Speech Emotion Recognition Based on Supervised Locally Linear Embedding

摘要：

Speech emotion recognition is a new and challenging subject in signal processing area. In this paper, a new feature extraction method based on supervised locally linear embedding (SLLE) is proposed for speech emotion recognition. SLLE is used to implement nonlinear dimensionality reduction on high-dimensional emotional speech features with nonlinear manifold structure. And then the enhanced low-dimensional data representations embedded with SLLE are extracted for speech emotion recognition. Experimental results on natural emotional Chinese speech database confirm the validity and high performance of the proposed method.

作者: Shiqing Zhang Lemin Li Zhijin Zhao

作者单位: School of Communication and Information Engineering, University of Electronic Science and Technology School of Communication and Information Engineering, University of Electronic Science and Technology School of Telecommunication, Hangzhou Dianzi University, Hangzhou, China

会议类型: 国际会议

会议名称: 2010 International Conference on Communications,Circuits and Systems(2010年通信、电路与系统国际会议)

会议地点: 成都

会议语种:英文

页码: 401-404

在线出版日期: 2010-06-28（万方平台首次上网日期，不代表论文的发表时间）