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--- |
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license: cc0-1.0 |
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language: |
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- fa |
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tags: |
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- text-to-speech |
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- tts |
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- speech-synthesis |
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- persian |
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- data-collection |
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- data-preprocessing |
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- speech-processing |
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- forced-alignment |
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- speech-dataset |
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- speech-corpus |
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- dataset-preparation |
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- persian-speech |
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- tts-dataset |
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- text-to-speech-dataset |
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- mana-tts |
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- manatts |
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- speech-data-collection |
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--- |
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# ManaTTS-Persian-Speech-Dataset |
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**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. |
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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)**. |
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--- |
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### Dataset Columns |
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| Column Name | Description | |
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|------------------|-------------| |
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| **file_name** | Unique identifier for the audio file. | |
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| **transcript** | Ground-truth text transcription of the audio chunk. | |
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| **duration** | Duration of the audio chunk (in seconds). | |
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| **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). | |
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| **hypothesis** | Approximate transcript used to search for the ground-truth text. | |
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| **CER** | Character Error Rate between the hypothesis and accepted transcript. | |
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| **search_type** | Indicates whether the transcript was matched continuously in the source text (`type 1`) or with gaps (`type 2`). | |
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| **ASRs** | Ordered list of ASRs used until a match was found. | |
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| **audio** | Audio file as a numerical array. | |
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| **sample_rate** | Sampling rate of the audio file (44.1 kHz). | |
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--- |
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## Usage |
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### Python (Hugging Face) |
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First install the required package: |
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```bash |
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pip install datasets |
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``` |
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Then load the data: |
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```python |
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from datasets import load_dataset |
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# Load a specific partition (e.g., part 001) |
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dataset = load_dataset("MahtaFetrat/Mana-TTS", |
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data_files="dataset/dataset_part_001.parquet", |
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split="train") |
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# Inspect the data |
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print(dataset) |
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print(dataset[0]) # View first sample |
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``` |
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### Command Line (wget) |
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Download individual files directly: |
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```bash |
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# Download single file (e.g., part 001) |
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wget https://huggingface.co/datasets/MahtaFetrat/Mana-TTS/resolve/main/dataset/dataset_part_001.parquet |
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``` |
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--- |
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## Trained TTS Model |
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[](https://huggingface.co/MahtaFetrat/Persian-Tacotron2-on-ManaTTS) |
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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). |
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--- |
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## Contributing |
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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. |
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--- |
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## License |
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This dataset is released under the **[CC-0 1.0 license](https://creativecommons.org/publicdomain/zero/1.0/)**. |
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--- |
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## Ethical Use Notice |
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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. |
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For questions, contact the maintainers. |
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--- |
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## Acknowledgments |
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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. |
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--- |
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## Community Impact |
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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. |
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--- |
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## Citation |
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If you use ManaTTS in your work, cite our paper: |
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```bibtex |
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@inproceedings{qharabagh-etal-2025-manatts, |
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title = "{M}ana{TTS} {P}ersian: A Recipe for Creating {TTS} Datasets for Lower-Resource Languages", |
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author = "Qharabagh, Mahta Fetrat and Dehghanian, Zahra and Rabiee, Hamid R.", |
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booktitle = "Proceedings of the 2025 Conference of the North American Chapter of the Association for Computational Linguistics", |
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month = apr, |
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year = "2025", |
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address = "Albuquerque, New Mexico", |
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publisher = "Association for Computational Linguistics", |
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pages = "9177--9206", |
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url = "https://aclanthology.org/2025.naacl-long.464/", |
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} |
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``` |
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--- |
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## Aditional Links |
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- [ManaTTS Github Repository](https://github.com/MahtaFetrat/ManaTTS-Persian-Speech-Dataset/tree/main) |
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- [ManaTTS Paper](https://aclanthology.org/2025.naacl-long.464/) |
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- [Nasl-e-Mana Magazine](https://naslemana.com/) |
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- Tacotron2 Trained on ManaTTS [Huggingface](https://huggingface.co/MahtaFetrat/Persian-Tacotron2-on-ManaTTS) | [Github](https://github.com/MahtaFetrat/ManaTTS-Persian-Tacotron2-Model) |
