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
- Editors:
- Helen Yannakoudakis, Ekaterina Kochmar, Claudia Leacock, Nitin Madnani, Ildikó Pilán, Torsten Zesch
- Venue:
- BEA
- SIG:
- SIGEDU
- Publisher:
- Association for Computational Linguistics
- Note:
- Pages:
- 296–305
- Language:
- URL:
- https://aclanthology.org/W19-4431
- DOI:
- 10.18653/v1/W19-4431
- 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., BEA 2019)
- PDF:
- https://preview.aclanthology.org/emnlp-22-attachments/W19-4431.pdf