@inproceedings{4b47e28d32bd46cb9ad946f3a8401761,
title = "Modeling perceptual similarity of audio signals for blind source separation evaluation",
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.",
keywords = "Audio, Music, Perceptual model, Source separation",
author = "Brendan Fox and Andrew Sabin and Pardo, {Bryan A} and Alec Zopf",
year = "2007",
doi = "10.1007/978-3-540-74494-8_57",
language = "English (US)",
isbn = "9783540744931",
series = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",
publisher = "Springer Verlag",
pages = "454--461",
booktitle = "Independent Component Analysis and Signal Separation - 7th International Conference, ICA 2007, Proceedings",
note = "7th International Conference on Independent Component Analysis (ICA) and Source Separation, ICA 2007 ; Conference date: 09-09-2007 Through 12-09-2007",
}