Towards a Cognitive Load Ready Multimodal Dialogue System for In-Vehicle Human-Machine Interaction
R. Neßelrath, и M. Feld. Adjunct Proceedings of the 5th International Conference on Automotive User Interfaces and Interactive Vehicular Applications, Eindhoven, стр. 49-52. (октября 2013)
Аннотация
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 di�cult 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.
%0 Conference Paper
%1 nesselrath2013clready
%A Neßelrath, Robert
%A Feld, Michael
%B Adjunct Proceedings of the 5th International Conference on Automotive User Interfaces and Interactive Vehicular Applications, Eindhoven
%D 2013
%K cognitive dialogue load multimodal system ubicomm2014
%P 49-52
%T Towards a Cognitive Load Ready Multimodal Dialogue System for In-Vehicle Human-Machine Interaction
%X 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 di�cult 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.
@inproceedings{nesselrath2013clready,
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 di�cult 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.},
added-at = {2014-04-20T18:15:31.000+0200},
author = {Ne{\ss}elrath, Robert and Feld, Michael},
biburl = {https://www.bibsonomy.org/bibtex/20c236bab9d9a51b412a431d64db29a63/porta},
booktitle = {Adjunct Proceedings of the 5th International Conference on Automotive User Interfaces and Interactive Vehicular Applications, Eindhoven},
file = {nesselrath2013clready.pdf:nesselrath2013clready.pdf:PDF},
groups = {public},
interhash = {b3b959782f27fb5cfe16183ba9b584e0},
intrahash = {0c236bab9d9a51b412a431d64db29a63},
keywords = {cognitive dialogue load multimodal system ubicomm2014},
month = {October},
pages = {49-52},
timestamp = {2014-11-01T12:24:55.000+0100},
title = {Towards a Cognitive Load Ready Multimodal Dialogue System for In-Vehicle Human-Machine Interaction},
username = {porta},
year = 2013
}