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 eect 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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