English

Upsampling artifacts in neural audio synthesis

Sound 2021-02-10 v2 Machine Learning Audio and Speech Processing

Abstract

A number of recent advances in neural audio synthesis rely on upsampling layers, which can introduce undesired artifacts. In computer vision, upsampling artifacts have been studied and are known as checkerboard artifacts (due to their characteristic visual pattern). However, their effect has been overlooked so far in audio processing. Here, we address this gap by studying this problem from the audio signal processing perspective. We first show that the main sources of upsampling artifacts are: (i) the tonal and filtering artifacts introduced by problematic upsampling operators, and (ii) the spectral replicas that emerge while upsampling. We then compare different upsampling layers, showing that nearest neighbor upsamplers can be an alternative to the problematic (but state-of-the-art) transposed and subpixel convolutions which are prone to introduce tonal artifacts.

Keywords

Cite

@article{arxiv.2010.14356,
  title  = {Upsampling artifacts in neural audio synthesis},
  author = {Jordi Pons and Santiago Pascual and Giulio Cengarle and Joan Serrà},
  journal= {arXiv preprint arXiv:2010.14356},
  year   = {2021}
}

Comments

In proceedings of ICASSP2021. Code: https://github.com/DolbyLaboratories/neural-upsampling-artifacts-audio

R2 v1 2026-06-23T19:41:22.550Z