Langsmith: An Interactive Academic Text Revision System

Takumi Ito, Tatsuki Kuribayashi, Masatoshi Hidaka, Jun Suzuki, Kentaro Inui


Abstract
Despite the current diversity and inclusion initiatives in the academic community, researchers with a non-native command of English still face significant obstacles when writing papers in English. This paper presents the Langsmith editor, which assists inexperienced, non-native researchers to write English papers, especially in the natural language processing (NLP) field. Our system can suggest fluent, academic-style sentences to writers based on their rough, incomplete phrases or sentences. The system also encourages interaction between human writers and the computerized revision system. The experimental results demonstrated that Langsmith helps non-native English-speaker students write papers in English. The system is available at https://emnlp-demo.editor.langsmith.co.jp/.
Anthology ID:
2020.emnlp-demos.28
Original:
2020.emnlp-demos.28v1
Version 2:
2020.emnlp-demos.28v2
Volume:
Proceedings of the 2020 Conference on Empirical Methods in Natural Language Processing: System Demonstrations
Month:
October
Year:
2020
Address:
Online
Editors:
Qun Liu, David Schlangen
Venue:
EMNLP
SIG:
Publisher:
Association for Computational Linguistics
Note:
Pages:
216–226
Language:
URL:
https://aclanthology.org/2020.emnlp-demos.28
DOI:
10.18653/v1/2020.emnlp-demos.28
Bibkey:
Cite (ACL):
Takumi Ito, Tatsuki Kuribayashi, Masatoshi Hidaka, Jun Suzuki, and Kentaro Inui. 2020. Langsmith: An Interactive Academic Text Revision System. In Proceedings of the 2020 Conference on Empirical Methods in Natural Language Processing: System Demonstrations, pages 216–226, Online. Association for Computational Linguistics.
Cite (Informal):
Langsmith: An Interactive Academic Text Revision System (Ito et al., EMNLP 2020)
Copy Citation:
PDF:
https://aclanthology.org/2020.emnlp-demos.28.pdf