张波,张雪英,陈桂军,孙颖

• 1:太原理工大学信息与计算机学院

摘要(Abstract)：

在智能人-机交互系统中,语音情感识别是目前的研究热点之一,支持向量机方法被广泛用于语音情感识别。然而,支持向量机方法存在噪声和野值敏感问题,往往难以进行精确识别。为了解决该问题,通过对隶属度函数进行深入研究,设计一种新的基于样本到类内超平面距离的隶属度函数,并基于该隶属度函数优化了模糊支持向量机分类超平面,从而提高了支持向量机的抗噪性和泛化能力。在多种情感语音库上进行实验仿真测试,结果表明,所提出的方法能够有效利用样本间的紧密度、边界样本点和过样本类中心的超平面来构造最优超平面,从而提高语音情感识别的准确率。

关键词(KeyWords)： 语音情感识别;模糊支持向量机;隶属度函数;孤立点;类内超平面;精确识别

Abstract:

Keywords:

基金项目(Foundation): 国家自然科学基金资助项目(61371193)~~

作者(Author): 张波,张雪英,陈桂军,孙颖

DOI: 10.16652/j.issn.1004-373x.2018.16.041

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