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Main Author: Alherran, Faisal
Format: Preprint
Published: 2026
Subjects:
Online Access:https://arxiv.org/abs/2604.18932
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author Alherran, Faisal
author_facet Alherran, Faisal
contents 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.
format Preprint
id arxiv_https___arxiv_org_abs_2604_18932
institution arXiv
publishDate 2026
record_format arxiv
spellingShingle Tadabur: A Large-Scale Quran Audio Dataset
Alherran, Faisal
Sound
Artificial Intelligence
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.
title Tadabur: A Large-Scale Quran Audio Dataset
topic Sound
Artificial Intelligence
url https://arxiv.org/abs/2604.18932