@inproceedings{elkaref-etal-2022-generating,
title = "Generating Classical {A}rabic Poetry using Pre-trained Models",
author = "Elkaref, Nehal and
Abu-Elkheir, Mervat and
ElOraby, Maryam and
Abdelgaber, Mohamed",
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-1.6",
doi = "10.18653/v1/2022.wanlp-1.6",
pages = "53--62",
abstract = "Poetry generation tends to be a complicated task given meter and rhyme constraints. Previous work resorted to exhaustive methods in-order to employ poetic elements. In this paper we leave pre-trained models, GPT-J and BERTShared to recognize patterns of meters and rhyme to generate classical Arabic poetry and present our findings and results on how well both models could pick up on these classical Arabic poetic elements.",
}
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<abstract>Poetry generation tends to be a complicated task given meter and rhyme constraints. Previous work resorted to exhaustive methods in-order to employ poetic elements. In this paper we leave pre-trained models, GPT-J and BERTShared to recognize patterns of meters and rhyme to generate classical Arabic poetry and present our findings and results on how well both models could pick up on these classical Arabic poetic elements.</abstract>
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%0 Conference Proceedings
%T Generating Classical Arabic Poetry using Pre-trained Models
%A Elkaref, Nehal
%A Abu-Elkheir, Mervat
%A ElOraby, Maryam
%A Abdelgaber, Mohamed
%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 elkaref-etal-2022-generating
%X Poetry generation tends to be a complicated task given meter and rhyme constraints. Previous work resorted to exhaustive methods in-order to employ poetic elements. In this paper we leave pre-trained models, GPT-J and BERTShared to recognize patterns of meters and rhyme to generate classical Arabic poetry and present our findings and results on how well both models could pick up on these classical Arabic poetic elements.
%R 10.18653/v1/2022.wanlp-1.6
%U https://aclanthology.org/2022.wanlp-1.6
%U https://doi.org/10.18653/v1/2022.wanlp-1.6
%P 53-62
Markdown (Informal)
[Generating Classical Arabic Poetry using Pre-trained Models](https://aclanthology.org/2022.wanlp-1.6) (Elkaref et al., WANLP 2022)
ACL
- Nehal Elkaref, Mervat Abu-Elkheir, Maryam ElOraby, and Mohamed Abdelgaber. 2022. Generating Classical Arabic Poetry using Pre-trained Models. In Proceedings of the Seventh Arabic Natural Language Processing Workshop (WANLP), pages 53–62, Abu Dhabi, United Arab Emirates (Hybrid). Association for Computational Linguistics.