User behavior fusion in dialog management with multi-modal history cues

doi:10.1007/s11042-014-2161-5

	User behavior fusion in dialog management with multi-modal history cues
	Yang, Minghao; Tao, Jianhua; Chao, Linlin; Li, Hao; Zhang, Dawei; Che, Hao; Gao, Tingli; Liu, Bin
发表期刊	MULTIMEDIA TOOLS AND APPLICATIONS
	2015-11-01
卷号	74 期号:22 页码:10025-10051
文章类型	Article
摘要	It enhances user experience by making the talking avatar be sensitive to user behaviors in human computer interaction (HCI). In this study, we combine user's multi-modal behaviors with behaviors' historical information in dialog management (DM) to improve the avatar's sensitivity not only to user explicit behavior (speech command) but also to user supporting expression (emotion and gesture, etc.). In the dialog management, according to the different contributions of facial expression, gesture and head motion to speech comprehension, we divide the user's multi-modal behaviors into three categories: complementation, conflict and independence. The behavior categories could be first automatically obtained from a short-term and time-dynamic (STTD) fusion model with audio-visual input. Different behavior category leads to different avatar's response in later dialog turns. Usually, the conflict behavior reflects user's ambiguous intention (for example: user says "no" while he (her) is smiling). In this case, the trial-and-error schema is adopted to eliminate the conversation ambiguity. For the later dialog process, we divide all the avatar dialog states into four types: "Ask", "Answer", "Chat" and "Forget". With the detection of complementation and independence behaviors, the user supporting expression as well as his (her) explicit behavior could be estimated as triggers for topic maintenance or transfer among four dialog states. At the first section of experiments, we discuss the reliability of STTD model for user behavior classification. Based on the proposed dialog management and STTD model, we continue to construct a drive route information query system by connecting the user behavior sensitive dialog management (BSDM) to a 3D talking avatar. The practical conversation records of avatar with different users show that the BSDM makes the avatar be able to understand and be sensitive to the users' facial expressions, emotional voice and gesture, which improves user experience on multi-modal human computer conversation.
关键词	Dialog Management (Dm) Multi-modal Data Fusion Human Computer Interaction (Hci) Emotion Detection
WOS标题词	Science & Technology ; Technology
DOI	10.1007/s11042-014-2161-5
收录类别	SCI
语种	英语
WOS研究方向	Computer Science ; Engineering
WOS类目	Computer Science, Information Systems ; Computer Science, Software Engineering ; Computer Science, Theory & Methods ; Engineering, Electrical & Electronic
WOS记录号	WOS:000364019400011
引用统计	被引频次：6[WOS] [WOS记录] [WOS相关记录]
文献类型	期刊论文
条目标识符	http://ir.ia.ac.cn/handle/173211/40843
专题	多模态人工智能系统全国重点实验室_智能交互
推荐引用方式 GB/T 7714	Yang, Minghao,Tao, Jianhua,Chao, Linlin,et al. User behavior fusion in dialog management with multi-modal history cues[J]. MULTIMEDIA TOOLS AND APPLICATIONS,2015,74(22):10025-10051.
APA	Yang, Minghao.,Tao, Jianhua.,Chao, Linlin.,Li, Hao.,Zhang, Dawei.,...&Liu, Bin.(2015).User behavior fusion in dialog management with multi-modal history cues.MULTIMEDIA TOOLS AND APPLICATIONS,74(22),10025-10051.
MLA	Yang, Minghao,et al."User behavior fusion in dialog management with multi-modal history cues".MULTIMEDIA TOOLS AND APPLICATIONS 74.22(2015):10025-10051.