@inproceedings{khalifa-etal-2022-towards,
title = "Towards Learning {A}rabic Morphophonology",
author = "Khalifa, Salam and
Kodner, Jordan and
Rambow, Owen",
editor = "Bouamor, Houda and
Al-Khalifa, Hend and
Darwish, Kareem and
Rambow, Owen and
Bougares, Fethi and
Abdelali, Ahmed and
Tomeh, Nadi and
Khalifa, Salam and
Zaghouani, Wajdi",
booktitle = "Proceedings of the Seventh Arabic Natural Language Processing Workshop (WANLP)",
month = dec,
year = "2022",
address = "Abu Dhabi, United Arab Emirates (Hybrid)",
publisher = "Association for Computational Linguistics",
url = "https://aclanthology.org/2022.wanlp-1.27",
doi = "10.18653/v1/2022.wanlp-1.27",
pages = "295--301",
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.",
}
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<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.</abstract>
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%0 Conference Proceedings
%T Towards Learning Arabic Morphophonology
%A Khalifa, Salam
%A Kodner, Jordan
%A Rambow, Owen
%Y Bouamor, Houda
%Y Al-Khalifa, Hend
%Y Darwish, Kareem
%Y Rambow, Owen
%Y Bougares, Fethi
%Y Abdelali, Ahmed
%Y Tomeh, Nadi
%Y Khalifa, Salam
%Y Zaghouani, Wajdi
%S Proceedings of the Seventh Arabic Natural Language Processing Workshop (WANLP)
%D 2022
%8 December
%I Association for Computational Linguistics
%C Abu Dhabi, United Arab Emirates (Hybrid)
%F khalifa-etal-2022-towards
%X 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.
%R 10.18653/v1/2022.wanlp-1.27
%U https://aclanthology.org/2022.wanlp-1.27
%U https://doi.org/10.18653/v1/2022.wanlp-1.27
%P 295-301
Markdown (Informal)
[Towards Learning Arabic Morphophonology](https://aclanthology.org/2022.wanlp-1.27) (Khalifa et al., WANLP 2022)
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.