| Index: webrtc/modules/audio_processing/intelligibility/intelligibility_utils.cc
|
| diff --git a/webrtc/modules/audio_processing/intelligibility/intelligibility_utils.cc b/webrtc/modules/audio_processing/intelligibility/intelligibility_utils.cc
|
| index 824b1676d895c0ab20f66c2ec6d1c1ee98a5d453..00d9b536584360a9ad989c72751bdd6e64319356 100644
|
| --- a/webrtc/modules/audio_processing/intelligibility/intelligibility_utils.cc
|
| +++ b/webrtc/modules/audio_processing/intelligibility/intelligibility_utils.cc
|
| @@ -15,6 +15,7 @@
|
| #include "webrtc/modules/audio_processing/intelligibility/intelligibility_utils.h"
|
|
|
| #include <math.h>
|
| +#include <stdlib.h>
|
| #include <string.h>
|
| #include <algorithm>
|
|
|
| @@ -31,28 +32,12 @@ float UpdateFactor(float target, float current, float limit) {
|
| return current + sign * fminf(delta, limit);
|
| }
|
|
|
| -bool cplxfinite(complex<float> c) {
|
| - return std::isfinite(c.real()) && std::isfinite(c.imag());
|
| -}
|
| -
|
| -bool cplxnormal(complex<float> c) {
|
| - return std::isnormal(c.real()) && std::isnormal(c.imag());
|
| +float AddDitherIfZero(float value) {
|
| + return value == 0.f ? std::rand() * 0.01f / RAND_MAX : value;
|
| }
|
|
|
| complex<float> zerofudge(complex<float> c) {
|
| - const static complex<float> fudge[7] = {{0.001f, 0.002f},
|
| - {0.008f, 0.001f},
|
| - {0.003f, 0.008f},
|
| - {0.0006f, 0.0009f},
|
| - {0.001f, 0.004f},
|
| - {0.003f, 0.004f},
|
| - {0.002f, 0.009f}};
|
| - static int fudge_index = 0;
|
| - if (cplxfinite(c) && !cplxnormal(c)) {
|
| - fudge_index = (fudge_index + 1) % 7;
|
| - return c + fudge[fudge_index];
|
| - }
|
| - return c;
|
| + return complex<float>(AddDitherIfZero(c.real()), AddDitherIfZero(c.imag()));
|
| }
|
|
|
| complex<float> NewMean(complex<float> mean, complex<float> data, int count) {
|
| @@ -136,10 +121,7 @@ void VarianceArray::InfiniteStep(const complex<float>* data, bool skip_fudge) {
|
| (old_sum + std::conj(sample - old_mean) * (sample - running_mean_[i]))
|
| .real();
|
| variance_[i] =
|
| - conj_sum_[i] / (count_ - 1); // + fudge[fudge_index].real();
|
| - // if (skip_fudge) {
|
| - // variance_[i] -= fudge[fudge_index].real();
|
| - // }
|
| + conj_sum_[i] / (count_ - 1);
|
| }
|
| array_mean_ += (variance_[i] - array_mean_) / (i + 1);
|
| }
|
| @@ -164,9 +146,6 @@ void VarianceArray::DecayStep(const complex<float>* data, bool /*dummy*/) {
|
| running_mean_[i] = decay_ * prev + (1.0f - decay_) * sample;
|
| running_mean_sq_[i] =
|
| decay_ * prev2 + (1.0f - decay_) * sample * std::conj(sample);
|
| - // variance_[i] = decay_ * variance_[i] + (1.0f - decay_) * (
|
| - // (sample - running_mean_[i]) * std::conj(sample -
|
| - // running_mean_[i])).real();
|
| variance_[i] = (running_mean_sq_[i] -
|
| running_mean_[i] * std::conj(running_mean_[i])).real();
|
| }
|
|
|