JoTTS is a German text-to-speech engine using tacotron and griffin-lim or wavernn as vocoder. The synthesizer model has been trained on my voice using tacotron1. Using grifin-lim as vocoder makes the audio generation much faster whereas using a trained vocoder returns better results in most cases.
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First create an instance of JoTTS.
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(optional) List all models that are available using list_models(). You can also look them up in the browser: https://github.com/padmalcom/Real-Time-Voice-Cloning-German/releases
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Load a model of your choice using load_models() which takes force_model_download as an optional parameter in case that the last download of the synthesizer failed and the model cannot be applied. The parameter model_name is validated against all available models on the release page.
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Call speak with a text parameter that contains the text to speak out loud. The second parameter wait_for_end can be set to True, to wait until speaking is done, e.g. to prevent your application to close. If you want to use a trained vocoder, set use_wavernn_vocoder to True.
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Use textToWav to create a wav file instead of speaking the text. out_path specifies where the wav file is written to. Use use_wavernn_vocoder to use a trained vocoder.
from jotts import JoTTS
if __name__ == "__main__":
tts = JoTTS()
tts.list_models()
tts.load_models(force_model_download=False, model_name="jonas_v0.1")
tts.speak("Das ist ein Test mit meiner Stimme.", wait_for_end = True, use_wavernn_vocoder=True)
tts.speak("Das ist ein Test mit meiner Stimme.", wait_for_end = True, use_wavernn_vocoder=False)
tts.textToWav(text="Das ist ein Test mit meiner Stimme.", out_path="vocoder_out.wav", use_wavernn_vocoder=True)
tts.textToWav(text="Das ist ein Test mit meiner Stimme.", out_path="griffin_lim_out.wav", use_wavernn_vocoder=False)- Add an option to change the default audio device to speak the text
- Add threading or multi processing to allow speaking without blocking
- Add a parameter to avoid online communication in case of running JoTTS on edge.
- Add a feature to quickly finetune a model with a arbitrary voice
Training a synthesizer model is easy - if you know how to do it. I created a course on udemy to show you how it is done. Don't buy the tutorial for the full price, there is a discout every month :-)
https://www.udemy.com/course/voice-cloning/
If you neither have the backgroud or the resources or if you are just lazy or too rich, contact me for contract work. Cloning a voice normally needs ~15 Minutes of clean audio from the voice you want to clone.
I hope that my (and any other person's) voice will be used only for legal and ethical purposes. Please do not get into mischief with it.