Abstract
This paper describes a writing assistance system that helps students improve their academic writing. Given an input text, the system suggests lexical substitutions that aim to incorporate more academic vocabulary. The substitution candidates are drawn from an academic word list and ranked by a masked language model. Experimental results show that lexical formality analysis can improve the quality of the suggestions, in comparison to a baseline that relies on the masked language model only.- Anthology ID:
- 2020.coling-main.196
- Volume:
- Proceedings of the 28th International Conference on Computational Linguistics
- Month:
- December
- Year:
- 2020
- Address:
- Barcelona, Spain (Online)
- Venue:
- COLING
- SIG:
- Publisher:
- International Committee on Computational Linguistics
- Note:
- Pages:
- 2163–2168
- Language:
- URL:
- https://aclanthology.org/2020.coling-main.196
- DOI:
- 10.18653/v1/2020.coling-main.196
- Cite (ACL):
- Dariush Saberi, John Lee, and Jonathan James Webster. 2020. Automatic Assistance for Academic Word Usage. In Proceedings of the 28th International Conference on Computational Linguistics, pages 2163–2168, Barcelona, Spain (Online). International Committee on Computational Linguistics.
- Cite (Informal):
- Automatic Assistance for Academic Word Usage (Saberi et al., COLING 2020)
- PDF:
- https://preview.aclanthology.org/nodalida-main-page/2020.coling-main.196.pdf