhancer::IntelligibilityEnhancer()
     : IntelligibilityEnhancer(IntelligibilityEnhancer::Config()) {
 }
 
 IntelligibilityEnhancer::IntelligibilityEnhancer(const Config& config)
     : freqs_(RealFourier::ComplexLength(
           RealFourier::FftOrder(config.sample_rate_hz * kWindowSizeMs / 1000))),
       window_size_(static_cast<size_t>(1 << RealFourier::FftOrder(freqs_))),
       chunk_length_(
           static_cast<size_t>(config.sample_rate_hz * kChunkSizeMs / 1000)),
       bank_size_(GetBankSize(config.sample_rate_hz, kErbResolution)),
       sample_rate_hz_(config.sample_rate_hz),
       erb_resolution_(kErbResolution),
       num_capture_channels_(config.num_capture_channels),
       num_render_channels_(config.num_render_channels),
       analysis_rate_(config.analysis_rate),
       active_(true),
       clear_variance_(freqs_,
                       config.var_type,
                       config.var_window_size,
                       config.var_decay_rate),
-      noise_variance_(freqs_,
-                      config.var_type,
-                      config.var_window_size,
-                      config.var_decay_rate),
       filtered_clear_var_(new float[bank_size_]),
       filtered_noise_var_(new float[bank_size_]),
-      filter_bank_(bank_size_),
       center_freqs_(new float[bank_size_]),
+      render_filter_bank_(CreateErbBank(freqs_)),
       rho_(new float[bank_size_]),
       gains_eq_(new float[bank_size_]),
       gain_applier_(freqs_, config.gain_change_limit),
       temp_render_out_buffer_(chunk_length_, num_render_channels_),
-      temp_capture_out_buffer_(chunk_length_, num_capture_channels_),
       kbd_window_(new float[window_size_]),
-      render_callback_(this, AudioSource::kRenderStream),
-      capture_callback_(this, AudioSource::kCaptureStream),
+      render_callback_(this),
       block_count_(0),
       analysis_step_(0) {
   RTC_DCHECK_LE(config.rho, 1.0f);
 
-  CreateErbBank();
+  memset(filtered_clear_var_.get(),
+         0,
+         bank_size_ * sizeof(filtered_clear_var_[0]));
+  memset(filtered_noise_var_.get(),
+         0,
+         bank_size_ * sizeof(filtered_noise_var_[0]));
 
   // Assumes all rho equal.
   for (size_t i = 0; i < bank_size_; ++i) {
     rho_[i] = config.rho * config.rho;
   }
 
   float freqs_khz = kClipFreq / 1000.0f;
   size_t erb_index = static_cast<size_t>(ceilf(
       11.17f * logf((freqs_khz + 0.312f) / (freqs_khz + 14.6575f)) + 43.0f));
   start_freq_ = std::max(static_cast<size_t>(1), erb_index * erb_resolution_);
 
   WindowGenerator::KaiserBesselDerived(kKbdAlpha, window_size_,
                                        kbd_window_.get());
   render_mangler_.reset(new LappedTransform(
       num_render_channels_, num_render_channels_, chunk_length_,
       kbd_window_.get(), window_size_, window_size_ / 2, &render_callback_));
-  capture_mangler_.reset(new LappedTransform(
-      num_capture_channels_, num_capture_channels_, chunk_length_,
-      kbd_window_.get(), window_size_, window_size_ / 2, &capture_callback_));
+}
+
+void IntelligibilityEnhancer::SetCaptureNoiseEstimate(
+    std::vector<float> noise) {
+  if (capture_filter_bank_.size() != bank_size_ ||
+      capture_filter_bank_[0].size() != noise.size()) {
+    capture_filter_bank_ = CreateErbBank(noise.size());
+  }
+  if (noise.size() != noise_power_.size()) {
+    noise_power_.resize(noise.size());
+  }
+  for (size_t i = 0; i < noise.size(); ++i) {
+    noise_power_[i] = noise[i] * noise[i];
+  }
 }
 
 void IntelligibilityEnhancer::ProcessRenderAudio(float* const* audio,
                                                  int sample_rate_hz,
                                                  size_t num_channels) {
   RTC_CHECK_EQ(sample_rate_hz_, sample_rate_hz);
   RTC_CHECK_EQ(num_render_channels_, num_channels);
 
   if (active_) {
     render_mangler_->ProcessChunk(audio, temp_render_out_buffer_.channels());
   }
 
   if (active_) {
     for (size_t i = 0; i < num_render_channels_; ++i) {
       memcpy(audio[i], temp_render_out_buffer_.channels()[i],
              chunk_length_ * sizeof(**audio));
     }
   }
 }
 
