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. © Springer-Verlag Berlin Heidelberg 2007.
CITATION STYLE
Fox, B., Sabin, A., Pardo, B., & Zopf, A. (2007). Modeling perceptual similarity of audio signals for blind source separation evaluation. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 4666 LNCS, pp. 454–461). Springer Verlag. https://doi.org/10.1007/978-3-540-74494-8_57
Mendeley helps you to discover research relevant for your work.