LinggleWrite: a Coaching System for Essay Writing

Chung-Ting Tsai, Jhih-Jie Chen, Ching-Yu Yang, Jason S. Chang


Abstract
This paper presents LinggleWrite, a writing coach that provides writing suggestions, assesses writing proficiency levels, detects grammatical errors, and offers corrective feedback in response to user’s essay. The method involves extracting grammar patterns, training models for automated essay scoring (AES) and grammatical error detection (GED), and finally retrieving plausible corrections from a n-gram search engine. Experiments on public test sets indicate that both AES and GED models achieve state-of-the-art performance. These results show that LinggleWrite is potentially useful in helping learners improve their writing skills.
Anthology ID:
2020.acl-demos.17
Volume:
Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics: System Demonstrations
Month:
July
Year:
2020
Address:
Online
Venue:
ACL
SIG:
Publisher:
Association for Computational Linguistics
Note:
Pages:
127–133
Language:
URL:
https://www.aclweb.org/anthology/2020.acl-demos.17
DOI:
10.18653/v1/2020.acl-demos.17
Bib Export formats:
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PDF:
http://aclanthology.lst.uni-saarland.de/2020.acl-demos.17.pdf
Video:
 http://slideslive.com/38928625