摘要
提出了一种基于遗传优化RBF神经网络的声纹识别算法,该算法中采用遗传算法对传统的RBF神经网络基函数中心以及宽度进行优化处理,克服了传统RBF神经网络参数难以确定的缺陷。同时,算法结合心理声学模型,提取了能表现说话人个性特征的Mel倒谱系数为特征进行说话人识别,可较好地提升系统的抗噪性能。仿真实验结果表明,与传统RBF神经网络相比,该方法具有快速学习网络权重的能力,并且网络的全局寻优能力强,使得系统的识别率进一步提高。
This paper proposed an algorithms of voiceprint recognition based on the genetic optimized RBF neural network, the center and width of RBF neural network are optimized by using the genetic algorithm, combined with psychoacoustic model, extracted Mel cepstrum coefficients that stand for personality of the speaker. The experimental results showed that this method can obtain more optimum model parameters and better results than that of the traditional RBF neural network.
出处
《信息技术》
2012年第5期168-170,共3页
Information Technology
关键词
遗传算法
RBF神经网络
声纹识别
genetic algorithm
RBF neural network
voiceprint recognition
