Tadabur: A Large-Scale Quran Audio Dataset
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Abstract (arXiv)
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.
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References · 7
- 2023DINOv2: Learning Robust Visual Features without Supervisioncited by 7,974
- 2022Robust Speech Recognition via Large-Scale Weak Supervisioncited by 4,057
- 2023Scaling Speech Technology to 1,000+ Languagescited by 411
- 2023WhisperX: Time-Accurate Speech Transcription of Long-Form Audiocited by 326
- 2026Qwen3-ASR Technical Reportcited by 118
- 2024EAT: Self-Supervised Pre-Training with Efficient Audio Transformercited by 53
- 2025Automatic Pronunciation Error Detection and Correction of the Holy Quran's Learners Using Deep Learningcited by 1
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