dc.contributor.author | SANDLER, MB | en_US |
dc.contributor.author | quinton, E | en_US |
dc.contributor.author | o'hanlon, K | en_US |
dc.contributor.author | dixon, S | en_US |
dc.contributor.author | DMRN+11: Digital Music Research Network One-day Workshop 2016 | en_US |
dc.date.accessioned | 2017-02-10T16:20:14Z | |
dc.date.available | 2016-12-20 | en_US |
dc.date.issued | 2016-12-20 | en_US |
dc.date.submitted | 2017-02-10T11:58:37.230Z | |
dc.identifier.uri | http://qmro.qmul.ac.uk/xmlui/handle/123456789/19348 | |
dc.description.abstract | Meter inference algorithms are typically designed to track metrical structure in presence of mild deviations of the feature estimates over time in order to account for performance imprecisions, expressive timing or musical effects such as accelerando. Abrupt changes of metrical structure over time are comparatively rarely addressed. In this paper, we present an unsupervised approach to detect metrical structure changes. Formulating the problem as a metrical structure based segmentation retrieval task, we present a variant of sparse Non-negative Matrix Factorisation (NMF) and demonstrate state of the art performance. | en_US |
dc.publisher | Centre for Digital Music, Queen Mary University of London | en_US |
dc.title | Automatic Detection of Metrical Structure Changes | en_US |
dc.type | Conference Proceeding | |
dc.rights.holder | © Centre for Digital Music, Queen Mary University of London | |
pubs.notes | Not known | en_US |
pubs.publication-status | Published | en_US |
pubs.publisher-url | https://qmro.qmul.ac.uk/xmlui/handle/123456789/19345 | en_US |
dcterms.dateAccepted | 2016-12-20 | en_US |