Natural language guidance of high-fidelity text-to-speech with synthetic annotations by Dan Lyth and Simon King, from Stability AI and Edinburgh University respectively.

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Contrary to other TTS models, Parler-TTS is a fully open-source release. All of the datasets, pre-processing, training code, and weights are released publicly under a permissive license, enabling the community to build on our work and develop their own powerful TTS models.\nIt consists in:

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• The Parler-TTS library for using and training high-quality TTS models.
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• The Data-Speech repository, for annotating speech characteristics in a large-scale setting.
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• This organization, that contains the released datasets and weights.
\n

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🚨 Two new checkpoints, Parler-TTS Mini v1.1 and Large v1, are out! 🚨\nTrained on 45k hours of narrated audio, they're better and faster than previous versions, and introduce speaker consistency across generations.\nTry them out here 🤗!

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