Abstract
One core challenge facing morphological inflection systems is capturing language-specific morphophonological changes. This is particularly true of languages like Arabic which are morphologically complex. In this paper, we learn explicit morphophonological rules from morphologically annotated Egyptian Arabic and corresponding surface forms. These rules are human-interpretable, capture known morphophonological phenomena in the language, and are generalizable to unseen forms.- Anthology ID:
- 2022.wanlp-1.27
- Volume:
- Proceedings of the Seventh Arabic Natural Language Processing Workshop (WANLP)
- Month:
- December
- Year:
- 2022
- Address:
- Abu Dhabi, United Arab Emirates (Hybrid)
- Editors:
- Houda Bouamor, Hend Al-Khalifa, Kareem Darwish, Owen Rambow, Fethi Bougares, Ahmed Abdelali, Nadi Tomeh, Salam Khalifa, Wajdi Zaghouani
- Venue:
- WANLP
- SIG:
- Publisher:
- Association for Computational Linguistics
- Note:
- Pages:
- 295–301
- Language:
- URL:
- https://aclanthology.org/2022.wanlp-1.27
- DOI:
- 10.18653/v1/2022.wanlp-1.27
- Cite (ACL):
- Salam Khalifa, Jordan Kodner, and Owen Rambow. 2022. Towards Learning Arabic Morphophonology. In Proceedings of the Seventh Arabic Natural Language Processing Workshop (WANLP), pages 295–301, Abu Dhabi, United Arab Emirates (Hybrid). Association for Computational Linguistics.
- Cite (Informal):
- Towards Learning Arabic Morphophonology (Khalifa et al., WANLP 2022)
- PDF:
- https://preview.aclanthology.org/nschneid-patch-4/2022.wanlp-1.27.pdf