Retyped the frequency estimate of the comfort noise for the higher band to harmonize the AEC code(#4

webrtc/modules/audio_processing/aec/aec_core_mips.c

 /*
  *  Copyright (c) 2013 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.
  */
 
 /*
  * The core AEC algorithm, which is presented with time-aligned signals.
  */
 
 #include "webrtc/modules/audio_processing/aec/aec_core.h"
 
 #include <math.h>
 
 #include "webrtc/common_audio/signal_processing/include/signal_processing_library.h"
 #include "webrtc/modules/audio_processing/aec/aec_core_internal.h"
 #include "webrtc/modules/audio_processing/aec/aec_rdft.h"
 
 static const int flagHbandCn = 1; // flag for adding comfort noise in H band
 extern const float WebRtcAec_weightCurve[65];
 extern const float WebRtcAec_overDriveCurve[65];
 
 void WebRtcAec_ComfortNoise_mips(AecCore* aec,
                                  float efw[2][PART_LEN1],
-                                 complex_t* comfortNoiseHband,
+                                 float comfortNoiseHband[2][PART_LEN1],
                                  const float* noisePow,
                                  const float* lambda) {
   int i, num;
   float rand[PART_LEN];
   float noise, noiseAvg, tmp, tmpAvg;
   int16_t randW16[PART_LEN];
   complex_t u[PART_LEN1];
 
   const float pi2 = 6.28318530717959f;
   const float pi2t = pi2 / 32768;
@@ skipping 227 matching lines @@
   tmp = sqrtf(WEBRTC_SPL_MAX(1 - lambda[PART_LEN] * lambda[PART_LEN], 0));
   //tmp = 1 - lambda[i];
   efw[0][PART_LEN] += tmp * u[PART_LEN][0];
   efw[1][PART_LEN] += tmp * u[PART_LEN][1];
 
   // For H band comfort noise
   // TODO: don't compute noise and "tmp" twice. Use the previous results.
   noiseAvg = 0.0;
   tmpAvg = 0.0;
   num = 0;
-  if ((aec->sampFreq == 32000 || aec->sampFreq == 48000) && flagHbandCn == 1) {
+  if (aec->num_bands > 1 && flagHbandCn == 1) {
     for (i = 0; i < PART_LEN; i++) {
       rand[i] = ((float)randW16[i]) / 32768;
     }
 
     // average noise scale
     // average over second half of freq spectrum (i.e., 4->8khz)
     // TODO: we shouldn't need num. We know how many elements we're summing.
     for (i = PART_LEN1 >> 1; i < PART_LEN1; i++) {
       num++;
       noiseAvg += sqrtf(noisePow[i]);
@@ skipping 19 matching lines @@
       tmp = pi2 * rand[i - 1];
 
       // Use average noise for H band
       u[i][0] = noiseAvg * (float)cos(tmp);
       u[i][1] = -noiseAvg * (float)sin(tmp);
     }
     u[PART_LEN][1] = 0;
 
     for (i = 0; i < PART_LEN1; i++) {
       // Use average NLP weight for H band
-      comfortNoiseHband[i][0] = tmpAvg * u[i][0];
-      comfortNoiseHband[i][1] = tmpAvg * u[i][1];
+      comfortNoiseHband[0][i] = tmpAvg * u[i][0];
+      comfortNoiseHband[1][i] = tmpAvg * u[i][1];
     }
+  } else {
+    memset(comfortNoiseHband, 0,
+           2 * PART_LEN1 * sizeof(comfortNoiseHband[0][0]));
   }
 }
 
 void WebRtcAec_FilterFar_mips(
     int num_partitions,
     int x_fft_buf_block_pos,
     float x_fft_buf[2][kExtendedNumPartitions * PART_LEN1],
     float h_fft_buf[2][kExtendedNumPartitions * PART_LEN1],
     float y_fft[2][PART_LEN1]) {
   int i;
@@ skipping 446 matching lines @@
   );
 }
 
 void WebRtcAec_InitAec_mips(void) {
   WebRtcAec_FilterFar = WebRtcAec_FilterFar_mips;
   WebRtcAec_FilterAdaptation = WebRtcAec_FilterAdaptation_mips;
   WebRtcAec_ScaleErrorSignal = WebRtcAec_ScaleErrorSignal_mips;
   WebRtcAec_ComfortNoise = WebRtcAec_ComfortNoise_mips;
   WebRtcAec_OverdriveAndSuppress = WebRtcAec_OverdriveAndSuppress_mips;
 }