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Speech Synthesis HiFi-GAN

Logo for Speech Synthesis HiFi-GAN
GAN-based waveform generator from mel-spectrograms.
Latest Version
April 4, 2023
49.49 MB

Speech Synthesis: HifiGAN Model Card

Model overview

HifiGAN is a neural vocoder model for text-to-speech applications. It is intended as the second part of a two-stage speech synthesis pipeline, with a mel-spectrogram generator such as FastPitch as the first stage.

Model architecture

HifiGAN is a neural vocoder based on a generative adversarial network framework, During training, the model uses a powerful discriminator consisting of small sub-discriminators, each one focusing on specific periodic parts of a raw waveform. The generator is very fast and has a small footprint, while producing high quality speech.



This model is trained on LJSpeech sampled at 22050Hz.

How to use this model

HifiGAN is intended to be used as the second part of a two stage speech synthesis pipeline. HifiGAN takes a mel spectrogram and returns audio.

Input: Mel spectrogram of shape (batch x mel_channels x time)

Output: Audio of shape (batch x time)




HifiGAN paper:


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