Abstract
Flashcard systems are effective tools for learning words but have their limitations in teaching word usage. To overcome this problem, we propose a novel flashcard system that shows a new example sentence on each repetition. This extension requires high-quality example sentences, automatically extracted from a huge corpus. To do this, we use a Determinantal Point Process which scales well to large data and allows to naturally represent sentence similarity and quality as features. Our human evaluation experiment on Japanese language indicates that the proposed method successfully extracted high-quality example sentences.- Anthology ID:
- W17-5014
- Volume:
- Proceedings of the 12th Workshop on Innovative Use of NLP for Building Educational Applications
- Month:
- September
- Year:
- 2017
- Address:
- Copenhagen, Denmark
- Editors:
- Joel Tetreault, Jill Burstein, Claudia Leacock, Helen Yannakoudakis
- Venue:
- BEA
- SIG:
- SIGEDU
- Publisher:
- Association for Computational Linguistics
- Note:
- Pages:
- 133–142
- Language:
- URL:
- https://aclanthology.org/W17-5014
- DOI:
- 10.18653/v1/W17-5014
- Cite (ACL):
- Arseny Tolmachev and Sadao Kurohashi. 2017. Automatic Extraction of High-Quality Example Sentences for Word Learning Using a Determinantal Point Process. In Proceedings of the 12th Workshop on Innovative Use of NLP for Building Educational Applications, pages 133–142, Copenhagen, Denmark. Association for Computational Linguistics.
- Cite (Informal):
- Automatic Extraction of High-Quality Example Sentences for Word Learning Using a Determinantal Point Process (Tolmachev & Kurohashi, BEA 2017)
- PDF:
- https://preview.aclanthology.org/nschneid-patch-2/W17-5014.pdf