Adding fraction of filter divergence in AEC metrics.

webrtc/modules/audio_processing/aec/aec_core.cc

Index: webrtc/modules/audio_processing/aec/aec_core.cc
diff --git a/webrtc/modules/audio_processing/aec/aec_core.cc b/webrtc/modules/audio_processing/aec/aec_core.cc
index e23a79312b05beb9c7904c103c605a5d454b3e69..3235ee439cc66297eaa8c21c2bedd6dcb0803cf8 100644
--- a/webrtc/modules/audio_processing/aec/aec_core.cc
+++ b/webrtc/modules/audio_processing/aec/aec_core.cc
@@ -50,6 +50,12 @@ static const size_t kSubCountLen = 4;
 static const size_t kCountLen = 50;
 static const int kDelayMetricsAggregationWindow = 1250;  // 5 seconds at 16 kHz.
 
+// Divergence metric is based on audio level, which gets updated every
+// |kCountLen + 1| * 10 milliseconds. Divergence metric takes the statistics of
+// |kDivergeMetricAggregationWindow| samples. Current value corresponds to 0.5
+// seconds at 16 kHz.
+static const int kDivergeMetricAggregationWindow = 25;

[peah-webrtc, 2016/04/06 11:01:10]

This should probably be called kDivergeMetricAggregationWindowSize.

[minyue-webrtc, 2016/04/06 13:35:37]

Done.

+
 // Quantities to control H band scaling for SWB input
 static const float cnScaleHband = 0.4f;  // scale for comfort noise in H band.
 // Initial bin for averaging nlp gain in low band
@@ -150,16 +156,18 @@ __inline static float MulIm(float aRe, float aIm, float bRe, float bIm) {
   return aRe * bIm + aIm * bRe;
 }
 
-PowerLevel::PowerLevel()
 // TODO(minyue): Due to a legacy bug, |framelevel| and |averagelevel| use a
-// window, of which the length is 1 unit longer than indicated. Remove "+1"
-// when the code is refactored.
-: framelevel(kSubCountLen + 1),
-  averagelevel(kCountLen + 1) {
+// window, of which the length is 1 unit longer than indicated. Remove "+1" when
+// the code is refactored.
+PowerLevel::PowerLevel()
+    : framelevel(kSubCountLen + 1),
+      averagelevel(kCountLen + 1) {
 }
 
 // TODO(minyue): Moving some initialization from WebRtcAec_CreateAec() to ctor.
-AecCore::AecCore() = default;
+AecCore::AecCore()
+    : divergent_filter_fraction(kDivergeMetricAggregationWindow) {
+}
 
 static int CmpFloat(const void* a, const void* b) {
   const float* da = (const float*)a;
@@ -562,6 +570,8 @@ static void InitMetrics(AecCore* self) {
   InitStats(&self->erle);
   InitStats(&self->aNlp);
   InitStats(&self->rerl);
+
+  self->divergent_filter_fraction.Reset();
 }
 
 static float CalculatePower(const float* in, size_t num_samples) {
@@ -605,6 +615,21 @@ static void UpdateMetrics(AecCore* aec) {
     aec->stateCounter++;
   }
 
+  if (aec->linoutlevel.framelevel.EndOfBlock()) {
+    const float near_level = aec->nearlevel.framelevel.GetLatestMean();
+    const float level_increase =
+        aec->linoutlevel.framelevel.GetLatestMean() - near_level;
+    const bool output_signal_active =
+        aec->nlpoutlevel.framelevel.GetLatestMean() >
+            actThresholdClean * aec->nlpoutlevel.minlevel;
+    // Level increase should be, in principle, negative, when the filter
+    // does not diverge. Here we allow some margin (0.01 * near end level) and
+    // numerical error (1.0). We count divergence only when the AEC output
+    // signal is active.
+    aec->divergent_filter_fraction.AddObservation(output_signal_active &&
+        level_increase > std::max(0.01 * near_level, 1.0));

[peah-webrtc, 2016/04/06 11:01:10]

If this would be a general and common task maybe a separate class would be
merited but at this stage this is only used here, and what is done is so simple,
so I don't think that a separate utility class is motivated for this.

I think the class instead should be locally implemented inside this file.

[minyue-webrtc, 2016/04/06 13:35:37]

Done.

+  }
+
   if (aec->farlevel.averagelevel.EndOfBlock()) {
     if (aec->farlevel.minlevel < noisyPower) {
       actThreshold = actThresholdClean;