README.md

---
license: cc-by-4.0
tags:
- quran-persian
- quranpersian
- text-to-speech
- tts
- speech-synthesis
- persian
- data-collection
- data-preprocessing
- speech-processing
- forced-alignment
- speech-dataset
- speech-corpus
- dataset-preparation
- persian-speech
- tts-dataset
- text-to-speech-dataset
- mana-tts
- manatts
- speech-data-collection
---

# Quran Persian Translation

![Hugging Face](https://img.shields.io/badge/Hugging%20Face-Dataset-orange)

Quran Persian Translation is a Persian dataset of over 20 hours of audio and text pairs designed for speech synthesis and other speech-related tasks. The dataset has been collected, processed, and annotated as a part of the Mana-TTS project. For details on data processing pipeline and statistics, please refer to the paper in the Citation secition.

## Acknowledgement
The raw audio and text files have been collected from the Persian translation of quran by [Masoud Riaei](https://www.masoudriaei.com/?page_id=4275) and read aloud by Behrouz Razavi. 
We thank the [Asr-e-Kankash](http://www.asrekankash.ir/) publication for granting the permission to publish the processed data under an open license.

### Data Columns

Each Parquet file contains the following columns:

- **file name** (`string`): The unique identifier of the audio file.
- **transcript** (`string`): The ground-truth transcript corresponding to the audio.
- **duration** (`float64`): Duration of the audio file in seconds.
- **match quality** (`string`): Either "HIGH" for `CER < 0.05` or "MIDDLE" for `0.05 < CER < 0.2` between actual and hypothesis transcript.
- **hypothesis** (`string`): The best transcript generated by ASR as hypothesis to find the matching ground-truth transcript.
- **CER** (`float64`): The Character Error Rate (CER) of the ground-truth and hypothesis transcripts.
- **search type** (`int64`): Either 1 indicating the GT transcripts is result of Interval Search or 2 if a result of Gapped Search (refer to paper for more details).
- **ASRs** (`string`): The Automatic Speech Recognition (ASR) systems used in order to find a satisfying matching transcript.
- **audio** (`sequence`): The actual audio data.
- **samplerate** (`float64`): The sample rate of the audio.

## Usage

To use the dataset, you can load it directly using the Hugging Face datasets library:

```python
from datasets import load_dataset

dataset = load_dataset("MahtaFetrat/Quran-Persian", split='train')
```

You can also download specific parts or the entire dataset:

```bash
# Download a specific part
wget https://huggingface.co/datasets/MahtaFetrat/Quran-Persian/resolve/main/dataset/dataset_part_01.parquet

# Download the entire dataset
git clone https://huggingface.co/datasets/MahtaFetrat/Quran-Persian
```

## Citation

If you use Quran-Persian in your research or projects, please cite the following paper:

```bash
@inproceedings{qharabagh-etal-2025-manatts,
    title = "{M}ana{TTS} {P}ersian: a recipe for creating {TTS} datasets for lower resource languages",
    author = "Qharabagh, Mahta Fetrat  and Dehghanian, Zahra  and Rabiee, Hamid R.",
    booktitle = "Proceedings of the 2025 Conference of the Nations of the Americas Chapter of the Association for Computational Linguistics: Human Language Technologies (Volume 1: Long Papers)",
    month = apr,
    year = "2025",
    address = "Albuquerque, New Mexico",
    publisher = "Association for Computational Linguistics",
    url = "https://aclanthology.org/2025.naacl-long.464/",
    pages = "9177--9206",
}
```

## License

This dataset is available under the cc-by-4.0. However, the dataset should not be utilized for replicating or imitating the speaker’s voice for malicious
purposes or unethical activities, including voice cloning for malicious intent.