Pull the Voice Activity Detector out from the AGC

webrtc/modules/audio_processing/agc/pitch_based_vad.cc

Index: webrtc/modules/audio_processing/agc/pitch_based_vad.cc
diff --git a/webrtc/modules/audio_processing/agc/pitch_based_vad.cc b/webrtc/modules/audio_processing/agc/pitch_based_vad.cc
deleted file mode 100644
index 0cfa52a0108afb0b255a4c10d519467dda0085c3..0000000000000000000000000000000000000000
--- a/webrtc/modules/audio_processing/agc/pitch_based_vad.cc
+++ /dev/null
@@ -1,122 +0,0 @@
-/*
- *  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_processing/agc/pitch_based_vad.h"
-
-#include <assert.h>
-#include <math.h>
-#include <string.h>
-
-#include "webrtc/modules/audio_processing/agc/circular_buffer.h"
-#include "webrtc/modules/audio_processing/agc/common.h"
-#include "webrtc/modules/audio_processing/agc/noise_gmm_tables.h"
-#include "webrtc/modules/audio_processing/agc/voice_gmm_tables.h"
-#include "webrtc/modules/interface/module_common_types.h"
-
-namespace webrtc {
-
-static_assert(kNoiseGmmDim == kVoiceGmmDim,
-              "noise and voice gmm dimension not equal");
-
-// These values should match MATLAB counterparts for unit-tests to pass.
-static const int kPosteriorHistorySize = 500;  // 5 sec of 10 ms frames.
-static const double kInitialPriorProbability = 0.3;
-static const int kTransientWidthThreshold = 7;
-static const double kLowProbabilityThreshold = 0.2;
-
-static double LimitProbability(double p) {
-  const double kLimHigh = 0.99;
-  const double kLimLow = 0.01;
-
-  if (p > kLimHigh)
-    p = kLimHigh;
-  else if (p < kLimLow)
-    p = kLimLow;
-  return p;
-}
-
-PitchBasedVad::PitchBasedVad()
-    : p_prior_(kInitialPriorProbability),
-      circular_buffer_(AgcCircularBuffer::Create(kPosteriorHistorySize)) {
-  // Setup noise GMM.
-  noise_gmm_.dimension = kNoiseGmmDim;
-  noise_gmm_.num_mixtures = kNoiseGmmNumMixtures;
-  noise_gmm_.weight = kNoiseGmmWeights;
-  noise_gmm_.mean = &kNoiseGmmMean[0][0];
-  noise_gmm_.covar_inverse = &kNoiseGmmCovarInverse[0][0][0];
-
-  // Setup voice GMM.
-  voice_gmm_.dimension = kVoiceGmmDim;
-  voice_gmm_.num_mixtures = kVoiceGmmNumMixtures;
-  voice_gmm_.weight = kVoiceGmmWeights;
-  voice_gmm_.mean = &kVoiceGmmMean[0][0];
-  voice_gmm_.covar_inverse = &kVoiceGmmCovarInverse[0][0][0];
-}
-
-PitchBasedVad::~PitchBasedVad() {}
-
-int PitchBasedVad::VoicingProbability(const AudioFeatures& features,
-                                      double* p_combined) {
-  double p;
-  double gmm_features[3];
-  double pdf_features_given_voice;
-  double pdf_features_given_noise;
-  // These limits are the same in matlab implementation 'VoicingProbGMM().'
-  const double kLimLowLogPitchGain = -2.0;
-  const double kLimHighLogPitchGain = -0.9;
-  const double kLimLowSpectralPeak = 200;
-  const double kLimHighSpectralPeak = 2000;
-  const double kEps = 1e-12;
-  for (int n = 0; n < features.num_frames; n++) {
-    gmm_features[0] = features.log_pitch_gain[n];
-    gmm_features[1] = features.spectral_peak[n];
-    gmm_features[2] = features.pitch_lag_hz[n];
-
-    pdf_features_given_voice = EvaluateGmm(gmm_features, voice_gmm_);
-    pdf_features_given_noise = EvaluateGmm(gmm_features, noise_gmm_);
-
-    if (features.spectral_peak[n] < kLimLowSpectralPeak ||
-        features.spectral_peak[n] > kLimHighSpectralPeak ||
-        features.log_pitch_gain[n] < kLimLowLogPitchGain) {
-      pdf_features_given_voice = kEps * pdf_features_given_noise;
-    } else if (features.log_pitch_gain[n] > kLimHighLogPitchGain) {
-      pdf_features_given_noise = kEps * pdf_features_given_voice;
-    }
-
-    p = p_prior_ * pdf_features_given_voice / (pdf_features_given_voice *
-        p_prior_ + pdf_features_given_noise * (1 - p_prior_));
-
-    p = LimitProbability(p);
-
-    // Combine pitch-based probability with standalone probability, before
-    // updating prior probabilities.
-    double prod_active = p * p_combined[n];
-    double prod_inactive = (1 - p) * (1 - p_combined[n]);
-    p_combined[n] = prod_active / (prod_active + prod_inactive);
-
-    if (UpdatePrior(p_combined[n]) < 0)
-      return -1;
-    // Limit prior probability. With a zero prior probability the posterior
-    // probability is always zero.
-    p_prior_ = LimitProbability(p_prior_);
-  }
-  return 0;
-}
-
-int PitchBasedVad::UpdatePrior(double p) {
-  circular_buffer_->Insert(p);
-  if (circular_buffer_->RemoveTransient(kTransientWidthThreshold,
-                                        kLowProbabilityThreshold) < 0)
-    return -1;
-  p_prior_ = circular_buffer_->Mean();
-  return 0;
-}
-
-}  // namespace webrtc