LI Hai-Feng
School of Computer Science and Technology, Harbin Institute of Technology, Harbin 150001, China;Shenzhen Academy of Aerospace Technology, Shenzhen 518057, ChinaCHEN Jing
School of Computer Science and Technology, Harbin Institute of Technology, Harbin 150001, ChinaMA Lin
School of Computer Science and Technology, Harbin Institute of Technology, Harbin 150001, China;Shenzhen Academy of Aerospace Technology, Shenzhen 518057, ChinaBO Hong-Jian
Shenzhen Academy of Aerospace Technology, Shenzhen 518057, ChinaXU Cong
School of Computer Science and Technology, Harbin Institute of Technology, Harbin 150001, ChinaLI Hong-Wei
School of Computer Science and Technology, Harbin Institute of Technology, Harbin 150001, ChinaNational Key Research and Development Program of China (2018YFC0806800); National Natural Science Foundation of China (61671187); Shenzhen Foundational Research Fund (JCYJ20180507183608379); Key Laboratory Project of Innovation Environment Construction Plan of Shenzhen Municipality (ZDSYS201707311437102); Open Fund of MOE-Microsoft Key Laboratory of Natural Language Processing and Speech (HIT.KLOF.20160xx); Applied Basic Research Programs(CJN13J004); Basic Research and Application Programs Foundation of Guangdong Province (2019A1515111179)
Emotion recognition is an interdisciplinary research field which relates to cognitive science, psychology, signal processing, pattern recognition, artificial intelligence, and so on, aiming at helping computer understand human emotion state to realize natural human-computer interaction. In this survey, the psychological theory of emotion is firstly introduced as the theoretical basis for the emotion model used in emotion recognition, including appraisal theory, dimensional models of emotion, brain mechanisms, and computing models. Then, the advanced technologies of dimensional emotion recognition from the artificial intelligence perspective, such as the speech emotion corpora, feature extraction, classification, are presented in detail. Finally, the challenges of dimensional emotion recognition are discussed and the workable solutions and future research directions are proposed.
李海峰,陈婧,马琳,薄洪健,徐聪,李洪伟.维度语音情感识别研究综述.软件学报,2020,31(8):2465-2491
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