Automatic Assistance for Academic Word Usage

Dariush Saberi, John Lee, Jonathan James Webster


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
Bibkey:
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)
Copy Citation:
PDF:
https://preview.aclanthology.org/auto-file-uploads/2020.coling-main.196.pdf