BSS Eval or Peass? Predicting the Perception of Singing-Voice Separation
Dominic Ward, Hagen Wierstorf, Russell D. Mason, Emad M. Grais, Mark D. Plumbley
Abstract
There is some uncertainty as to whether objective metrics for predicting the perceived quality of audio source separation are sufficiently accurate. This issue was investigated by employing a revised experimental methodology to collect subjective ratings of sound quality and interference of singing-voice recordings that have been extracted from musical mixtures using state-of-the-art audio source separation. A correlation analysis between the experimental data and the measures of two objective evaluation toolkits, BSS Eval and PEASS, was performed to assess their performance. The artifacts-related perceptual score of the PEASS toolkit had the strongest correlation with the perception of artifacts and distortions caused by singing-voice separation. Both the source-to-interference ratio of BSS Eval and the interference-related perceptual score of PEASS showed comparable correlations with the human ratings of interference.
BibTeX
@inproceedings{icassp2018_bssevalorpeasspr,
title = {BSS Eval or Peass? Predicting the Perception of Singing-Voice Separation},
author = {Dominic Ward and Hagen Wierstorf and Russell D. Mason and Emad M. Grais and Mark D. Plumbley},
booktitle = {ICASSP 2018},
year = {2018}
}