HCC: Coordinating Communication: Visual, Social & Biological Factors in Grounding for Humans and Agents

随着越来越多的智能机器的出现，人们越来越需要开发不仅智能的技术，而且对人和他们周围的其他机器敏感，对他们使用的环境敏感。这样的理解将允许开发能够以更自然、更无缝和更流畅的方式协调它们与人类互动的技术。为了达到这些目标，本研究计划聚焦于三个关键但研究不足的互动情境，每一个情境都代表着对人际交流的不同限制：(1)共享视觉通道的物理情境，(2)融洽的社会情境，以及(3)衰老的生物情境。虽然已经对这些语境因素进行了一些研究，但还没有人讨论它们之间的相互作用，也没有人将它们归结为一个更广泛的概念，即语境在人际协调中的作用。本研究采用理论驱动的设计方法，包括实验研究、理论发展、计算建模、系统实施和评估。具体地说，该研究计划提出：a)使用启发式实验对人与人之间的交流进行严格的研究，以更详细地了解一系列语境中的人际交流；b)将研究结果正式化为提供行为预测并捕获观察到的行为模式的计算显式形式；c)将模型集成到在更大的计算体系结构内实现的对话管理器中；以及，d)通过让未经训练的人与系统进行交互来评估系统的有效性，并揭示潜在模型和理论理解中的差距。这项研究的结果将促进我们对各种语境因素在人际交流中所起作用的理论理解。这些结果将对各种科学界有用，包括那些研究基本人类交流的社区(例如，心理学家、语言学家和通信研究人员)和那些研究交互式计算系统的社区(例如，计算机科学家、计算语言学家和交互设计师)。这项研究还将提供实用的设计指南和通用计算模型，描述机器如何在日常互动中根据这些背景因素做出智能选择。在实践层面上，开发许多不同技术的技术专家可以应用通用计算模型，例如具体化代理、大规模显示、无处不在的计算、车内导航，以及为老年人和认知障碍者提供的辅助技术。

With the advent of increasing numbers of increasingly smart machines, there is a growing need to develop technologies that are not only smart, but sensitive to the people and the other machines around them, and sensitive to the context in which they are used. Such an understanding will permit the development of technologies that can coordinate their interactions with humans in a more natural, seamless and fluid fashion. To meet these goals, this research program focuses on three critical yet under-studied contexts of interaction, each of which represents a different constraint upon interpersonal communication: (1) the physical context of shared visual access, (2) the social context of rapport, and (3) the biological context of aging. While some research has been conducted on each of these contextual factors, none has addressed their interaction, nor gathered them into one broader conception of the role of context in interpersonal coordination. This research applies a theory-driven design approach that includes experimental studies, theory development, computational modeling, system implementation and evaluation. In particular, the research program proposes: a) A rigorous study of human-to-human communication using elicitation experiments to develop a more detailed understanding of interpersonal communication across a range of contexts; b) A formalization of the findings into computationally explicit forms that provide predictions of behavior and capture the observed behavioral patterns; c) Integration of the models into a dialogue manager that is implemented within a larger computational architecture; and, d) Evaluation of the implemented system by having untrained humans interact with the system in such a way as to evaluate its effectiveness and reveal gaps in the underlying models as well as in our theoretical understanding.The outcome of this research will advance our theoretical understanding of the role various contextual factors play during interpersonal communication. The results will be useful to a variety of scientific communities including those that study basic human communication (e.g., psychologists, linguists and communication researchers) and those that study interactive computational systems (e.g., computer scientists, computational linguists, and interaction designers). The research will also provide practical design guidelines and a general computational model that describes how machines can make intelligent choices on the basis of these contextual factors during everyday interactions. At a practical level, the general computational model can be applied by technologists developing many different technologies, such as embodied agents, large-scale displays, ubiquitous computing, in-car navigation, and assistive technologies for the elderly and those with cognitive impairments.