面向汽车领域的认知负荷感知多模态对话框架

Robert Neßelrath
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引用次数: 3

摘要

在汽车领域开发多模态人机交互的一个重要目标是保持驾驶员的低分心。然而,认知负荷的测量是困难和不准确的,但预测对话和呈现策略在这方面的影响的方法是有希望的。本文讨论了认知负荷的理论和相关工作,并确定了在监测和减少驾驶员分心方面发挥作用的对话系统组件。随后,我们介绍了一个对话系统框架架构,该架构支持认知负荷预测和情境依赖的人机交互决策和操作。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Towards a Cognitive Load Aware Multimodal Dialogue Framework for the Automotive Domain
A significant aim in developing multimodal HCI for the automotive domain is to keep driver's distraction low. However, the measurement of the cognitive load is difficult and inaccurate but an approach to predict the effect of dialogue and presentation strategies on this is promising. In this paper we discuss cognitive load in theory and related work, and identify dialogue system components that play a role for monitoring and reducing driver's distraction. Subsequently we introduce a dialogue system framework architecture that supports cognitive load prediction and situation-dependent decision making & manipulation of the HCI.
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