NVIDIA Deep Learning Examples
NVIDIA Deep Learning Examples
HiFi-GAN for PyTorch
Resource
NVIDIA Deep Learning Examples
NVIDIA Deep Learning Examples
HiFi-GAN for PyTorch

HiFi-GAN model implements a spectrogram inversion model that allows to synthesize speech waveforms from mel-spectrograms.

The performance measurements in this document were conducted at the time of publication and may not reflect the performance achieved from NVIDIA's latest software release. For the most up-to-date performance measurements, go to https://developer.nvidia.com/deep-learning-performance-training-inference.

Changelog

February 2022

  • Initial release

Known issues

  • With mixed-precision training on Ampere GPUs, the model might suffer from slower training. Be sure to use the scripts provided in the platform/ directory, and a PyTorch NGC container not older than 21.12-py3.
  • For some mel-spectrogram generator models, the best results require fine-tuning of HiFi-GAN on outputs from those models. For more details, refer to the fine-tuning step of the Quick Start Guide section.

NVIDIA uses cookies to improve your experience on our web site. We and our third-party partners also use cookies and other tools to collect and record information you provide as well as information about your interactions with our websites for performance improvement, analytics, and to assist in marketing efforts. By clicking "Accept All", you consent to our use of cookies and other tools as described in our Cookie Policy. You can manage your cookie settings by clicking on "Manage Settings." By continuing to use this site or by clicking one of the buttons below, you agree to our Terms of Service (which contains important waivers). Please see our Privacy Policy for more information on our privacy practices.