Multimodal data collection of human-robot humorous interactions in the Joker project

L. Devillers, S. Rosset, G. D. Duplessis, M. A. Sehili, Lucile Bechade, Agnès Delaborde, Clément Gossart, Vincent Letard, Fan Yang, Y. Yemez, Bekir Berker Turker, T. M. Sezgin, Kevin El Haddad, S. Dupont, Daniel Luzzati, Y. Estève, E. Gilmartin, N. Campbell
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引用次数: 40

Abstract

Thanks to a remarkably great ability to show amusement and engagement, laughter is one of the most important social markers in human interactions. Laughing together can actually help to set up a positive atmosphere and favors the creation of new relationships. This paper presents a data collection of social interaction dialogs involving humor between a human participant and a robot. In this work, interaction scenarios have been designed in order to study social markers such as laughter. They have been implemented within two automatic systems developed in the Joker project: a social dialog system using paralinguistic cues and a task-based dialog system using linguistic content. One of the major contributions of this work is to provide a context to study human laughter produced during a human-robot interaction. The collected data will be used to build a generic intelligent user interface which provides a multimodal dialog system with social communication skills including humor and other informal socially oriented behaviors. This system will emphasize the fusion of verbal and non-verbal channels for emotional and social behavior perception, interaction and generation capabilities.
Joker项目中人机幽默互动的多模式数据收集
笑是一种表现娱乐和参与的非凡能力,是人类交往中最重要的社会标志之一。一起笑实际上可以帮助建立一个积极的氛围,有利于建立新的关系。本文介绍了人类参与者和机器人之间涉及幽默的社会互动对话的数据收集。在这项工作中,互动场景的设计是为了研究笑声等社会标志。它们已经在Joker项目中开发的两个自动系统中实现:使用副语言线索的社交对话系统和使用语言内容的基于任务的对话系统。这项工作的主要贡献之一是为研究人机交互过程中产生的人类笑声提供了一个背景。收集到的数据将用于构建一个通用的智能用户界面,该界面提供一个具有社交沟通技巧的多模态对话系统,包括幽默和其他非正式的社交导向行为。该系统将强调情感和社会行为感知、互动和生成能力的语言和非语言渠道的融合。
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