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Evaluation of Audio Source Separation Models Using Hypothesis-Driven Non-Parametric Statistical Methods

Simpson, AJR, Roma, G, Grais, EM, Mason, RD, Hummersone, C, Liutkus, A and Plumbley, MD (2016) Evaluation of Audio Source Separation Models Using Hypothesis-Driven Non-Parametric Statistical Methods In: European Signal Processing Conference (EUSIPCO) 2016, 2016-08-29 - 2016-09-02, Budapest.

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Abstract

Audio source separation models are typically evaluated using objective separation quality measures, but rigorous statistical methods have yet to be applied to the problem of model comparison. As a result, it can be difficult to establish whether or not reliable progress is being made during the development of new models. In this paper, we provide a hypothesis-driven statistical analysis of the results of the recent source separation SiSEC challenge involving twelve competing models tested on separation of voice and accompaniment from fifty pieces of “professionally produced” contemporary music. Using nonparametric statistics, we establish reliable evidence for meaningful conclusions about the performance of the various models.

Item Type: Conference or Workshop Item (Conference Paper)
Subjects : Electronic Engineering
Divisions : Faculty of Engineering and Physical Sciences > Electronic Engineering
Authors :
AuthorsEmailORCID
Simpson, AJRUNSPECIFIEDUNSPECIFIED
Roma, GUNSPECIFIEDUNSPECIFIED
Grais, EMUNSPECIFIEDUNSPECIFIED
Mason, RDUNSPECIFIEDUNSPECIFIED
Hummersone, CUNSPECIFIEDUNSPECIFIED
Liutkus, AUNSPECIFIEDUNSPECIFIED
Plumbley, MDUNSPECIFIEDUNSPECIFIED
Date : 2016
Copyright Disclaimer : © 2016 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.
Related URLs :
Depositing User : Symplectic Elements
Date Deposited : 12 Jul 2016 10:16
Last Modified : 12 Jul 2016 10:16
URI: http://epubs.surrey.ac.uk/id/eprint/811172

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