blob: 96519759133197209f20727433daf122dce6cb31 [file] [log] [blame]
/*
* 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/vad/gmm.h"
#include <math.h>
#include <stdlib.h>
#include "webrtc/typedefs.h"
namespace webrtc {
static const int kMaxDimension = 10;
static void RemoveMean(const double* in,
const double* mean_vec,
int dimension,
double* out) {
for (int n = 0; n < dimension; ++n)
out[n] = in[n] - mean_vec[n];
}
static double ComputeExponent(const double* in,
const double* covar_inv,
int dimension) {
double q = 0;
for (int i = 0; i < dimension; ++i) {
double v = 0;
for (int j = 0; j < dimension; j++)
v += (*covar_inv++) * in[j];
q += v * in[i];
}
q *= -0.5;
return q;
}
double EvaluateGmm(const double* x, const GmmParameters& gmm_parameters) {
if (gmm_parameters.dimension > kMaxDimension) {
return -1; // This is invalid pdf so the caller can check this.
}
double f = 0;
double v[kMaxDimension];
const double* mean_vec = gmm_parameters.mean;
const double* covar_inv = gmm_parameters.covar_inverse;
for (int n = 0; n < gmm_parameters.num_mixtures; n++) {
RemoveMean(x, mean_vec, gmm_parameters.dimension, v);
double q = ComputeExponent(v, covar_inv, gmm_parameters.dimension) +
gmm_parameters.weight[n];
f += exp(q);
mean_vec += gmm_parameters.dimension;
covar_inv += gmm_parameters.dimension * gmm_parameters.dimension;
}
return f;
}
} // namespace webrtc