1 files changed, 381 insertions, 0 deletions
diff --git a/webrtc/modules/audio_processing/intelligibility/intelligibility_enhancer.cc b/webrtc/modules/audio_processing/intelligibility/intelligibility_enhancer.cc
new file mode 100644
index 0000000000..d014ce060c
--- /dev/null
+++ b/webrtc/modules/audio_processing/intelligibility/intelligibility_enhancer.cc
@@ -0,0 +1,381 @@
+/*
+ *  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.
+ */
+
+//
+//  Implements core class for intelligibility enhancer.
+//
+//  Details of the model and algorithm can be found in the original paper:
+//  http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=6882788
+//
+
+#include "webrtc/modules/audio_processing/intelligibility/intelligibility_enhancer.h"
+
+#include <math.h>
+#include <stdlib.h>
+#include <algorithm>
+#include <numeric>
+
+#include "webrtc/base/checks.h"
+#include "webrtc/common_audio/include/audio_util.h"
+#include "webrtc/common_audio/window_generator.h"
+
+namespace webrtc {
+
+namespace {
+
+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.
+
+}  // 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) {
+}
+
+void IntelligibilityEnhancer::TransformCallback::ProcessAudioBlock(
+    const complex<float>* const* in_block,
+    int in_channels,
+    size_t frames,
+    int /* out_channels */,
+    complex<float>* const* out_block) {
+  RTC_DCHECK_EQ(parent_->freqs_, frames);
+  for (int i = 0; i < in_channels; ++i) {
+    parent_->DispatchAudio(source_, 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_]),
+      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),
+      block_count_(0),
+      analysis_step_(0) {
+  RTC_DCHECK_LE(config.rho, 1.0f);
+
+  CreateErbBank();
+
+  // 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::ProcessRenderAudio(float* const* audio,
+                                                 int sample_rate_hz,
+                                                 int 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 (int 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,
+                                                  int 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());
+
+  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.
+}
+
+void IntelligibilityEnhancer::SolveForLambda(float power_target,
+                                             float power_bot,
+                                             float power_top) {
+  const float kConvergeThresh = 0.001f;  // TODO(ekmeyerson): Find best values
+  const int kMaxIters = 100;             // for these, based on experiments.
+
+  const float reciprocal_power_target = 1.f / power_target;
+  float lambda_bot = kLambdaBot;
+  float lambda_top = kLambdaTop;
+  float power_ratio = 2.0f;  // Ratio of achieved power to target power.
+  int iters = 0;
+  while (std::fabs(power_ratio - 1.0f) > kConvergeThresh &&
+         iters <= kMaxIters) {
+    const float lambda = lambda_bot + (lambda_top - lambda_bot) / 2.0f;
+    SolveForGainsGivenLambda(lambda, start_freq_, gains_eq_.get());
+    const float power =
+        DotProduct(gains_eq_.get(), filtered_clear_var_.get(), bank_size_);
+    if (power < power_target) {
+      lambda_bot = lambda;
+    } else {
+      lambda_top = lambda;
+    }
+    power_ratio = std::fabs(power * reciprocal_power_target);
+    ++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]);
+    }
+  }
+}
+
+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() {
+  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_);
+  }
+
+  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_ /
+            (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;
+
+    rrr = static_cast<size_t>(round(
+        center_freqs_[min(bank_size_, i + rf) - 1] * freqs_ /
+            (0.5f * sample_rate_hz_)));
+    rr = static_cast<size_t>(round(
+        center_freqs_[min(bank_size_, i + 1) - 1] * freqs_ /
+            (0.5f * sample_rate_hz_)));
+    rrr = min(freqs_, max(rrr, kOne)) - 1;
+    rr = min(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;
+      element += step;
+    }
+    step = 1.0f / (rrr - rr);
+    element = 1.0f;
+    for (size_t j = rr; j <= rrr; ++j) {
+      filter_bank_[i - 1][j] = element;
+      element -= step;
+    }
+    for (size_t j = ll; j <= rr; ++j) {
+      filter_bank_[i - 1][j] = 1.0f;
+    }
+  }
+
+  float sum;
+  for (size_t i = 0; i < freqs_; ++i) {
+    sum = 0.0f;
+    for (size_t j = 0; j < bank_size_; ++j) {
+      sum += filter_bank_[j][i];
+    }
+    for (size_t j = 0; j < bank_size_; ++j) {
+      filter_bank_[j][i] /= sum;
+    }
+  }
+}
+
+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) {
+    sols[n] = 1.0f;
+  }
+
+  // Analytic solution for optimal gains. See paper for derivation.
+  for (size_t n = start_freq - 1; n < bank_size_; ++n) {
+    float alpha0, beta0, gamma0;
+    gamma0 = 0.5f * rho_[n] * var_x0[n] * var_n0[n] +
+             lambda * var_x0[n] * var_n0[n] * var_n0[n];
+    beta0 = lambda * var_x0[n] * (2 - rho_[n]) * var_x0[n] * var_n0[n];
+    if (quadratic) {
+      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