YourTTS: Towards Zero-Shot Multi-Speaker TTS and Zero-Shot Voice Conversion for everyone
Paper • 2112.02418 • Published • 5
Model Description
This model is an end-to-end deep-learning-based Kinyarwanda Text-to-Speech (TTS). The model was trained using the Coqui's TTS library, and the YourTTS[1] architecture.
Usage
Install the Coqui's TTS library:
pip install TTS
Download the files from this repo, then run:
tts --text "text" --model_path model.pth --config_path config.json --speakers_file_path speakers.pth --speaker_wav conditioning_audio.wav --out_path out.wav
Where the conditioning audio is a wav file(s) to condition a multi-speaker TTS model with a Speaker Encoder, you can give multiple file paths. The d_vectors is computed as their average.
References
[1] YourTTS paper
[2] Kinyarwanda TTS: Using a multi-speaker dataset to build a Kinyarwanda TTS model
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