| --- |
| license: cc-by-4.0 |
| tags: |
| - audio |
| - audio-super-resolution |
| - speech |
| - music |
| - flow-matching |
| library_name: pytorch |
| --- |
| |
| # UniverSR - General Audio (Flagship) |
|
|
| Vocoder-free audio super-resolution model that upsamples **8/12/16/24 kHz → 48 kHz** audio using flow matching in the complex STFT domain. Trained on speech, music, and sound effects. |
|
|
| This is the **recommended model** for general use. |
| For speech-only evaluation (e.g. VCTK benchmark), see [universr-speech](https://huggingface.co/woongzip1/universr-speech). |
|
|
| **Paper**: [arXiv:2510.00771](https://arxiv.org/abs/2510.00771) | |
| **Demo**: [woongzip1.github.io/universr-demo](https://woongzip1.github.io/universr-demo/) | **Code**: [github.com/woongzip1/UniverSR](https://github.com/woongzip1/UniverSR) |
|
|
| ## Usage |
|
|
| ```python |
| import torchaudio |
| from universr import UniverSR |
| |
| model = UniverSR.from_pretrained("woongzip1/universr-audio", device="cuda") |
| output = model.enhance("low_res.wav", input_sr=8000) |
| torchaudio.save("output_48k.wav", output.cpu(), 48000) |
| ``` |
|
|
| ## Citation |
|
|
| ```bibtex |
| @inproceedings{choi2026universr, |
| title = {{UniverSR}: Unified and Versatile Audio Super-Resolution via Vocoder-Free Flow Matching}, |
| author = {Choi, Woongjib and Lee, Sangmin and Lim, Hyungseob and Kang, Hong-Goo}, |
| booktitle = {IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP)}, |
| year = {2026} |
| } |
| ``` |
