Update README.md

# Ayah-Corpus: A Multi-Reciter Arabic Quranic Speech Dataset

## Dataset Description:
Ayah-Corpus is a large-scale, multi-reciter Arabic speech dataset meticulously curated for Automatic Speech Recognition (ASR) tasks. It consists of high-quality audio recordings of Quranic verses (Ayahs) paired with their corresponding exact transcriptions. The audio is sourced from two primary repositories: Al-Quran.cloud and EveryAyah.com.

This dataset is specifically designed to facilitate the development of ASR models for Quranic Arabic, which features a distinct vocabulary, phonetic structure, and recitation style (Tajweed) compared to Modern Standard Arabic or colloquial dialects. All audio files have been standardized to a 16kHz sampling rate to be compatible with most modern ASR pipelines.

## Dataset Structure:
The dataset is divided into train, validation, and test splits, ensuring a strict separation of reciters between the sets to evaluate model generalization to unseen voices.

### Data Splits:
| Split | Number of Samples | Number of Reciters |
|-------|------------------|-------------------|
| train | 230,254 | 38 |
| validation | 14,487 | 3 |
| test | 18,593 | 3 |
| **Total** | **263,334** | **44** |

### Data Fields:
Each instance in the dataset consists of the following fields:

- **audio**: A dictionary containing the raw audio data (bytes) and its sampling rate
- **duration**: The duration of the audio file in seconds (float)
- **text**: The ground-truth transcription of the Quranic verse (string)
- **reciter**: The name of the reciter (Qari) (string)

### Data Instance Example:
```python
{
"audio": {
"path": null,
"bytes": "...",
"sampling_rate": 16000
},
"duration": 12.17,
"text": "الْحَمْدُ لِلَّهِ رَبِّ الْعَالَمِينَ",
"reciter": "Karim Mansoori"
}

```
How to Use
The dataset can be easily loaded using the datasets library:

```
from datasets import load_dataset
# Load the dataset
dataset = load_dataset("rabah2026/Ayah-Corpus")

# Accessing a split
train_dataset = dataset["train"]

# Printing the first example
print(train_dataset[0])

```

## Reciters in each Split:
To ensure robustness and prevent data leakage, reciters are exclusively assigned to one split.

### Train Set Reciters (38):
- Abdul Basit
- Abdullah Basfar
- Abdurrahmaan As-Sudais
- Abdul Samad
- Abu Bakr Ash-Shaatree
- Ahmed ibn Ali al-Ajamy
- Alafasy
- Hani Rifai
- Husary
- Husary (Mujawwad)
- Hudhaify
- Ibrahim Akhdar
- Maher Al Muaiqly
- Minshawi
- Minshawy (Mujawwad)
- Muhammad Ayyoub
- Muhammad Jibreel
- Parhizgar
- Ayman Sowaid
- Abdullaah Awaad Al-Juhaynee
- Abdullah Matroud
- Ahmed Neana
- Akram AlAlaqimy
- Ali Hajjaj AlSuesy
- Ali Jaber
- Fares Abbad
- Ghamadi
- Khaalid Abdullaah Al-Qahtaanee
- Mohammad Al Tablaway
- Muhammad AbdulKareem
- Muhsin Al Qasim
- Nabil Rifa3i
- Nasser Alqatami
- Sahl Yassin
- Salaah AbdulRahman Bukhatir
- Salah Al Budair
- Saood Ash-Shuraym
- Yaser Salamah

### Validation Set Reciters (3):
- Mustafa Ismail
- Yasser Ad-Dussary
- Aziz Alili

### Test Set Reciters (3):
- Karim Mansoori
- Khalefa Al Tunaiji
- Mahmoud Ali Al Banna

## Dataset Creation:
The dataset was curated through a multi-step process:

- CSV files containing metadata about audio URLs and transcriptions were collected from alquran.cloud and everyayah.com
- The corresponding audio files were downloaded and converted to .wav format at a 16kHz sampling rate
- A cleaning script ensured data integrity by verifying that every audio file had a corresponding metadata entry
- A processing pipeline packaged the data with metadata into Apache Parquet files
- The data was uploaded to the Hugging Face Hub, chunked into 3 Parquet files per reciter for memory efficiency

## Licensing Information:
This dataset is licensed under the **Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International (CC BY-NC-SA 4.0)** license. You are free to share and adapt the material for non-commercial purposes as long as you give appropriate credit, provide a link to the license, and distribute your contributions under the same license.

## Citation:
If you use this dataset in your research, please cite it as follows:

```bibtex


@dataset
{rabah2026_ayah_corpus,
author = {Rabah},
title = {Ayah-Corpus: A Multi-Reciter Arabic Quranic Speech Dataset},
year = {2025},
url = {https://huggingface.co/datasets/rabah2026/Ayah-Corpus}
}
```
Curated by:
This dataset was curated by Rabah.

README.md

@@ -0,0 +1,16 @@
+---
+license: apache-2.0
+task_categories:
+- automatic-speech-recognition
+language:
+- ar
+tags:
+- quran
+- coran
+- everyayah
+- alquran
+- claud
+pretty_name: Ayah-Corpus
+size_categories:
+- 100B<n<1T
+---