Tahdib: A Rhythm-Aware Phrase Insertion for Classical Arabic Poetry Composition
Mohamad Elzohbi, Richard Zhao · 2025
This paper presents a methodology for inserting phrases in Arabic poems to conform to a specific rhythm using ByT5, a byte-level multilingual transformer-based model.Our work discusses a rule-based grapheme-to-beat transformation tailored for extracting the rhythm from fully diacritized Arabic script.Our approach employs a conditional denoising objective to fine-tune ByT5, where the model reconstructs masked words to match a target rhythm.We adopt a curriculum learning strategy, pre-training on a general Arabic dataset before fine-tuning on poetic dataset, and explore cross-lingual transfer from English to Arabic.Experimental results demonstrate that our models achieve high rhythmic alignment while maintaining semantic coherence.The proposed model has the potential to be used in co-creative applications in the process of composing classical Arabic poems.