-void IntelligibilityEnhancer::AnalyzeCaptureAudio(float* const* audio,
-                                                  int sample_rate_hz,
-                                                  size_t num_channels) {
-  RTC_CHECK_EQ(sample_rate_hz_, sample_rate_hz);
-  RTC_CHECK_EQ(num_capture_channels_, num_channels);
-
-  capture_mangler_->ProcessChunk(audio, temp_capture_out_buffer_.channels());
-}
-
-void IntelligibilityEnhancer::DispatchAudio(
-    IntelligibilityEnhancer::AudioSource source,
-    const complex<float>* in_block,
-    complex<float>* out_block) {
-  switch (source) {
-    case kRenderStream:
-      ProcessClearBlock(in_block, out_block);
-      break;
-    case kCaptureStream:
-      ProcessNoiseBlock(in_block, out_block);
-      break;
-  }
-}
-
 void IntelligibilityEnhancer::ProcessClearBlock(const complex<float>* in_block,
                                                 complex<float>* out_block) {
   if (block_count_ < 2) {
     memset(out_block, 0, freqs_ * sizeof(*out_block));
     ++block_count_;
     return;
   }
 
   // TODO(ekm): Use VAD to |Step| and |AnalyzeClearBlock| only if necessary.
   if (true) {
     clear_variance_.Step(in_block, false);
     if (block_count_ % analysis_rate_ == analysis_rate_ - 1) {
       const float power_target = std::accumulate(
           clear_variance_.variance(), clear_variance_.variance() + freqs_, 0.f);
       AnalyzeClearBlock(power_target);
       ++analysis_step_;
     }
     ++block_count_;
   }
 
   if (active_) {
     gain_applier_.Apply(in_block, out_block);
   }
 }
 
 void IntelligibilityEnhancer::AnalyzeClearBlock(float power_target) {
-  FilterVariance(clear_variance_.variance(), filtered_clear_var_.get());
-  FilterVariance(noise_variance_.variance(), filtered_noise_var_.get());
-
+  FilterVariance(clear_variance_.variance(),
+                 render_filter_bank_,
+                 filtered_clear_var_.get());
+  FilterVariance(&noise_power_[0],
+                 capture_filter_bank_,
+                 filtered_noise_var_.get());
   SolveForGainsGivenLambda(kLambdaTop, start_freq_, gains_eq_.get());
   const float power_top =
       DotProduct(gains_eq_.get(), filtered_clear_var_.get(), bank_size_);
   SolveForGainsGivenLambda(kLambdaBot, start_freq_, gains_eq_.get());
   const float power_bot =
       DotProduct(gains_eq_.get(), filtered_clear_var_.get(), bank_size_);
   if (power_target >= power_bot && power_target <= power_top) {
     SolveForLambda(power_target, power_bot, power_top);
     UpdateErbGains();
   }  // Else experiencing variance underflow, so do nothing.
@@ skipping 25 matching lines @@
     ++iters;
   }
 }
 
 void IntelligibilityEnhancer::UpdateErbGains() {
   // (ERB gain) = filterbank' * (freq gain)
   float* gains = gain_applier_.target();
   for (size_t i = 0; i < freqs_; ++i) {
     gains[i] = 0.0f;
     for (size_t j = 0; j < bank_size_; ++j) {
-      gains[i] = fmaf(filter_bank_[j][i], gains_eq_[j], gains[i]);
+      gains[i] = fmaf(render_filter_bank_[j][i], gains_eq_[j], gains[i]);
     }
   }
 }
 
-void IntelligibilityEnhancer::ProcessNoiseBlock(const complex<float>* in_block,
-                                                complex<float>* /*out_block*/) {
-  noise_variance_.Step(in_block);
-}
-
 size_t IntelligibilityEnhancer::GetBankSize(int sample_rate,
                                             size_t erb_resolution) {
   float freq_limit = sample_rate / 2000.0f;
   size_t erb_scale = static_cast<size_t>(ceilf(
       11.17f * logf((freq_limit + 0.312f) / (freq_limit + 14.6575f)) + 43.0f));
   return erb_scale * erb_resolution;
 }
 
-void IntelligibilityEnhancer::CreateErbBank() {
+std::vector<std::vector<float>> IntelligibilityEnhancer::CreateErbBank(
+    size_t num_freqs) {
+  std::vector<std::vector<float>> filter_bank(bank_size_);
   size_t lf = 1, rf = 4;
 
   for (size_t i = 0; i < bank_size_; ++i) {
     float abs_temp = fabsf((i + 1.0f) / static_cast<float>(erb_resolution_));
     center_freqs_[i] = 676170.4f / (47.06538f - expf(0.08950404f * abs_temp));
     center_freqs_[i] -= 14678.49f;
   }
   float last_center_freq = center_freqs_[bank_size_ - 1];
   for (size_t i = 0; i < bank_size_; ++i) {
     center_freqs_[i] *= 0.5f * sample_rate_hz_ / last_center_freq;
   }
 
