Inproceedings,

Towards a Cognitive Load Ready Multimodal Dialogue System for In-Vehicle Human-Machine Interaction

, and .
Adjunct Proceedings of the 5th International Conference on Automotive User Interfaces and Interactive Vehicular Applications, Eindhoven, page 49-52. (October 2013)

Abstract

This position paper approaches one of the critical topics in the development of multimodal HMI for the automotive domain: keeping the driver's distraction low. However, the estimation of the cognitive load (CL), of which distraction is one symptom, is dicult and inaccurate. Instead our research indicates that an approach to predict the e ect of dialogue and presentation strategies on this is more promising. In this paper we discuss CL in theory and related work, and identify dialogue system components that play a role for monitoring and reducing driver distraction. Subsequently we introduce a dialogue system framework architecture that supports CL prediction and situation-dependent decision making & manipulation of the HMI.

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