Plausibility and Well-formedness Acceptability Test on Deep Neural Nativeness Classification

Kwonsik Park, Sanghoun Song


Anthology ID:
2020.paclic-1.27
Volume:
Proceedings of the 34th Pacific Asia Conference on Language, Information and Computation
Month:
October
Year:
2020
Address:
Hanoi, Vietnam
Editors:
Minh Le Nguyen, Mai Chi Luong, Sanghoun Song
Venue:
PACLIC
SIG:
Publisher:
Association for Computational Linguistics
Note:
Pages:
234–242
Language:
URL:
https://aclanthology.org/2020.paclic-1.27
DOI:
Bibkey:
Cite (ACL):
Kwonsik Park and Sanghoun Song. 2020. Plausibility and Well-formedness Acceptability Test on Deep Neural Nativeness Classification. In Proceedings of the 34th Pacific Asia Conference on Language, Information and Computation, pages 234–242, Hanoi, Vietnam. Association for Computational Linguistics.
Cite (Informal):
Plausibility and Well-formedness Acceptability Test on Deep Neural Nativeness Classification (Park & Song, PACLIC 2020)
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PDF:
https://aclanthology.org/2020.paclic-1.27.pdf