Grammatical-Error-Aware Incorrect Example Retrieval System for Learners of Japanese as a Second Language

Mio Arai, Masahiro Kaneko, Mamoru Komachi


Abstract
Existing example retrieval systems do not include grammatically incorrect examples or present only a few examples, if any. Even if a retrieval system has a wide coverage of incorrect examples along with the correct counterpart, learners need to know whether their query includes errors or not. Considering the usability of retrieving incorrect examples, our proposed method uses a large-scale corpus and presents correct expressions along with incorrect expressions using a grammatical error detection system so that the learner do not need to be aware of how to search for the examples. Intrinsic and extrinsic evaluations indicate that our method improves accuracy of example sentence retrieval and quality of learner’s writing.
Anthology ID:
W19-4431
Volume:
Proceedings of the Fourteenth Workshop on Innovative Use of NLP for Building Educational Applications
Month:
August
Year:
2019
Address:
Florence, Italy
Venues:
ACL | BEA | WS
SIG:
SIGEDU
Publisher:
Association for Computational Linguistics
Note:
Pages:
296–305
Language:
URL:
https://aclanthology.org/W19-4431
DOI:
10.18653/v1/W19-4431
Bibkey:
Cite (ACL):
Mio Arai, Masahiro Kaneko, and Mamoru Komachi. 2019. Grammatical-Error-Aware Incorrect Example Retrieval System for Learners of Japanese as a Second Language. In Proceedings of the Fourteenth Workshop on Innovative Use of NLP for Building Educational Applications, pages 296–305, Florence, Italy. Association for Computational Linguistics.
Cite (Informal):
Grammatical-Error-Aware Incorrect Example Retrieval System for Learners of Japanese as a Second Language (Arai et al., 2019)
Copy Citation:
PDF:
https://aclanthology.org/W19-4431.pdf