基于卷积神经网络的电子变调语音检测算法

摘要

提出了一种基于梅尔倒谱系数统计特征和卷积神经网络的电子变调语音检测算法.首先提取待测语音的梅尔倒谱系数及其差分系数,并将上述系数的统计特征进行有针对性的构造,作为卷积神经网络的输入.从卷积核尺寸、卷积核个数以及池化层尺寸等方面,对24种不同网络结构进行了测试评估,最终确定了可有效用于变调检测的卷积神经网络结构.实验结果表明,所提出的算法能够有效地检测出电子变调的痕迹,并可准确估计出电子变调语音经过的具体伪造操作,为电子变调语音的检测提供了一种新的方法.%An electronic disguised voice detection algorithm based on the statistical features of MFCC and the convolution neural network was proposed.Firstly,the statistical features of MFCC were extracted and reconstructed as the input of convolution neural network.Considering the convolution kernel size,the number of convolution kernels and the pooling size,24 different network structures were evaluated in this work.Finally,the convolution neural network structure which could be effectively used for electronic disguised voice detection was determined.The experimental results show that the proposed algorithm can effectively detect the trace of electronic disguising.Meanwhile,the specific forgery operation of the electronic disguised voice can also be estimated.