Key estimation in electronic dance music

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• dc.contributor.author Faraldo Pérez, Ángelca
• dc.contributor.author Gómez Gutiérrez, Emilia, 1975-ca
• dc.contributor.author Jordà Puig, Sergica
• dc.contributor.author Herrera Boyer, Perfecto, 1964-ca
• dc.date.accessioned 2017-10-23T09:13:45Z
• dc.date.available 2017-10-23T09:13:45Z
• dc.date.issued 2016
• dc.description Comunicació presentada a la 38th European Conference on IR Research (ECIR 2016), celebrada els dies 20 a 23 de març de 2016 a Pàdua, Itàlia.
• dc.description.abstract In this paper we study key estimation in electronic dance music, an umbrella term referring to a variety of electronic music subgenres intended for dancing at nightclubs and raves. We start by defining notions of tonality and key before outlining the basic architecture of a template-based key estimation method. Then, we report on the tonal characteristics of electronic dance music, in order to infer possible modifications of the method described. We create new key profiles combining these observations with corpus analysis, and add two pre-processing stages to the basic algorithm. We conclude by comparing our profiles to existing ones, and testing our modifications on independent datasets of pop and electronic dance music, observing interesting improvements in the performance or our algorithms, and suggesting paths for future research.en
• dc.description.sponsorship This research has been partially supported by the EU-funded GiantSteps project (FP7-ICT-2013-10. Grant agreement number 610591).
• dc.format.mimetype application/pdfca
• dc.identifier.citation Faraldo Á, Gómez E, Jordà S, Herrera P. Key estimation in electronic dance music. In: Ferro N, Crestani F, Moens M-F, Mothe J, Silvestri F, Di Nunzio GM, Hauff C, Silvello G, editors. Advances in Information Retrieval. 38th European Conference on IR Research, ECIR 2016; 2016 Mar 20-23; Padua, Italy. [New York City]: Springer; 2016. p. 335-47. DOI: 10.1007/978-3-319-30671-1_25
• dc.identifier.doi http://dx.doi.org/10.1007/978-3-319-30671-1_25
• dc.identifier.uri http://hdl.handle.net/10230/33060
• dc.language.iso eng
• dc.publisher Springerca
• dc.relation.ispartof Ferro N, Crestani F, Moens M-F, Mothe J, Silvestri F, Di Nunzio GM, Hauff C, Silvello G, editors. Advances in Information Retrieval. 38th European Conference on IR Research, ECIR 2016; 2016 Mar 20-23; Padua, Italy. [New York City]: Springer; 2016. p. 335-47.
• dc.relation.projectID info:eu-repo/grantAgreement/EC/FP7/610591
• dc.rights © Springer The final publication is available at Springer via http://dx.doi.org/10.1007/978-3-319-30671-1_25.
• dc.rights.accessRights info:eu-repo/semantics/openAccess
• dc.subject.keyword Music information retrievalen
• dc.subject.keyword Computational key estimationen
• dc.subject.keyword Key profilesen
• dc.subject.keyword Electronic dance musicen
• dc.subject.keyword Tonalityen
• dc.subject.keyword Music theoryen
• dc.title Key estimation in electronic dance musicca
• dc.type info:eu-repo/semantics/conferenceObject
• dc.type.version info:eu-repo/semantics/acceptedVersion