Arabic Word-level Readability Visualization for Assisted Text Simplification

Reem Hazim, Hind Saddiki, Bashar Alhafni, Muhamed Al Khalil, Nizar Habash


Abstract
This demo paper presents a Google Docs add-on for automatic Arabic word-level readability visualization. The add-on includes a lemmatization component that is connected to a five-level readability lexicon and Arabic WordNet-based substitution suggestions. The add-on can be used for assessing the reading difficulty of a text and identifying difficult words as part of the task of manual text simplification. We make our add-on and its code publicly available.
Anthology ID:
2022.emnlp-demos.24
Volume:
Proceedings of the 2022 Conference on Empirical Methods in Natural Language Processing: System Demonstrations
Month:
December
Year:
2022
Address:
Abu Dhabi, UAE
Editors:
Wanxiang Che, Ekaterina Shutova
Venue:
EMNLP
SIG:
Publisher:
Association for Computational Linguistics
Note:
Pages:
242–249
Language:
URL:
https://aclanthology.org/2022.emnlp-demos.24
DOI:
10.18653/v1/2022.emnlp-demos.24
Bibkey:
Cite (ACL):
Reem Hazim, Hind Saddiki, Bashar Alhafni, Muhamed Al Khalil, and Nizar Habash. 2022. Arabic Word-level Readability Visualization for Assisted Text Simplification. In Proceedings of the 2022 Conference on Empirical Methods in Natural Language Processing: System Demonstrations, pages 242–249, Abu Dhabi, UAE. Association for Computational Linguistics.
Cite (Informal):
Arabic Word-level Readability Visualization for Assisted Text Simplification (Hazim et al., EMNLP 2022)
Copy Citation:
PDF:
https://aclanthology.org/2022.emnlp-demos.24.pdf