---
license: cc0-1.0
language:
- fa
tags:
- 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
---
# ManaTTS-Persian-Speech-Dataset  

**ManaTTS** is the largest publicly available single-speaker Persian corpus, comprising over **114 hours** of high-quality audio (sampled at **44.1 kHz**). Released under the permissive **CC-0 license**, this dataset is freely usable for both educational and commercial purposes.  

Collected from **[Nasl-e-Mana](https://naslemana.com/)** magazine, the dataset covers a diverse range of topics, making it ideal for training robust **text-to-speech (TTS) models**. The release includes a **fully transparent, open-source pipeline** for data collection and processing, featuring tools for **audio segmentation** and **forced alignment**. For the full codebase, visit the **[ManaTTS GitHub repository](https://github.com/MahtaFetrat/ManaTTS-Persian-Speech-Dataset)**.  

---

### Dataset Columns  

| Column Name      | Description |
|------------------|-------------|
| **file_name**    | Unique identifier for the audio file. |
| **transcript**   | Ground-truth text transcription of the audio chunk. |
| **duration**     | Duration of the audio chunk (in seconds). |
| **match_quality** | Quality of alignment between the approximate transcript and ground truth (`HIGH` or `MIDDLE`). Reflects confidence in transcript accuracy (see [paper](https://aclanthology.org/2025.naacl-long.464/) for details). |
| **hypothesis**   | Approximate transcript used to search for the ground-truth text. |
| **CER**          | Character Error Rate between the hypothesis and accepted transcript. |
| **search_type**  | Indicates whether the transcript was matched continuously in the source text (`type 1`) or with gaps (`type 2`). |
| **ASRs**         | Ordered list of ASRs used until a match was found. |
| **audio**        | Audio file as a numerical array. |
| **sample_rate**  | Sampling rate of the audio file (44.1 kHz). |

---

## Usage

### Python (Hugging Face)
First install the required package:
```bash
pip install datasets
```

Then load the data:
```python
from datasets import load_dataset

# Load a specific partition (e.g., part 001)
dataset = load_dataset("MahtaFetrat/Mana-TTS", 
                      data_files="dataset/dataset_part_001.parquet", 
                      split="train")

# Inspect the data
print(dataset)
print(dataset[0])  # View first sample
```

### Command Line (wget)
Download individual files directly:
```bash
# Download single file (e.g., part 001)
wget https://huggingface.co/datasets/MahtaFetrat/Mana-TTS/resolve/main/dataset/dataset_part_001.parquet
```

---

## Trained TTS Model  

[![Hugging Face](https://img.shields.io/badge/Hugging%20Face-Model-orange)](https://huggingface.co/MahtaFetrat/Persian-Tacotron2-on-ManaTTS)  

A **Tacotron2-based TTS model** trained on ManaTTS is available on Hugging Face. For inference and weights, visit the [model repository](https://huggingface.co/MahtaFetrat/Persian-Tacotron2-on-ManaTTS).  

---

## Contributing  

Contributions to this project are welcome! If you encounter any issues or have suggestions for improvements, please open an issue or submit a pull request.

---

## License  

This dataset is released under the **[CC-0 1.0 license](https://creativecommons.org/publicdomain/zero/1.0/)**.  

---

## Ethical Use Notice  

The ManaTTS dataset is intended **exclusively for ethical research and development**. Misuse—including voice impersonation, identity theft, or fraudulent activities—is strictly prohibited. By using this dataset, you agree to uphold **integrity and privacy standards**. Violations may result in legal consequences.  

For questions, contact the maintainers.  

---

## Acknowledgments  

We extend our deepest gratitude to **[Nasl-e-Mana](https://naslemana.com/)**, the monthly magazine of Iran’s blind community, for their generosity in releasing this data under **CC-0**. Their commitment to open collaboration has been pivotal in advancing Persian speech synthesis.  

---

## Community Impact  

We encourage researchers and developers to leverage this resource for **assistive technologies**, such as screen readers, to benefit the Iranian blind community. Open-source collaboration is key to driving accessibility innovation.  

---

## Citation  

If you use ManaTTS in your work, cite our paper:  

```bibtex
@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 North American Chapter of the Association for Computational Linguistics",
    month = apr,
    year = "2025",
    address = "Albuquerque, New Mexico",
    publisher = "Association for Computational Linguistics",
    pages = "9177--9206",
    url = "https://aclanthology.org/2025.naacl-long.464/",
}
```

---


## Aditional Links
- [ManaTTS Github Repository](https://github.com/MahtaFetrat/ManaTTS-Persian-Speech-Dataset/tree/main)
- [ManaTTS Paper](https://aclanthology.org/2025.naacl-long.464/)
- [Nasl-e-Mana Magazine](https://naslemana.com/)
- Tacotron2 Trained on ManaTTS [Huggingface](https://huggingface.co/MahtaFetrat/Persian-Tacotron2-on-ManaTTS) | [Github](https://github.com/MahtaFetrat/ManaTTS-Persian-Tacotron2-Model)