LISA (Local Implicit representation for Super resolution of Arbitrary scale)
This repository contains the official implementation for LISA introduced in the following paper:
Learning Continuous Representation of Audio for Arbitrary Scale Super Resolution.
The paper can be found at https://arxiv.org/abs/2111.00195.
Environment
- Python 3
- Pytorch 1.6.0
- TensorboardX
- yaml, numpy, tqdm, imageio
If you find out any other dependency is required, please let us know via github issue or pull requests.
Reproducing Experiments
-
Read
scripts/setup.shandconfigs/audio/lisa.yamlcarefully for model and experiments setup. -
Prepare datasets to use (such as VCTK).
To train model: run scripts/train_audio.sh
How to cite
If you find our work useful in your research, please cite:
@inproceedings{kim2021lisa,
title={Learning Continuous Representation of Audio for Arbitrary Scale Super Resolution},
author={Jaechang Kim and Yunjoo Lee and Seunghoon Hong and Jungseul Ok},
booktitle={ICASSP},
year={2022}
}
Reference
This repository is based on previous works below.

