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Spotting Agreement and Disagreement: A Survey of Nonverbal Audiovisual Cues and Tools

机译:发现协议和分歧:非语言视听提示和工具的调查

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摘要

While detecting and interpreting temporal patterns of non–verbal behavioral cues in a given context is a natural and often unconscious process for humans, it remains a rather difficult task for computer systems. Nevertheless, it is an important one to achieve if the goal is to realise a naturalistic communication between humans and machines. Machines that are able to sense social attitudes like agreement and disagreement and respond to them in a meaningful way are likely to be welcomed by users due to the more natural, efficient and human–centered interaction they are bound to experience. This paper surveys the nonverbal cues that could be present during agreement and disagreement behavioural displays and lists a number of tools that could be useful in detecting them, as well as a few publicly available databases that could be used to train these tools for analysis of spontaneous, audiovisual instances of agreement and disagreement.
机译:虽然在给定的上下文中检测和解释非语言行为提示的时间模式对于人类来说是自然的且通常是无意识的过程,但对于计算机系统而言,这仍然是一项相当艰巨的任务。然而,如果目标是实现人机之间的自然主义交流,则实现这一目标很重要。能够感知诸如同意和不同意见之类的社会态度并以有意义的方式回应它们的机器,由于它们必然会体验到更加自然,高效和以人为中心的交互,因此可能会受到用户的欢迎。本文调查了在同意和不同意行为展示过程中可能出现的非语言提示,并列出了许多可用于检测它们的工具,以及一些可用于训练这些工具以进行自发性分析的公开数据库。 ,同意和不同意的视听实例。

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