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---
license: mit
language:
- en
- zh
- ja
tags:
- speech
- singing
- singing voice
- audio
- music
- vocoder
- codec
- pytorch
---
## Aliasing-Free Neural Audio Synthesis
This is the official Hugging Face model repository for the paper **"[Aliasing-Free Neural Audio Synthesis](https://arxiv.org/abs/2512.20211)"**, 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.
For more details, please visit our [GitHub Repository](https://github.com/sizigi/AliasingFreeNeuralAudioSynthesis).
## 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:
```bash
AliasingFreeNeuralAudioSynthesis/experiments
```
of our official repository, and then follow the instructions written in the repository to resume, finetune, and inference our pretrained checkpoints.
## Citation
```bibtex
@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},
}
```
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