no code implementations • 3 Jul 2024 • Juan Piñeros Liberato, Bashar Alhafni, Muhamed Al Khalil, Nizar Habash
Automatic readability assessment is relevant to building NLP applications for education, content analysis, and accessibility.
no code implementations • 29 Apr 2024 • Bashar Alhafni, Reem Hazim, Juan Piñeros Liberato, Muhamed Al Khalil, Nizar Habash
We present the SAMER Corpus, the first manually annotated Arabic parallel corpus for text simplification targeting school-aged learners.
no code implementations • 19 Oct 2022 • Reem Hazim, Hind Saddiki, Bashar Alhafni, Muhamed Al Khalil, Nizar Habash
This demo paper presents a Google Docs add-on for automatic Arabic word-level readability visualization.
no code implementations • COLING 2020 • Zhengyang Jiang, Nizar Habash, Muhamed Al Khalil
This demo paper introduces the online Readability Leveled Arabic Thesaurus interface.
no code implementations • LREC 2020 • Muhamed Al Khalil, Nizar Habash, Zhengyang Jiang
We present a large-scale 26, 000-lemma leveled readability lexicon for Modern Standard Arabic.
no code implementations • WS 2018 • Hind Saddiki, Nizar Habash, Violetta Cavalli-Sforza, Muhamed Al Khalil
Advances in automatic readability assessment can impact the way people consume information in a number of domains.