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--- |
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language: en |
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license: bsd-3-clause |
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library_name: pytorch-lightning |
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tags: |
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- pytorch |
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- pytorch-lightning |
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- audio-upsampling |
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datasets: vctk |
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model_name: nu-wave-x2 |
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--- |
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# nu-wave-x2 |
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## Model description |
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NU-Wave: A Diffusion Probabilistic Model for Neural Audio Upsampling |
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- [GitHub Repo](https://github.com/mindslab-ai/nuwave) |
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- [Paper](https://arxiv.org/pdf/2104.02321.pdf) |
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This model was trained by contributor Frederico S. Oliveira, who graciously [provided the checkpoint](https://github.com/mindslab-ai/nuwave/issues/18) in this repo in the original author's GitHub repo. |
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This model was trained using source code written by Junhyeok Lee and Seungu Han under the BSD 3.0 License. All credit goes to them for this work. |
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This model takes in audio at 24kHz and upsamples it to 48kHz. |
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## Intended uses & limitations |
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#### How to use |
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```python |
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# You can include sample code which will be formatted |
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``` |
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#### Limitations and bias |
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Provide examples of latent issues and potential remediations. |
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## Training data |
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Describe the data you used to train the model. |
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If you initialized it with pre-trained weights, add a link to the pre-trained model card or repository with description of the pre-training data. |
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## Training procedure |
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Preprocessing, hardware used, hyperparameters... |
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## Eval results |
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Provide some evaluation results. |
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### BibTeX entry and citation info |
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```bibtex |
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@inproceedings{..., |
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year={2020} |
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} |
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``` |
