The University of Southampton
University of Southampton Institutional Repository

Towards effective singing voice extraction from stereophonic recordings

Sofianos, S., Ariyaeeinia, A. and Polfreman, R. (2010) Towards effective singing voice extraction from stereophonic recordings In 2010 IEEE International Conference on Acoustics Speech and Signal Processing (ICASSP). IEEE., pp. 233-236. (doi:10.1109/ICASSP.2010.5496004).

Record type: Conference or Workshop Item (Paper)

Abstract

Extracting a singing voice from its music accompaniment can significantly facilitate certain applications of Music Information Retrieval including singer identification and singing melody extraction. In this paper, we present a hybrid approach for this purpose, which combines properties of the Azimuth Discrimination and Resynthesis (ADRess) method with Independent Component Analysis (ICA). Our proposed approach is developed specifically for the case of singing voice separation from stereophonic recordings. The paper presents the characteristics of the proposed method and details an objective evaluation of its effectiveness.

Full text not available from this repository.

More information

Published date: 28 June 2010
Additional Information: ISSN: 1520-6149
Venue - Dates: IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), United States, 2010-06-28

Identifiers

Local EPrints ID: 181931
URI: http://eprints.soton.ac.uk/id/eprint/181931
ISBN: 9781424442959
PURE UUID: 84f9c770-2df1-47e1-81cc-f12124783548

Catalogue record

Date deposited: 26 Apr 2011 10:25
Last modified: 18 Jul 2017 11:58

Export record

Altmetrics

Contributors

Author: S. Sofianos
Author: A. Ariyaeeinia
Author: R. Polfreman

University divisions

Download statistics

Downloads from ePrints over the past year. Other digital versions may also be available to download e.g. from the publisher's website.

View more statistics

Atom RSS 1.0 RSS 2.0

Contact ePrints Soton: eprints@soton.ac.uk

ePrints Soton supports OAI 2.0 with a base URL of http://eprints.soton.ac.uk/cgi/oai2

This repository has been built using EPrints software, developed at the University of Southampton, but available to everyone to use.

We use cookies to ensure that we give you the best experience on our website. If you continue without changing your settings, we will assume that you are happy to receive cookies on the University of Southampton website.

×