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科技导报  2015 

基于组合核函数SVM的说话人识别方法

DOI: 10.3981/j.issn.1000-7857.2015.01.016, PP. 90-94

Keywords: 说话人识别,支持向量机,组合核函数,多重网格搜索

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Abstract:

鉴于应用支持向量机进行说话人识别过度依赖于选择核函数的问题,提出一种基于组合核函数支持向量机(SVM)的说话人识别方法.对多项式核函数、径向基核函数进行线性加权,构建既具有全局核函数优点又具有局部核函数优点的组合核函数,并通过多重网格搜索调节权重系数使组合核函数适用于当前数据分布,确定组合核函数SVM的最优参数,实现对说话人的有效识别.对TIMIT数据集和含噪声数据集的仿真实验显示,基于组合核函数SVM的说话人识别性能明显优于单一的多项式核函数、径向基核函数和线性核函数.

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