Computational study of human communication dynamic

J-HGBU '11 Pub Date : 2011-12-01 DOI:10.1145/2072572.2072578
Louis-Philippe Morency
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引用次数: 5

Abstract

Face-to-face communication is a highly dynamic process where participants mutually exchange and interpret linguistic and gestural signals. Even when only one person speaks at the time, other participants exchange information continuously amongst themselves and with the speaker through gesture, gaze, posture and facial expressions. To correctly interpret the high-level communicative signals, an observer needs to jointly integrate all spoken words, subtle prosodic changes and simultaneous gestures from all participants. In this paper, we present our ongoing research effort at USC MultiComp Lab to create models of human communication dynamic that explicitly take into consideration the multimodal and interpersonal aspects of human face-to-face interactions. The computational framework presented in this paper has wide applicability, including the recognition of human social behaviors, the synthesis of natural animations for robots and virtual humans, improved multimedia content analysis, and the diagnosis of social and behavioral disorders (e.g., autism spectrum disorder).
人类交流动态的计算研究
面对面的交流是一个高度动态的过程,参与者相互交换和解释语言和手势信号。即使只有一个人说话,其他参与者也会通过手势、凝视、姿势和面部表情不断地在他们之间和说话者之间交换信息。为了正确解读高层次的交际信号,观察者需要将所有参与者的言语、细微的韵律变化和同步的手势综合起来。在本文中,我们介绍了我们在南加州大学MultiComp实验室正在进行的研究工作,以创建人类交流动态模型,明确考虑到人类面对面互动的多模态和人际方面。本文提出的计算框架具有广泛的适用性,包括人类社会行为的识别,机器人和虚拟人的自然动画的合成,改进的多媒体内容分析,以及社会和行为障碍(如自闭症谱系障碍)的诊断。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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