@inproceedings{tsai-etal-2020-lingglewrite,
title = "{L}inggle{W}rite: a Coaching System for Essay Writing",
author = "Tsai, Chung-Ting and
Chen, Jhih-Jie and
Yang, Ching-Yu and
Chang, Jason S.",
editor = "Celikyilmaz, Asli and
Wen, Tsung-Hsien",
booktitle = "Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics: System Demonstrations",
month = jul,
year = "2020",
address = "Online",
publisher = "Association for Computational Linguistics",
url = "https://aclanthology.org/2020.acl-demos.17",
doi = "10.18653/v1/2020.acl-demos.17",
pages = "127--133",
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.",
}
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<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.</abstract>
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%0 Conference Proceedings
%T LinggleWrite: a Coaching System for Essay Writing
%A Tsai, Chung-Ting
%A Chen, Jhih-Jie
%A Yang, Ching-Yu
%A Chang, Jason S.
%Y Celikyilmaz, Asli
%Y Wen, Tsung-Hsien
%S Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics: System Demonstrations
%D 2020
%8 July
%I Association for Computational Linguistics
%C Online
%F tsai-etal-2020-lingglewrite
%X 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.
%R 10.18653/v1/2020.acl-demos.17
%U https://aclanthology.org/2020.acl-demos.17
%U https://doi.org/10.18653/v1/2020.acl-demos.17
%P 127-133
Markdown (Informal)
[LinggleWrite: a Coaching System for Essay Writing](https://aclanthology.org/2020.acl-demos.17) (Tsai et al., ACL 2020)
ACL
- Chung-Ting Tsai, Jhih-Jie Chen, Ching-Yu Yang, and Jason S. Chang. 2020. LinggleWrite: a Coaching System for Essay Writing. In Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics: System Demonstrations, pages 127–133, Online. Association for Computational Linguistics.