research-article

Towards Using Gaze Properties to Detect Language Proficiency

Authors:

Paweł W. Woźniak,

Lewis L. ChuangAuthors Info & Claims

NordiCHI '16: Proceedings of the 9th Nordic Conference on Human-Computer Interaction

Article No.: 118, Pages 1 - 6

https://doi.org/10.1145/2971485.2996753

Published: 23 October 2016 Publication History

Abstract

Humans are inherently skilled at using subtle physiological cues from other persons, for example gaze direction in a conversation. Personal computers have yet to explore this implicit input modality. In a study with 14 participants, we investigate how a user's gaze can be leveraged in adaptive computer systems. In particular, we examine the impact of different languages on eye movements by presenting simple questions in multiple languages to our participants. We found that fixation duration is sufficient to ascertain if a user is highly proficient in a given language. We propose how these findings could be used to implement adaptive visualizations that react implicitly on the user's gaze.

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Cited By

Orlosky JHuynh BHollerer T(2019)Using Eye Tracked Virtual Reality to Classify Understanding of Vocabulary in Recall Tasks2019 IEEE International Conference on Artificial Intelligence and Virtual Reality (AIVR)10.1109/AIVR46125.2019.00019(66-667)Online publication date: Dec-2019
https://doi.org/10.1109/AIVR46125.2019.00019

Index Terms

Towards Using Gaze Properties to Detect Language Proficiency
1. Computing methodologies
  1. Artificial intelligence
    1. Philosophical/theoretical foundations of artificial intelligence
      1. Cognitive science
2. Human-centered computing
  1. Human computer interaction (HCI)

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cover image ACM Other conferences

NordiCHI '16: Proceedings of the 9th Nordic Conference on Human-Computer Interaction

October 2016

1045 pages

ISBN:9781450347631

DOI:10.1145/2971485

General Chairs:
Staffan Björk
University of Gothenburg
,
Eva Eriksson
Chalmers University of Technology
,
Program Chairs:
Morten Fjeld
Chalmers University of Technology
,
Susanne Bødker
University of Aarhus
,
Publications Chairs:
Wolmet Barendregt
University of Gothenburg
,
Mohammad Obaid
Chalmers University of Technology

Copyright © 2016 ACM.

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Chalmers University of Technology
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: 23 October 2016

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NordiCHI '16

NordiCHI '16: 9th Nordic Conference on Human-Computer Interaction

October 23 - 27, 2016

Gothenburg, Sweden

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NordiCHI '16 Paper Acceptance Rate 58 of 231 submissions, 25%;

Overall Acceptance Rate 379 of 1,572 submissions, 24%

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Cited By

Orlosky JHuynh BHollerer T(2019)Using Eye Tracked Virtual Reality to Classify Understanding of Vocabulary in Recall Tasks2019 IEEE International Conference on Artificial Intelligence and Virtual Reality (AIVR)10.1109/AIVR46125.2019.00019(66-667)Online publication date: Dec-2019
https://doi.org/10.1109/AIVR46125.2019.00019

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