用高资源系统融合方法，解决阿拉伯语朗诵诗歌的韵律分类难题
Poem Meter Classification of Recited Arabic Poetry: Integrating High-Resource Systems for a Low-Resource Task
- 融合两个高资源系统处理低资源诗歌韵律识别任务
- 提出新框架，在公开数据集上实现当前最佳性能
- 发布首个基准数据集，助力后续研究
阿拉伯诗歌是阿拉伯语言与文化的核心组成部分，常用于记录重大事件如战争冲突，也用于表达爱情、自豪、哀悼等情感。其核心特征之一是独特的韵律结构，即“韵律”（meter），在阿拉伯语言学中称为“阿鲁德”（Arouod）。准确识别诗句韵律需深厚的专业知识且过程复杂。针对朗诵诗歌，该任务更具挑战性。以往方法依赖大量标注数据，但此类数据稀缺。本文提出一种先进框架，通过整合两个高资源系统来完成低资源下的诗歌韵律自动识别任务。为保证模型泛化能力，研究团队发布了首个面向该任务的基准数据集，以推动后续研究发展。
原文摘要 · Abstract (English)
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 "\textit{Aroud}". Identifying these meters for a verse is a lengthy and complicated process. It also requires technical knowledge in \textit{Aruod}. 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.
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