Tadabur: A Large-Scale Quran Audio Dataset

The most comprehensive and richly annotated Qur'anic recitation corpus to date

_{The full dataset release is in progress and will be uploaded soon—apologies for the delay.}

Faisal Alherran

     

---

✦ Overview

Tadabur is a large-scale, high-diversity Qur'anic speech dataset designed to advance research in Qur'anic Automatic Speech Recognition (ASR), reciter modeling, tajwīd-aware speech processing, and prosodic analysis. It is the most comprehensive publicly available collection of Qur'anic recitation audio to date.

---

📊 Dataset at a Glance

Property	Value
🕐 Total Audio Duration	1400+ hours
🎙️ Distinct Reciters	600+
🔗 Alignment	Verse-level + word-level timestamps
⚖️ License	CC BY-NC 4.0

---

🧭 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 comprising more than 1400 hours of recitation audio from over 600 distinct reciters, providing substantial variation in recitation styles, vocal characteristics, and recording conditions.

Tadabur includes complete coverage of all Qur'an, spanning styles such as murattal and mujawwad. Each file is accompanied by automatically derived word-level temporal alignments and structured metadata in a consistent JSON schema.

This diversity makes Tadabur a comprehensive and representative resource for Quranic speech research — enabling advances in ASR, tajwīd-aware modeling, reciter identification, and prosodic analysis.

---

📈 Comparison with Prior Datasets

Dataset	Samples	Reciters	Transcription	Word-Level Alignment
Quran Recitations (Kaggle)	6,689	12	✗	✗
Quran Speech-to-Text (SLR132)	226,129	30	✓	✗
Buraaq Quran Audio–Text	187,080	30	✓	✗
Tadabur (Ours)	365,000+	600+	✓	✓

Tadabur surpasses all prior publicly available Quranic datasets by a wide margin in scale, reciter diversity, and annotation richness.

---

🔄 Dataset Pipeline

A fully automated, multi-stage process transforms raw long-form recitations into clean, verse-level annotated audio files:

🌐 Collection  →  🤖 LLM Metadata  →  🎙️ WhisperX Align  →  ✂️ Boundary Detect  →  🧹 Curation
  Public repos      Surah & reciter      Word-level             Recitation-stop        ASR filtering &
  & archives        extraction via LLM   timestamps & AAM       segmenter              deduplication

---

🧩 Dataset Structure

Each example in the dataset consists of two components:

1. Audio file — a single Qur'anic verse (.wav)
2. Metadata file (JSON) — verse, reciter, and word alignment info

JSON Schema

{
  "reciter_id": 88,
  "surah_id": 3,
  "ayah_id": 82,
  "word_alignments": [
    {
      "word": "أَفَلَا",
      "start": 0.00,
      "end": 0.62
    },
    ...
  ],
  "text_ar_simple": "افلا يتدبرون القران ولو كان من عند غير الله لوجدوا فيه اختلافا كثيرا",
  "text_ar_uthmani": "أَفَلَا يَتَدَبَّرُونَ ٱلْقُرْءَانَ ۚ وَلَوْ كَانَ مِنْ عِندِ غَيْرِ ٱللَّهِ لَوَجَدُوا۟ فِيهِ ٱخْتِلَـٰفًا كَثِيرًا",
  "ayah_duration_s": 10.9,
  "audio_filename": "tadabur_spk0088_S3_A82_db1f8e71_000003.wav"
}

File Naming Convention

tadabur_spk{reciter_id:04d}_S{surah_id}_A{ayah_id}_{hash}_{segment:06d}.wav

---

🎯 Supported Tasks

Task	Description
🗣️ Automatic Speech Recognition (ASR)	Verse-level transcription of Qur'anic audio
👤 Reciter Identification	Speaker classification across 600 reciters
📊 Model Evaluation	Benchmarking ASR models on Qur'anic speech using WER

---

🤖 Fine-Tuned Whisper Models

Alongside the dataset, we release Whisper models fine-tuned on Tadabur for Qur'anic ASR. These models are domain-adapted to handle prolonged phoneme durations, tajwīd rules, melodic articulation, and the wide acoustic diversity unique to Qur'anic recitation.

Model	Base	Status	Link
Tadabur-Whisper-Small	Whisper Small	✅ Available	🤗 HuggingFace

---

📝 Notes

• Some reciters may appear multiple times for the same surah and ayah. These repetitions intentionally capture natural variation in recitation, including differences in pace, melody, pronunciation, and recording conditions.
• Recitation styles include murattal (measured/standard), mujawwad (melodic/ornate), and others.
• Audio was collected from public Qur'anic repositories and archives, then processed through the automated pipeline described above.

---

⚖️ License

This dataset is released under the Creative Commons Attribution–NonCommercial 4.0 (CC BY-NC 4.0) license.

For research and educational purposes only. Attribution is required.

---

🕌 Ethical & Cultural Considerations

The Qur'an holds deep religious and cultural significance for over a billion people worldwide. Tadabur is intended solely for respectful and beneficial use, including:

• ✅ Academic research
• ✅ Education and literacy tools
• ✅ Development of assistive technologies

🚫 Users must not employ this dataset for:

• Mockery or distortion of Qur'anic recitation
• Disrespectful or misleading audio synthesis
• Any application that may cause offense to Muslim communities

---

📚 Citation

If you use Tadabur in your research, please cite:

@misc{alherran2026tadabur,
  author    = {Alherran, Faisal},
  title     = {Tadabur: A Large-Scale Quran Audio Dataset},
  year      = {2026},
  url       = {https://github.com/fherran/tadabur},
  note      = {HuggingFace: huggingface.co/datasets/FaisaI/tadabur}
}

---

_{Tadabur · A Large-Scale Quran Audio Dataset · github.com/fherran/tadabur
Released under CC BY-NC 4.0 for research and educational use. Users must engage with Qur'anic content respectfully.}