# Poem Meter Classification of Recited Arabic Poetry: Integrating High-Resource Systems for a Low-Resource Task

arXiv: https://arxiv.org/abs/2504.12172 · HTML: https://mlsanity.com/paper/2504.12172/

## Key facts

- No citing papers in the map yet (data through 14 Oct 2026).
- Builds on 17 of its 58 references that are in the map.
- First posted on arXiv 16 Apr 2025.

## Builds on (most cited first, 17 of 17)

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- [Learning meters of Arabic and English poems with Recurrent Neural Networks: a step forward for language understanding and synthesis](https://mlsanity.com/paper/1905.05700/) (2019)
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## Abstract (arXiv)

Arabic poetry is an essential and integral part of Arabic language and culture. It has been used by the Arabs to spot lights on their major events such as depicting brutal battles and conflicts. They also used it, as in many other languages, for various purposes such as romance, pride, lamentation, etc. Arabic poetry has received major attention from linguistics over the decades. One of the main characteristics of Arabic poetry is its special rhythmic structure as opposed to prose. This structure is referred to as a meter. Meters, along with other poetic characteristics, are intensively studied in an Arabic linguistic field called "textitAroud". Identifying these meters for a verse is a lengthy and complicated process. It also requires technical knowledge in textitAruod. For recited poetry, it adds an extra layer of processing. Developing systems for automatic identification of poem meters for recited poems need large amounts of labelled data. In this study, we propose a state-of-the-art framework to identify the poem meters of recited Arabic poetry, where we integrate two separate high-resource systems to perform the low-resource task. To ensure generalization of our proposed architecture, we publish a benchmark for this task for future research.