Tarab: A Multi-Dialect Corpus of Arabic Lyrics and Poetry

2026-03-17

AI Summary

This study addresses the lack of comprehensive Arabic creative text corpora that integrate multiple dialects and span diverse historical periods, a gap that has hindered linguistic and cultural research. To bridge this, the authors present the largest open-source corpus of Arabic creative texts to date, comprising 2.56 million poetic lines and over 13.5 million tokens. For the first time, it unifies Classical Arabic, Modern Standard Arabic, and six major regional dialects across a temporal span exceeding fourteen centuries. The corpus is enriched with structured metadata on linguistic variety, geographic origin, and historical-cultural context. Developed through systematic collection, standardization, and validation procedures, this resource supports foundational tasks such as language variety identification and genre classification. It has been publicly released on Hugging Face, offering a critical infrastructure for research in linguistics, literature, and artificial intelligence.

Technology Category

• Natural Language Processing: Sentiment Analysis, Stylistic Analysis, and Argument Mining
• Machine Learning: Large Multimodal Models (LMMs)
• Cognitive Modeling & Cognitive Systems: Computational Creativity

Application Category

• Search and Retrieval-Augmented AI: Multilingual and cross-lingual Web search
• Web Mining and Content Analysis: Large pretrained models with web data
• Semantics and Knowledge: Scalable techniques for the creation, curation, publication, maintenance, and consumption of large, Web-based, structured, reusable, knowledge graphs and ontologies

Abstract

We introduce the Tarab Corpus, a large-scale cultural and linguistic resource that brings together Arabic song lyrics and poetry within a unified analytical framework. The corpus comprises 2.56 million verses and more than 13.5 million tokens, making it, to our knowledge, the largest open Arabic corpus of creative text spanning both classical and contemporary production. Tarab is broadly balanced between songs and poems and covers Classical Arabic, Modern Standard Arabic (MSA), and six major regional varieties: Egyptian, Gulf, Levantine, Iraqi, Sudanese, and Maghrebi Arabic. The artists and poets represented in the corpus are associated with 28 modern nation states and multiple historical eras, covering over fourteen centuries of Arabic creative expression from the Pre-Islamic period to the twenty-first century. Each verse is accompanied by structured metadata describing linguistic variety, geographic origin, and historical or cultural context, enabling comparative linguistic, stylistic, and diachronic analysis across genres and time. We describe the data collection, normalisation, and validation pipeline and present baseline analyses for variety identification and genre differentiation. The dataset is publicly available on HuggingFace at https://huggingface.co/datasets/drelhaj/Tarab.

Problem

• Arabic lyrics
• Arabic poetry
• multi-dialect corpus
• linguistic variety
• diachronic analysis

Innovation

• multi-dialect corpus
• Arabic lyrics and poetry
• structured metadata
• diachronic analysis
• linguistic variety identification