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Psychophysical Evaluation of Audio Source Separation Methods

Simpson, AJR, Roma, G, Grais, Emad M, Mason, Russell, Hummersone, Christopher and Plumbley, Mark (2017) Psychophysical Evaluation of Audio Source Separation Methods In: 13th International Conference on Latent Variable Analysis and Signal Separation (LVA/ICA 2017), 2017-02-21 - 2017-02-23, Grenoble, France.

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Source separation evaluation is typically a top-down process, starting with perceptual measures which capture fitness-for-purpose and followed by attempts to find physical (objective) measures that are predictive of the perceptual measures. In this paper, we take a contrasting bottom-up approach. We begin with the physical measures provided by the Blind Source Separation Evaluation Toolkit (BSS Eval) and we then look for corresponding perceptual correlates. This approach is known as psychophysics and has the distinct advantage of leading to interpretable, psychophysical models. We obtained perceptual similarity judgments from listeners in two experiments featuring vocal sources within musical mixtures. In the first experiment, listeners compared the overall quality of vocal signals estimated from musical mixtures using a range of competing source separation methods. In a loudness experiment, listeners compared the loudness balance of the competing musical accompaniment and vocal. Our preliminary results provide provisional validation of the psychophysical approach

Item Type: Conference or Workshop Item (Conference Paper)
Subjects : Electronic Engineering
Divisions : Faculty of Engineering and Physical Sciences > Electronic Engineering
Authors :
Simpson, AJR
Roma, G
Grais, Emad
Date : 15 February 2017
DOI : 10.1007/978-3-319-53547-0_21
Copyright Disclaimer : The final publication is available at
Contributors :
Uncontrolled Keywords : Deep learning, source separation, perceptual evaluation
Related URLs :
Depositing User : Symplectic Elements
Date Deposited : 14 Dec 2016 16:08
Last Modified : 16 Jan 2019 17:10

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