Modeling perceptual similarity of audio signals for blind source separation evaluation

Authors:
Brendan Fox;Andrew Sabin;Bryan Pardo;Alec Zopf
Affiliations:
Northwestern University, Evanston, IL;Northwestern University, Evanston, IL;Northwestern University, Evanston, IL;Northwestern University, Evanston, IL
Venue:
ICA'07 Proceedings of the 7th international conference on Independent component analysis and signal separation
Year:
2007

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Abstract

Existing perceptual models of audio quality, such as PEAQ, were designed to measure audio codec performance and are not well suited to evaluation of audio source separation algorithms. The relationship of many other signal quality measures to human perception is not well established. We collected subjective human assessments of distortions encountered when separating audio sources from mixtures of two to four harmonic sources. We then correlated these assessments to 18 machine-measurable parameters. Results show a strong correlation (r=0.96) between a linear combination of a subset of four of these parameters and mean human assessments. This correlation is stronger than that between human assessments and several measures currently in use.