MetRec: A dataset for meter classification of arabic poetry

Maged S Al-Shaibani; Zaid Alyafeai; Irfan Ahmad

doi:10.1016/j.dib.2020.106497

MetRec: A dataset for meter classification of arabic poetry

Data Brief. 2020 Nov 4:33:106497. doi: 10.1016/j.dib.2020.106497. eCollection 2020 Dec.

Authors

Maged S Al-Shaibani¹, Zaid Alyafeai¹, Irfan Ahmad¹

Affiliation

¹ Information and Computer Science Department, KFUPM, Dhahran 31261, Saudi Arabia.

Abstract

In this data article, we report a dataset related to the research titled "Meter Classification of Arabic Poems Using Deep Bidirectional Recurrent Neural Networks"[2]. The dataset was collected from a large repository of Arabic poems, Aldiwan website [1]. The data collection was done using a Python script that scrapes the website to find the poems and their associated meters. The dataset contains the verses and their corresponding meter classes. Meter classes are represented as numbers from 0 to 13. The dataset can be highly useful for further research in order to improve the field of Arabic poems' meter classification.

Keywords: Arabic; classification; meter; poetry; prosody.