Aliasing-Free Neural Audio Synthesis
This is the official Hugging Face model repository for the paper "Aliasing-Free Neural Audio Synthesis", which is the first work to achieve simple and efficient aliasing-free upsampling-based neural audio generation in the entire field of neural vocoders and codecs.
[Project Page] [GitHub Repository] [Paper]
Model Checkpoints
This repository contains the following checkpoints:
| Model Name | Directory | Description |
|---|---|---|
| Pupu-Vocoder_Small | ./pupuvocoder/* | 14M parameter small version of Pupu-Vocoder. |
| Pupu-Vocoder_Large | ./pupuvocoder_large/* | 122M parameter large version of Pupu-Vocoder. |
| Pupu-Codec_Small | ./pupucodec/* | 32M parameter small version of Pupu-Codec. |
| Pupu-Codec_Large | ./pupucodec_large/* | 119M parameter large version of Pupu-Codec. |
How to use
You need to put the pretrained models in:
AliasingFreeNeuralAudioSynthesis/experiments
of our official repository, and then follow the instructions written in the GitHub repository to resume, finetune, and inference our pretrained checkpoints.
Citation
@article{afgen,
title = {Aliasing Free Neural Audio Synthesis},
author = {Yicheng Gu and Junan Zhang and Chaoren Wang and Jerry Li and Zhizheng Wu and Lauri Juvela},
year = {2025},
journal = {arXiv:2512.20211},
}