Fixing a comment on AEC divergence metric.

webrtc/modules/audio_processing/aec/aec_core.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 56 matching lines @@
 
 // Buffer size (samples)
 static const size_t kBufSizePartitions = 250;  // 1 second of audio in 16 kHz.
 
 // Metrics
 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
-// |kDivergentFilterFractionAggregationWindowSize| samples. Current value
-// corresponds to 1 second at 16 kHz.
+// |kSubCountLen + 1| * PART_LEN samples. Divergence metric takes the statistics
+// of |kDivergentFilterFractionAggregationWindowSize| audio levels. The
+// following value corresponds to 1 second at 16 kHz.
 static const int kDivergentFilterFractionAggregationWindowSize = 50;
 
 // 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
 static const int freqAvgIc = PART_LEN / 2;
 
 // Matlab code to produce table:
 // win = sqrt(hanning(63)); win = [0 ; win(1:32)];
 // fprintf(1, '\t%.14f, %.14f, %.14f,\n', win);
@@ skipping 1891 matching lines @@
 
 int WebRtcAec_system_delay(AecCore* self) {
   return self->system_delay;
 }
 
 void WebRtcAec_SetSystemDelay(AecCore* self, int delay) {
   assert(delay >= 0);
   self->system_delay = delay;
 }
 }  // namespace webrtc