Controlling Grammatical Error Correction Using Word Edit Rate

Kengo Hotate, Masahiro Kaneko, Satoru Katsumata, Mamoru Komachi


Abstract
When professional English teachers correct grammatically erroneous sentences written by English learners, they use various methods. The correction method depends on how much corrections a learner requires. In this paper, we propose a method for neural grammar error correction (GEC) that can control the degree of correction. We show that it is possible to actually control the degree of GEC by using new training data annotated with word edit rate. Thereby, diverse corrected sentences is obtained from a single erroneous sentence. Moreover, compared to a GEC model that does not use information on the degree of correction, the proposed method improves correction accuracy.
Anthology ID:
P19-2020
Volume:
Proceedings of the 57th Annual Meeting of the Association for Computational Linguistics: Student Research Workshop
Month:
July
Year:
2019
Address:
Florence, Italy
Venue:
ACL
SIG:
Publisher:
Association for Computational Linguistics
Note:
Pages:
149–154
Language:
URL:
https://www.aclweb.org/anthology/P19-2020
DOI:
10.18653/v1/P19-2020
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PDF:
http://aclanthology.lst.uni-saarland.de/P19-2020.pdf