Pith. sign in

REVIEW

An Improved Measure of Musical Noise Based on Spectral Kurtosis

Not yet reviewed by Pith; the record is open.

This paper has not been read by Pith yet. Machine review is queued; the pith claim, tier, and objections will appear here once it completes.

SPECIMEN: schema-true, not a live event

T0 review · schema-true

One-sentence machine reading of the paper's core claim.

pith:XXXXXXXX · record.json · timestamp

arxiv 2105.13079 v1 pith:LWONZTK7 submitted 2021-05-27 eess.AS cs.SD

An Improved Measure of Musical Noise Based on Spectral Kurtosis

classification eess.AS cs.SD
keywords audiomeasuremusicalnoisecodinghumanlisteningperception
verification ladder T0 review T1 audit T2 compute T3 formal T4 reserved
0 comments
read the original abstract

Audio processing methods operating on a time-frequency representation of the signal can introduce unpleasant sounding artifacts known as musical noise. These artifacts are observed in the context of audio coding, speech enhancement, and source separation. The change in kurtosis of the power spectrum introduced during the processing was shown to correlate with the human perception of musical noise in the context of speech enhancement, leading to the proposal of measures based on it. These baseline measures are here shown to correlate with human perception only in a limited manner. As ground truth for the human perception, the results from two listening tests are considered: one involving audio coding and one involving source separation. Simple but effective perceptually motivated improvements are proposed and the resulting new measure is shown to clearly outperform the baselines in terms of correlation with the results of both listening tests. Moreover, with respect to the listening test on musical noise in audio coding, the exhibited correlation is nearly as good as the one exhibited by the Artifact-related Perceptual Score (APS), which was found to be the best objective measure for this task. The APS is however computationally very expensive. The proposed measure is easily computed, requiring only a fraction of the computational cost of the APS.

discussion (0)

Sign in with ORCID, Apple, or X to comment. Anyone can read and Pith papers without signing in.