English

NU-Wave: A Diffusion Probabilistic Model for Neural Audio Upsampling

Audio and Speech Processing 2022-11-10 v2 Artificial Intelligence Machine Learning

Abstract

In this work, we introduce NU-Wave, the first neural audio upsampling model to produce waveforms of sampling rate 48kHz from coarse 16kHz or 24kHz inputs, while prior works could generate only up to 16kHz. NU-Wave is the first diffusion probabilistic model for audio super-resolution which is engineered based on neural vocoders. NU-Wave generates high-quality audio that achieves high performance in terms of signal-to-noise ratio (SNR), log-spectral distance (LSD), and accuracy of the ABX test. In all cases, NU-Wave outperforms the baseline models despite the substantially smaller model capacity (3.0M parameters) than baselines (5.4-21%). The audio samples of our model are available at https://mindslab-ai.github.io/nuwave, and the code will be made available soon.

Keywords

Cite

@article{arxiv.2104.02321,
  title  = {NU-Wave: A Diffusion Probabilistic Model for Neural Audio Upsampling},
  author = {Junhyeok Lee and Seungu Han},
  journal= {arXiv preprint arXiv:2104.02321},
  year   = {2022}
}

Comments

Accepted to Interspeech 2021

R2 v1 2026-06-24T00:52:38.013Z