See this page for a large list of example outputs.Ĭool application of Tortoise+GPT-3 (not by me): Usage guide ColabĬolab is the easiest way to try this out. On a K80, expect to generate a medium sized sentence every 2 minutes.
It leverages both an autoregressive decoder and a diffusion decoder both known for their low Tortoise is a bit tongue in cheek: this model I'm naming my speech-related repos after Mojave desert flora and fauna. Added ability to use your own pretrained models.Added ability to download voice conditioning latent via a script, and then use a user-provided conditioning latent.Added ability to produce totally random voices.Wrap the text you want to use to prompt the model but not be spoken in brackets. Added several new voices from the training set.Improvements to read.py and do_tts.py (new options).New CLVP-large model for further improved decoding guidance.Add better debugging support existing tools now spit out debug files which can be used to reproduce bad runs.Found that it does not, in fact, make an appreciable difference in the output. I would definitely appreciate any comments, suggestions or reviews:
This repo contains all the code needed to run Tortoise TTS in inference mode.Ī ( very) rough draft of the Tortoise paper is now available in doc format.
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