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Co-authored-by: Yoach Lacombe <[email protected]>
README.md
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# Parler-TTS
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<a target="_blank" href="https://huggingface.co/spaces/parler-tts/parler_tts_mini">
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<img src="https://huggingface.co/datasets/huggingface/badges/raw/main/open-in-hf-spaces-sm.svg" alt="Open in HuggingFace"/>
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</a>
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Parler-TTS is a lightweight text-to-speech (TTS) model that can generate high-quality, natural sounding speech in the style of a given speaker (gender, pitch, speaking style, etc). It is a reproduction of work from the paper [Natural language guidance of high-fidelity text-to-speech with synthetic annotations](https://www.text-description-to-speech.com/) 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.
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It consists in:
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* The [Parler-TTS library](https://github.com/huggingface/parler-tts) for using and training high-quality TTS models.
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* The [Data-Speech repository](https://github.com/huggingface/data-speech), for annotating speech characteristics in a large-scale setting.
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* This [organization](https://huggingface.co/parler-tts), that contains the released datasets and weights.
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🚨 [v0.1 model](https://huggingface.co/parler-tts/parler_tts_300M_v0.1) & demo out! Try it out [here](https://huggingface.co/spaces/parler-tts/parler_tts_mini) 🤗!
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