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  This repository provides all the necessary tools for using a [scalable HiFiGAN Unit](https://arxiv.org/abs/2406.10735) vocoder trained with [LibriTTS](https://www.openslr.org/141/).
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- The pre-trained model take as input discrete self-supervised representations and produces a waveform as output. Typically, this model is utilized on top of a speech-to-unit translation model that converts an input utterance from a source language into a sequence of discrete speech units in a target language.
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- To generate the discrete self-supervised representations, we employ a K-means clustering model trained on WavLM hidden layers, with `k=1000`.
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  ## Install SpeechBrain
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  This repository provides all the necessary tools for using a [scalable HiFiGAN Unit](https://arxiv.org/abs/2406.10735) vocoder trained with [LibriTTS](https://www.openslr.org/141/).
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+ The pre-trained model take as input continous self-supervised representations and produces a waveform as output. This is suitable for a wide range of generative tasks such as speech enhancement, separation, text-to-speech, voice cloning, etc. Please read [DASB - Discrete Audio and Speech Benchmark](https://arxiv.org/abs/2406.14294) for more information.
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+ To generate the continuous self-supervised representations, we use `microsoft/wavlm-large`.
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  ## Install SpeechBrain
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