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.
Cite
CITATION STYLE
ElOraby, M., Abdelgaber, M., Elkaref, N., & Abu-Elkheir, M. (2022). Generating Classical Arabic Poetry using Pre-trained Models. In WANLP 2022 - 7th Arabic Natural Language Processing - Proceedings of the Workshop (pp. 53–62). Association for Computational Linguistics (ACL). https://doi.org/10.18653/v1/2022.wanlp-1.6
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