Predicting Native Language from Gaze
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1704.07398.pdf
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Author(s)
Berzak, Yevgeni
Shikanai, Chie
Flynn, Suzanne
Katz, Boris
Date Issued
May 2017
Journal
Proceedings of the 55th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)
Publisher
Association for Computational Linguistics (ACL)
Citation
Berzak, Yevgeni, et al. "Predicting Native Language from Gaze." Proceedings of the 55th Annual Meeting of the Association for Computational Linguistics, Vancouver, Canada, 30 July - 4 August, 2017, Association for Computational Linguistics, 2017. pp. 541–51.
Version
Original manuscript
Abstract
A fundamental question in language learning concerns the role of a speaker’s first language in second language acquisition. We present a novel methodology for studying this question: analysis of eye-movement patterns in second language reading of free-form text. Using this methodology, we demonstrate for the first time that the native language of English learners can be predicted from their gaze fixations when reading English. We provide
analysis of classifier uncertainty and learned features, which indicates that differences in English reading are likely to be rooted in linguistic divergences across native languages. The presented framework complements production studies and offers new ground for advancing research on multilingualism.
MIT Department
Massachusetts Institute of Technology. Computer Science and Artificial Intelligence Laboratory
Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science
Massachusetts Institute of Technology. Department of Linguistics and Philosophy
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Creative Commons Attribution-Noncommercial-Share Alike
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DOI of Published Version
https://doi.org/10.18653/V1/P17-1050
