Added dataset information

README.md

@@ -19,3 +19,77 @@ configs:
   - split: train
     path: data/train-*
 ---
+---
+license: cc0-1.0
+language:
+- de
+task_categories:
+- text-to-speech
+tags:
+- text-to-speech
+- tts
+- german
+- voice
+- orpheus-tts
+- thorsten-voice
+---
+
+# Thorsten-Voice TV-24kHz-Neutral-tokenised
+
+## Overview
+
+This dataset is a **tokenised German text-to-speech dataset** created for training and fine-tuning the **Orpheus TTS** model family.
+
+It is based on approximately **12,000 speech recordings** from the original **Thorsten-Voice Dataset (2022.10)** and has been **resampled to 24 kHz** and **tokenised using Orpheus TTS preprocessing**.
+
+This dataset is intended for:
+- Training and fine-tuning Orpheus-based German TTS models
+- Research on neural speech synthesis
+- Open, unrestricted TTS experimentation
+
+---
+
+## Dataset Origin
+
+- **Original dataset:** Thorsten-Voice Dataset 2022.10  
+- **DOI:** https://doi.org/10.5281/zenodo.7265581  
+- **Language:** German (de)  
+- **Speaker:** Thorsten (single speaker)
+
+All audio originates from the original Thorsten-Voice corpus and was reprocessed for compatibility with Orpheus TTS.
+
+---
+
+## Processing Details
+
+- Audio resampled to **24,000 Hz**
+- Loudness normalized to **-24dB**
+- Tokenised using the **Orpheus TTS tokenizer** jupyter notebook (huggingface dataset package < 4)
+- Stored as a tokenised dataset ready for training
+
+The tokenisation reflects the **Orpheus TTS codebase as of December 2025**.
+
+---
+
+## License
+
+This dataset is released under the **Creative Commons Zero (CC0 1.0)** license.
+
+> You are free to use, modify, distribute and build upon this dataset for any purpose, including commercial use, without restriction.
+
+---
+
+## Related Projects
+
+- **Thorsten-Voice Project:**  
+  https://www.Thorsten-Voice.de
+
+- **Orpheus TTS (GitHub):**  
+  https://github.com/canopylabs/orpheus-tts
+
+---
+
+## Notes
+
+This dataset is part of the ongoing **Thorsten-Voice** ecosystem and is provided to support open, reproducible speech synthesis research.
+