Create README.md

README.md

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+# 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)