@inproceedings{berzak-etal-2017-predicting,
title = "Predicting Native Language from Gaze",
author = "Berzak, Yevgeni and
Nakamura, Chie and
Flynn, Suzanne and
Katz, Boris",
editor = "Barzilay, Regina and
Kan, Min-Yen",
booktitle = "Proceedings of the 55th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)",
month = jul,
year = "2017",
address = "Vancouver, Canada",
publisher = "Association for Computational Linguistics",
url = "https://aclanthology.org/P17-1050",
doi = "10.18653/v1/P17-1050",
pages = "541--551",
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.",
}
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%0 Conference Proceedings
%T Predicting Native Language from Gaze
%A Berzak, Yevgeni
%A Nakamura, Chie
%A Flynn, Suzanne
%A Katz, Boris
%Y Barzilay, Regina
%Y Kan, Min-Yen
%S Proceedings of the 55th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)
%D 2017
%8 July
%I Association for Computational Linguistics
%C Vancouver, Canada
%F berzak-etal-2017-predicting
%X 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.
%R 10.18653/v1/P17-1050
%U https://aclanthology.org/P17-1050
%U https://doi.org/10.18653/v1/P17-1050
%P 541-551
Markdown (Informal)
[Predicting Native Language from Gaze](https://aclanthology.org/P17-1050) (Berzak et al., ACL 2017)
ACL
- Yevgeni Berzak, Chie Nakamura, Suzanne Flynn, and Boris Katz. 2017. Predicting Native Language from Gaze. In Proceedings of the 55th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), pages 541–551, Vancouver, Canada. Association for Computational Linguistics.