coqui-tts/recipes/thorsten_DE
Noran Raskin a790df4e94
Training recipes for thorsten dataset (#1020)
* Fix style

* Fix isort

* Remove tensorboardX from requirements

Co-authored-by: logan hart <72301874+loganhart420@users.noreply.github.com>
Co-authored-by: Eren Gölge <egolge@coqui.ai>
2022-05-30 12:07:31 +02:00
..
align_tts Training recipes for thorsten dataset (#1020) 2022-05-30 12:07:31 +02:00
glow_tts Training recipes for thorsten dataset (#1020) 2022-05-30 12:07:31 +02:00
hifigan Training recipes for thorsten dataset (#1020) 2022-05-30 12:07:31 +02:00
multiband_melgan Training recipes for thorsten dataset (#1020) 2022-05-30 12:07:31 +02:00
speedy_speech Training recipes for thorsten dataset (#1020) 2022-05-30 12:07:31 +02:00
tacotron2-DDC Training recipes for thorsten dataset (#1020) 2022-05-30 12:07:31 +02:00
univnet Training recipes for thorsten dataset (#1020) 2022-05-30 12:07:31 +02:00
vits_tts Training recipes for thorsten dataset (#1020) 2022-05-30 12:07:31 +02:00
wavegrad Training recipes for thorsten dataset (#1020) 2022-05-30 12:07:31 +02:00
wavernn Training recipes for thorsten dataset (#1020) 2022-05-30 12:07:31 +02:00
README.md Training recipes for thorsten dataset (#1020) 2022-05-30 12:07:31 +02:00
download_thorsten_DE.sh Training recipes for thorsten dataset (#1020) 2022-05-30 12:07:31 +02:00

README.md

🐸💬 TTS Thorsten Recipes

For running the recipes you need the Thorsten-Voice dataset.

You can download it manually from the official website or use download_thorsten_de.sh alternatively running any of the train_modelX.pyscripts will download the dataset if not already present.

Then, go to your desired model folder and run the training.

Running Python files. (Choose the desired GPU ID for your run and set ```CUDA_VISIBLE_DEVICES```)
```terminal
CUDA_VISIBLE_DEVICES="0" python train_modelX.py
```

💡 Note that these runs are just templates to help you start training your first model. They are not optimized for the best result. Double-check the configurations and feel free to share your experiments to find better parameters together 💪.