基于局部保持投影和主元分析的语音情感识别

Speech Emotion Recognition Based on Locality Preserving Projections and PCA

为了提高情感识别的准确性,该文以语音信号为研究对象,提出了一种新型的语音情感识别方法.将局部保持投影算法(LPP)的思想融入到主元分析(PCA)的目标函数中,使得在原始变量空间投影到低维空间的过程中,不仅实现了整体方差的最大化,而且保持了局部近邻结构不变,有利于全局和局部特征的全面提取,克服了传统PCA方法只关注全局结构特征而忽略局部特征的缺陷.对比实验结果验证了该方法的可行性和有效性,实现了对喜悦、愤怒、悲伤、恐惧和中性5种人类基本情感的识别,研究成果将为情感识别提供新的研究方法,促进人机交互系统进一步深入发展.

In order to improve the accuracy of emotion recognition, this paper proposes a novel speech emotion recognition algorithm, and takes speech signal as the research subject. The idea of locality preserving projection（LPP） is integrated into the objective function of PCA. It not only realizes the maximum of the total variance, but also keeps the local neighbor structure. That is beneficial to comprehensive extraction of global and local features, and overcomes the defects that the traditional PCA can only keep the structure in global and can not maintain the structure in local. Experiment results verify the feasibility and effectiveness of the proposed method, and accomplish recognition for five kinds of human emotion（joy,anger, sadness, fear, neutral）. Research results provide new methods into emotion recognition, promote the further development of human-computer interaction system.