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Estimating cognitive load using pupil diameter during a spoken dialogue task

Authors:

Zeljko MedenicaAuthors Info & Claims

AutomotiveUI '13: Proceedings of the 5th International Conference on Automotive User Interfaces and Interactive Vehicular Applications

Pages 242 - 245

https://doi.org/10.1145/2516540.2516570

Published: 28 October 2013 Publication History

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Abstract

We explore the feasibility of using pupil diameter to estimate how the cognitive load of the driver changes during a spoken dialogue task with a remote conversant. The conversants play a series of Taboo games, which do not follow a structured turn-taking nor initiative protocol. We contrast the driver's pupil diameter when the remote conversant begins speaking with the diameter right before the driver responds. Although we find a significant difference in pupil diameter for the first pair in each game, subsequent pairs show little difference. We speculate that this is due to the less structured nature of the task, where there are no set time boundaries on when the conversants work on the task. This suggests that spoken dialogue systems for in-car use might better manage the driver's cognitive load by using a more structured interaction, such as system-initiative dialogues.

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Cited By

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Appel TLeifheit L(2024)Fluid Intelligence and Mental Effort during Block Programming: What the Eyes Can Tell UsProceedings of the 2024 Symposium on Eye Tracking Research and Applications10.1145/3649902.3653944(1-6)Online publication date: 4-Jun-2024
https://dl.acm.org/doi/10.1145/3649902.3653944
Zheng HDu ZWang S(2024)Dynamic driving risk in highway tunnel groups based on pupillary oscillationsAccident Analysis & Prevention10.1016/j.aap.2023.107414195(107414)Online publication date: Feb-2024
https://doi.org/10.1016/j.aap.2023.107414
Kosch TKarolus JZagermann JReiterer HSchmidt AWoźniak P(2023)A Survey on Measuring Cognitive Workload in Human-Computer InteractionACM Computing Surveys10.1145/358227255:13s(1-39)Online publication date: 13-Jul-2023
https://dl.acm.org/doi/10.1145/3582272
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Index Terms

Estimating cognitive load using pupil diameter during a spoken dialogue task
1. Human-centered computing
  1. Human computer interaction (HCI)
    1. Interaction paradigms
      1. Natural language interfaces

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Published In

AutomotiveUI '13: Proceedings of the 5th International Conference on Automotive User Interfaces and Interactive Vehicular Applications

October 2013

281 pages

ISBN:9781450324786

DOI:10.1145/2516540

Conference Chair:
Jacques Terken
Eindhoven University of Technology, Eindhoven, The Netherlands
,
Program Chairs:
Marieke Martens
TNO / Universiteit Twente, Twente, The Netherlands
,
Christian Müller
DFKI, Saarbrücken, Germany
,
Jennifer Healey
INTEL Labs, Santa Clara, USA
,
Publications Chair:
Sebastian Osswald
Technische Universität München, TUM CREATE, Singapore

Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than the author(s) must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected].

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SIGCHI: ACM Special Interest Group on Computer-Human Interaction

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Association for Computing Machinery

New York, NY, United States

Publication History

Published: 28 October 2013

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U.S. Department of Justice

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AutomotiveUI '13

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Eindhoven University of Technology Department of Industrial Design

AutomotiveUI '13: Automotive User Interfaces and Interactive Vehicular Applications

October 28 - 30, 2013

Eindhoven, Netherlands

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AutomotiveUI '13 Paper Acceptance Rate 41 of 67 submissions, 61%;

Overall Acceptance Rate 248 of 566 submissions, 44%

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Appel TLeifheit L(2024)Fluid Intelligence and Mental Effort during Block Programming: What the Eyes Can Tell UsProceedings of the 2024 Symposium on Eye Tracking Research and Applications10.1145/3649902.3653944(1-6)Online publication date: 4-Jun-2024
https://dl.acm.org/doi/10.1145/3649902.3653944
Zheng HDu ZWang S(2024)Dynamic driving risk in highway tunnel groups based on pupillary oscillationsAccident Analysis & Prevention10.1016/j.aap.2023.107414195(107414)Online publication date: Feb-2024
https://doi.org/10.1016/j.aap.2023.107414
Kosch TKarolus JZagermann JReiterer HSchmidt AWoźniak P(2023)A Survey on Measuring Cognitive Workload in Human-Computer InteractionACM Computing Surveys10.1145/358227255:13s(1-39)Online publication date: 13-Jul-2023
https://dl.acm.org/doi/10.1145/3582272
Bacchin DGehrer NKrejtz KDuchowski AGamberini L(2023)Gaze-based Metrics of Cognitive Load in a Conjunctive Visual Memory TaskExtended Abstracts of the 2023 CHI Conference on Human Factors in Computing Systems10.1145/3544549.3585650(1-8)Online publication date: 19-Apr-2023
https://dl.acm.org/doi/10.1145/3544549.3585650
Wei WXue QYang XDu HWang YTang Q(2023)Assessing the Cognitive Load Arising from In-Vehicle Infotainment Systems Using Pupil DiameterCross-Cultural Design10.1007/978-3-031-35939-2_33(440-450)Online publication date: 9-Jul-2023
https://doi.org/10.1007/978-3-031-35939-2_33
Stampf AColley MRukzio E(2022)Towards Implicit Interaction in Highly Automated Vehicles - A Systematic Literature ReviewProceedings of the ACM on Human-Computer Interaction10.1145/35467266:MHCI(1-21)Online publication date: 20-Sep-2022
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Hirachan NMathews ARomero JRojas R(2022)Measuring Cognitive Workload Using Multimodal Sensors2022 44th Annual International Conference of the IEEE Engineering in Medicine & Biology Society (EMBC)10.1109/EMBC48229.2022.9871308(4921-4924)Online publication date: 11-Jul-2022
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Tement SMusil BPlohl NHorvat MStojmenova KSodnik J(2022)Assessment and Profiling of Driving Style and SkillsUser Experience Design in the Era of Automated Driving10.1007/978-3-030-77726-5_7(151-176)Online publication date: 1-Jan-2022
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Kun AMeulen HJanssen C(2019)Calling while driving using augmented realityPresence: Teleoperators and Virtual Environments10.1162/pres_a_0031627:1(1-14)Online publication date: 1-Mar-2019
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Ma JGu JJia HYao ZChang R(2018)The Relationship Between Drivers’ Cognitive Fatigue and Speed Variability During Monotonous Daytime DrivingFrontiers in Psychology10.3389/fpsyg.2018.004599Online publication date: 4-Apr-2018
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Recommendations

Spoken tasks for human-human experiments: towards in-car speech user interfaces for multi-threaded dialogue

Discourse Marker Use in Task-Oriented Spoken Dialog

Human-robot collaborative tutoring using multiparty multimodal spoken dialogue

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