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，越来越需要开发不仅智能，而且对周围的人和其他机器敏感的技术，以及对使用它们的环境敏感的技术。这种理解将使技术得以发展，以更自然、无缝和流畅的方式协调它们与人类的互动。为了实现这些目标，本研究计划将重点放在三个关键但尚未得到充分研究的互动环境上，每一个都代表了人际交流的不同约束：(1)共享视觉访问的物理环境，(2)融洽的社会环境，(3)衰老的生物环境。虽然对这些背景因素进行了一些研究，但没有一个研究涉及它们之间的相互作用，也没有将它们集中到一个关于背景在人际协调中的作用的更广泛的概念中。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、系统实现和评估。具体而言，该研究计划提出：a)利用启发实验对人与人之间的交流进行严格研究，以更详细地了解各种背景下的人际交流；b)将发现形式化为计算明确的形式，提供行为预测并捕获观察到的行为模式；c)将模型集成到对话管理器中，该对话管理器在更大的计算体系结构中实现；d)通过让未经训练的人与系统交互来评估已实现的系统，从而评估其有效性，并揭示基础模型以及我们理论理解中的差距。本研究的结果将促进我们对人际交往中各种情境因素作用的理论认识。这些结果将对各种科学团体有用，包括那些研究基本人类交流的人（例如，心理学家，语言学家和交流研究人员）和那些研究交互式计算系统的人（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一个通用的计算模型，描述机器如何在日常交互中根据这些上下文因素做出智能选择。在实际层面上，通用计算模型可以被开发许多不同技术的技术人员应用，例如具身代理、大规模显示、无处不在的计算、车内导航以及针对老年人和认知障碍患者的辅助技术。

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.