NU-Wave: A Diffusion Probabilistic Model for Neural Audio Upsampling
About
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.
Related benchmarks
| Task | Dataset | Result | Rank | |
|---|---|---|---|---|
| Speech Super-resolution | VCTK 0.92 (test) | LSD1.22 | 16 | |
| Audio Bandwidth Extension | VCTK (test) | LSD3.8 | 4 |