Tadabur: A Large-Scale Quran Audio Dataset

arXiv cs.AI / 4/22/2026

💬 OpinionModels & Research

Key Points

  • The paper introduces Tadabur, a large-scale Quran audio dataset designed to overcome limitations of existing Quran datasets in both size and diversity.
  • Tadabur includes 1,400+ hours of recitation audio recorded from 600+ distinct reciters, capturing wide variation in recitation styles, vocal traits, and recording conditions.
  • The dataset is intended to provide a more comprehensive and representative resource for research and analysis of Quranic speech.
  • By expanding both dataset duration and variability, Tadabur aims to enable future studies and support the creation of standardized Quranic speech benchmarks.

Abstract

Despite growing interest in Quranic data research, existing Quran datasets remain limited in both scale and diversity. To address this gap, we present Tadabur, a large-scale Quran audio dataset. Tadabur comprises more than 1400+ hours of recitation audio from over 600 distinct reciters, providing substantial variation in recitation styles, vocal characteristics, and recording conditions. This diversity makes Tadabur a comprehensive and representative resource for Quranic speech research and analysis. By significantly expanding both the total duration and variability of available Quran data, Tadabur aims to support future research and facilitate the development of standardized Quranic speech benchmarks.