Instructions to use alphacep/vosk-vc-ru with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use alphacep/vosk-vc-ru with Transformers:
# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("alphacep/vosk-vc-ru", dtype="auto") - Notebooks
- Google Colab
- Kaggle
About
This is a basic zero-shot voice conversion model trained with VITS + contentvec
See:
https://github.com/alphacep/vosk-tts/tree/master/vc
https://github.com/quickvc/QuickVC-VoiceConversion
https://github.com/auspicious3000/contentvec
Speaker Similarity
Computed with eval.py with Resemblyzer
Original QuickVC (trained on VCTK) Average: 0.667 Min: 0.477
New model Average: 0.880 Min: 0.712
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