Sakura: Large-scale Incorrect Example Retrieval System for Learners of Japanese as a Second Language

Mio Arai, Tomonori Kodaira, Mamoru Komachi


Abstract
This study develops an incorrect example retrieval system, called Sakura, using a large-scale Lang-8 dataset for Japanese language learners. Existing example retrieval systems do not include grammatically incorrect examples or present only a few examples, if any. If a retrieval system has a wide coverage of incorrect examples along with the correct counterpart, learners can revise their composition themselves. Considering the usability of retrieving incorrect examples, our proposed system uses a large-scale corpus to expand the coverage of incorrect examples and presents correct expressions along with incorrect expressions. Our intrinsic and extrinsic evaluations indicate that our system is more useful than a previous system.
Anthology ID:
P19-3001
Volume:
Proceedings of the 57th Annual Meeting of the Association for Computational Linguistics: System Demonstrations
Month:
July
Year:
2019
Address:
Florence, Italy
Editors:
Marta R. Costa-jussà, Enrique Alfonseca
Venue:
ACL
SIG:
Publisher:
Association for Computational Linguistics
Note:
Pages:
1–6
Language:
URL:
https://aclanthology.org/P19-3001
DOI:
10.18653/v1/P19-3001
Bibkey:
Cite (ACL):
Mio Arai, Tomonori Kodaira, and Mamoru Komachi. 2019. Sakura: Large-scale Incorrect Example Retrieval System for Learners of Japanese as a Second Language. In Proceedings of the 57th Annual Meeting of the Association for Computational Linguistics: System Demonstrations, pages 1–6, Florence, Italy. Association for Computational Linguistics.
Cite (Informal):
Sakura: Large-scale Incorrect Example Retrieval System for Learners of Japanese as a Second Language (Arai et al., ACL 2019)
Copy Citation:
PDF:
https://aclanthology.org/P19-3001.pdf