Multiple feature fusion for unimodal emotion recognition

作     者：Yang Lingzhi Ban Xiaojuan Michele Mukeshimana Chen Zhe 

作者机构：School of Computer and Communication EngineeringBeijing Key Laboratory of Knowledge Engineering for Materials ScienceUniversity of Science and Technology BeijingBeijing 10083China Citic Pacific Special Steel Holdings Qingdao Special Iron and Steel Company Limited Faculity of Engineering SciencesUniversity of BurundiBujumbura P.0.Box 1550 BujumburaBurundi Qingdao Hisense Group Company LimitedQingdao 266000China 

出 版 物：《The Journal of China Universities of Posts and Telecommunications》 (中国邮电高校学报（英文版）)

年 卷 期：2019年第26卷第2期

页      面：17-29页

核心收录：

学科分类：0809[工学-电子科学与技术（可授工学、理学学位）] 08[工学] 

基　　金：supported by the National Key Research and Development Program of China(2016YFB1001404) the National Natural Science Foundation of China(61873299,61702036,61572075) 

主　　题：multiple feature LUPI emotion recognition semi-serial fusion method 

摘      要：A new semi-serial fusion method of multiple feature based on learning using privileged information(LUPI) model was put *** exploitation of LUPI paradigm permits the improvement of the learning accuracy and its stability,by additional information and computations using optimization *** execution time is also reduced,by sparsity and dimension of testing *** essence of improvements obtained using multiple features types for the emotion recognition(speech expression recognition),is particularly applicable when there is only one modality but still need to improve the *** results show that the LUPI in unimodal case is effective when the size of the feature is *** comparison to other methods using one type of features or combining them in a concatenated way,this new method outperforms others in recognition accuracy,execution reduction,and stability.