Design and Analysis of a Human-Machine Interaction System for Researching Human's Dynamic Emotion

doi:10.1109/TSMC.2019.2958094

CORC > 自动化研究所 > 中国科学院自动化研究所 > 模式识别国家重点实验室 > 智能交互

	Design and Analysis of a Human-Machine Interaction System for Researching Human's Dynamic Emotion
	Sun, Xiao 1; Pei, Zhengmeng 1; Zhang, Chen 1; Li, Guoqiang 2; Tao, Jianhua 3
刊名	IEEE TRANSACTIONS ON SYSTEMS MAN CYBERNETICS-SYSTEMS
	2021-10-01
卷号	51 期号:10 页码:6111-6121
关键词	Heuristic algorithms Hidden Markov models Robots Sun Vehicle dynamics Task analysis Deep learning Emotional guidance emotional transfer human-machine interaction Markov chain Monte Carlo
ISSN号	2168-2216
DOI	10.1109/TSMC.2019.2958094
通讯作者	Li, Guoqiang(li.g@sjtu.edu.cn)
英文摘要	Dynamic emotion is typically used to facilitate human-machine interactions. Conversational data from social media contain a considerable amount of useful information, and such data are the foundation for researching dynamic and artificial emotion. At present, most human-machine interaction systems focus on the complexity and accuracy of the dialog but neglect the emotional characteristics of the speaker. When generating a dialog considering the emotional personality of the interlocutor, controlling, and guiding the dialog to a specified direction are essential. This article presents a system for studying dynamic emotions in human-computer interaction from the perspective of emotional transfer and guidance. Based on the emotional state of the interlocutor and the distribution of emotional transfer, the process of emotional transfer is simulated and sampled, and the sequence of emotional guidance is generated. In this system, two algorithms are proposed. A generative Markov chain Monte Carlo (GEN-MCMC) algorithm is proposed to generate a variety of emotional transfer sequences that fit the talke's personality dynamically based on the real-world dialog. Further, a guiding MCMC (GUI-MCMC) algorithm-based GEN-MCMC is proposed to generate the emotional guiding sequences. The generated emotional sequences by GEN-MCMC were evaluated in two aspects: 1) consistency and 2) diversity. The experimental results show that the GEN-MCMC algorithm performs better than the general sequence generation algorithm in terms of consistency and diversity in generating emotional states. The GUI-MCMC was able to generate a proper stimulus sequence when given the first and target emotions. An emotional stimulus sequence can simulate the emotional transfer of the interlocutor in the process of dialogue, and give the observer appropriate reference to guide and control the emotions of dialogue. The experimental results show that the proposed system can effectively model the dynamic emotion in emotional transfer and guidance, which can be further used to build chat robots, intelligent assistants, and human-machine interaction systems. The models can also be used for emotional induction and enhance the feel-good or feel-terrible factor in human-machine communication applications, such as medical treatment of mental diseases, interrogation, and psychological attack and defense.
资助项目	State Program of the National Natural Science Foundation of China[61976078] ; State Program of the National Natural Science Foundation of China[61732013] ; China Postdoctoral Science Foundation[2017T100447] ; Open Project Program of the National Laboratory of Pattern Recognition ; National Key Research and Development Program of China[2019YFA0706203]
WOS关键词	REGRESSION ; NETWORK ; MCMC
WOS研究方向	Automation & Control Systems ; Computer Science
语种	英语
出版者	IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
WOS记录号	WOS:000696079100023
资助机构	State Program of the National Natural Science Foundation of China ; China Postdoctoral Science Foundation ; Open Project Program of the National Laboratory of Pattern Recognition ; National Key Research and Development Program of China
内容类型	期刊论文
源URL	[http://ir.ia.ac.cn/handle/173211/46016]
专题	模式识别国家重点实验室_智能交互
通讯作者	Li, Guoqiang
作者单位	1.Hefei Univ Technol, Sch Comp & Informat, Hefei 230601, Peoples R China 2.Shanghai Jiao Tong Univ, Sch Software, Shanghai 200240, Peoples R China 3.Chinese Acad Sci, Inst Automat, Natl Lab Pattern Recognit, Beijing 100190, Peoples R China
推荐引用方式 GB/T 7714	Sun, Xiao,Pei, Zhengmeng,Zhang, Chen,et al. Design and Analysis of a Human-Machine Interaction System for Researching Human's Dynamic Emotion[J]. IEEE TRANSACTIONS ON SYSTEMS MAN CYBERNETICS-SYSTEMS,2021,51(10):6111-6121.
APA	Sun, Xiao,Pei, Zhengmeng,Zhang, Chen,Li, Guoqiang,&Tao, Jianhua.(2021).Design and Analysis of a Human-Machine Interaction System for Researching Human's Dynamic Emotion.IEEE TRANSACTIONS ON SYSTEMS MAN CYBERNETICS-SYSTEMS,51(10),6111-6121.
MLA	Sun, Xiao,et al."Design and Analysis of a Human-Machine Interaction System for Researching Human's Dynamic Emotion".IEEE TRANSACTIONS ON SYSTEMS MAN CYBERNETICS-SYSTEMS 51.10(2021):6111-6121.