Model Description
This model is an end-to-end deep-learning-based Kinyarwanda Text-to-Speech (TTS). Due to its zero-shot learning capabilities, new voices can be introduced with 1min speech. The model was trained using the Coqui's TTS library, and the YourTTS[1] architecture. It was trained on 67 hours of Kinyarwanda bible data, for 100 epochs.
Data Sources
- Audio data: [www.faithcomesbyhearing.com, version -> Common Language Version audio Old Testament]
- Text data: [www.bible.com, version -> Bibiliya Ijambo ry'imana(BIR)(only the Old Testament was used)]
Usage
Install the Coqui's TTS library:
pip install TTS
Download the files from this repo, then run:
tts --text "text" --model_path best_model.pth --encoder_path SE_checkpoint.pth.tar --encoder_config_path config_se.json --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
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