   for (size_t i = 0; i < bank_size_; ++i) {
-    filter_bank_[i].resize(freqs_);
+    filter_bank[i].resize(num_freqs);
   }
 
   for (size_t i = 1; i <= bank_size_; ++i) {
     size_t lll, ll, rr, rrr;
     static const size_t kOne = 1;  // Avoids repeated static_cast<>s below.
     lll = static_cast<size_t>(round(
-        center_freqs_[max(kOne, i - lf) - 1] * freqs_ /
+        center_freqs_[max(kOne, i - lf) - 1] * num_freqs /
             (0.5f * sample_rate_hz_)));
     ll = static_cast<size_t>(round(
-        center_freqs_[max(kOne, i) - 1] * freqs_ / (0.5f * sample_rate_hz_)));
-    lll = min(freqs_, max(lll, kOne)) - 1;
-    ll = min(freqs_, max(ll, kOne)) - 1;
+        center_freqs_[max(kOne, i) - 1] * num_freqs /
+            (0.5f * sample_rate_hz_)));
+    lll = min(num_freqs, max(lll, kOne)) - 1;
+    ll = min(num_freqs, max(ll, kOne)) - 1;
 
     rrr = static_cast<size_t>(round(
-        center_freqs_[min(bank_size_, i + rf) - 1] * freqs_ /
+        center_freqs_[min(bank_size_, i + rf) - 1] * num_freqs /
             (0.5f * sample_rate_hz_)));
     rr = static_cast<size_t>(round(
-        center_freqs_[min(bank_size_, i + 1) - 1] * freqs_ /
+        center_freqs_[min(bank_size_, i + 1) - 1] * num_freqs /
             (0.5f * sample_rate_hz_)));
-    rrr = min(freqs_, max(rrr, kOne)) - 1;
-    rr = min(freqs_, max(rr, kOne)) - 1;
+    rrr = min(num_freqs, max(rrr, kOne)) - 1;
+    rr = min(num_freqs, max(rr, kOne)) - 1;
 
     float step, element;
 
     step = 1.0f / (ll - lll);
     element = 0.0f;
     for (size_t j = lll; j <= ll; ++j) {
-      filter_bank_[i - 1][j] = element;
+      filter_bank[i - 1][j] = element;
       element += step;
     }
     step = 1.0f / (rrr - rr);
     element = 1.0f;
     for (size_t j = rr; j <= rrr; ++j) {
-      filter_bank_[i - 1][j] = element;
+      filter_bank[i - 1][j] = element;
       element -= step;
     }
     for (size_t j = ll; j <= rr; ++j) {
-      filter_bank_[i - 1][j] = 1.0f;
+      filter_bank[i - 1][j] = 1.0f;
     }
   }
 
   float sum;
-  for (size_t i = 0; i < freqs_; ++i) {
+  for (size_t i = 0; i < num_freqs; ++i) {
     sum = 0.0f;
     for (size_t j = 0; j < bank_size_; ++j) {
-      sum += filter_bank_[j][i];
+      sum += filter_bank[j][i];
     }
     for (size_t j = 0; j < bank_size_; ++j) {
-      filter_bank_[j][i] /= sum;
+      filter_bank[j][i] /= sum;
     }
   }
+  return filter_bank;
 }
 
 void IntelligibilityEnhancer::SolveForGainsGivenLambda(float lambda,
                                                        size_t start_freq,
                                                        float* sols) {
   bool quadratic = (kConfigRho < 1.0f);
   const float* var_x0 = filtered_clear_var_.get();
   const float* var_n0 = filtered_noise_var_.get();
 
   for (size_t n = 0; n < start_freq; ++n) {
@@ skipping 10 matching lines @@
       alpha0 = lambda * var_x0[n] * (1 - rho_[n]) * var_x0[n] * var_x0[n];
       sols[n] =
           (-beta0 - sqrtf(beta0 * beta0 - 4 * alpha0 * gamma0)) / (2 * alpha0);
     } else {
       sols[n] = -gamma0 / beta0;
     }
     sols[n] = fmax(0, sols[n]);
   }
 }
 
-void IntelligibilityEnhancer::FilterVariance(const float* var, float* result) {
-  RTC_DCHECK_GT(freqs_, 0u);
-  for (size_t i = 0; i < bank_size_; ++i) {
-    result[i] = DotProduct(&filter_bank_[i][0], var, freqs_);
-  }
-}
-
-float IntelligibilityEnhancer::DotProduct(const float* a,
-                                          const float* b,
-                                          size_t length) {
-  float ret = 0.0f;
-
-  for (size_t i = 0; i < length; ++i) {
-    ret = fmaf(a[i], b[i], ret);
-  }
-  return ret;
-}
-
 bool IntelligibilityEnhancer::active() const {
   return active_;
 }
 
 }  // namespace webrtc