Update README.md

README.md

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----
-license: cc-by-4.0
----
+---
+license: cc-by-4.0
+language:
+- eu
+pretty_name: Maider Dataset
+size_categories:
+- 10k<n<100k
+task_categories:
+- text-to-speech
+- automatic-speech-recognition
+tags:
+- audio
+- TTS
+- Basque
+- Aholab
+- Ilenia
+- synthetic
+base_model:
+- itzune/maider-tts
+---
+
+# Maider Dataset (Synthetic)
+
+This is a large-scale **synthetic speech corpus** designed for training and fine-tuning Basque Text-to-Speech (TTS) models. It consists of **99,996 audio files** synthesized from the "Maider" voice model.
+
+This dataset was generated by **Itzune** and serves as the primary source for training the [itzune/maider-tts (Piper version)](https://huggingface.co/itzune/maider-tts) model, enabling high-quality Basque synthesis in edge-compatible formats.
+
+## Dataset Structure
+
+Due to the large volume of data (approx. 100,000 files), the dataset is organized in the **WebDataset** format. The audio files are bundled into `.tar` shards to optimize storage, I/O performance, and streaming.
+
+
+
+### Files
+- **data/**: Directory containing the `.tar` shards. Each shard contains approximately 1,000 audio samples.
+- **metadata.csv**: The main metadata file using `|` as a delimiter. It follows this structure:
+  - `file_name`: The name of the audio file (e.g., `audio_1.wav`).
+  - `transcription`: The corresponding Basque text used for synthesis.
+
+## Technical Specifications
+
+- **Audio Format:** WAV (PCM)
+- **Sample Rate:** 22050 Hz
+- **Language:** Basque (eu)
+- **Voice Profile:** Maider (Female)
+- **Total Samples:** 99,996
+- **Generation Method:** Synthesized using VITS-based architecture.
+
+## Usage
+
+You can load this dataset using the Hugging Face `datasets` library. Using `streaming=True` is highly recommended to avoid downloading the entire 100k files at once:
+
+```python
+from datasets import load_dataset
+
+dataset = load_dataset("itzune/maider-dataset", streaming=True)
+
+# View an example
+sample = next(iter(dataset["train"]))
+print(f"Text: {sample['transcription']}")
+```
+
+## Credits and Licensing
+
+### Source and Methodology
+This is a **synthetic dataset** generated by **Itzune**. It was created using the `aHoTTS` synthesis tools provided by **HiTZ Basque Center for Language Technology - Aholab Signal Processing Laboratory**. 
+
+The audio files were synthesized using the pre-trained **Maider (VITS)** model, following the methodology described in the HiTZ/Aholab repository. This dataset serves as a large-scale synthetic corpus for downstream tasks, such as exporting models to edge-compatible formats (e.g., Piper).
+
+### Acknowledgments
+The underlying technology and the original voice models were developed by:
+- **HiTZ Basque Center for Language Technology - Aholab Signal Processing Laboratory**, University of the Basque Country (UPV/EHU).
+- **Project ILENIA:** The Maider voice resource was developed with funding from Project ILENIA.
+
+### License
+- **Dataset Content:** Licensed under [Creative Commons Attribution 4.0 International (CC BY 4.0)](https://creativecommons.org/licenses/by/4.0/).
+- **Original Tools/Code:** The tools used to generate this data are licensed under the **Apache License 2.0** by the original authors.
+
+## Citation
+If you use this dataset, please cite the original work from HiTZ/Aholab:
+> García, V., Hernáez, I., & Navas, E. (2022). Evaluation of Tacotron Based Synthesizers for Spanish and Basque. Applied Sciences, 12(3), 1686. https://doi.org/10.3390/app12031686