dc.contributor.author | Panteli, M | en_US |
dc.contributor.author | Benetos, E | en_US |
dc.contributor.author | Dixon, S | en_US |
dc.date.accessioned | 2018-01-11T10:36:36Z | |
dc.date.available | 2017-11-26 | en_US |
dc.date.issued | 2017-12-18 | en_US |
dc.date.submitted | 2017-12-19T12:09:31.444Z | |
dc.identifier.issn | 1932-6203 | en_US |
dc.identifier.other | e0189399 | |
dc.identifier.other | e0189399 | |
dc.identifier.other | ARTN e0189399 | en_US |
dc.identifier.other | ARTN e0189399 | en_US |
dc.identifier.uri | http://qmro.qmul.ac.uk/xmlui/handle/123456789/31245 | |
dc.description.sponsorship | EB is supported by a RAEng Research Fellowship (RF/128) from the Royal Academy of Engineering (http://raeng.org.uk/). MP is supported by a Principal’s research studentship from Queen Mary University of London (http://qmul.ac.uk). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript. | en_US |
dc.relation.ispartof | PLOS ONE | en_US |
dc.rights | This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. | |
dc.title | A computational study on outliers in world music | en_US |
dc.type | Article | |
dc.rights.holder | Copyright: © 2017 Panteli et al. | |
dc.identifier.doi | 10.1371/journal.pone.0189399 | en_US |
pubs.author-url | http://gateway.webofknowledge.com/gateway/Gateway.cgi?GWVersion=2&SrcApp=PARTNER_APP&SrcAuth=LinksAMR&KeyUT=WOS:000418389500025&DestLinkType=FullRecord&DestApp=ALL_WOS&UsrCustomerID=612ae0d773dcbdba3046f6df545e9f6a | en_US |
pubs.issue | 12 | en_US |
pubs.notes | No embargo | en_US |
pubs.notes | Paper is open access with a CC-BY license | en_US |
pubs.publication-status | Published | en_US |
pubs.volume | 12 | en_US |
qmul.funder | A Machine Learning Framework for Audio Analysis and Retrieval::Royal Academy of Engineering | en_US |
qmul.funder | A Machine Learning Framework for Audio Analysis and Retrieval::Royal Academy of Engineering | en_US |