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dc.contributor.author Iñesta, José M.
dc.contributor.author Conklin, Darrell
dc.contributor.author Ramírez, Rafael,1966-
dc.date.accessioned 2021-02-05T07:17:02Z
dc.date.available 2021-02-05T07:17:02Z
dc.date.issued 2016
dc.identifier.citation Iñesta JM, Conklin D, Ramírez R. Machine learning and music generation. Journal of Mathematics and Music: Mathematical and Computational Approaches to Music Theory, Analysis, Composition and Performance. 2016 Oct 17;10(2):87-91. DOI: 10.1080/17459737.2016.1216369
dc.identifier.issn 1745-9737
dc.identifier.uri http://hdl.handle.net/10230/46353
dc.description.sponsorship We guest editors acknowledge the financial support of the following funding sources: the Ministerio de Economía y Competitividad project TIMuL [No. TIN2013–48152–C2–1–R]; [No. TIN2013–48152–C2–2–R, supported by UE FEDER funds]; the project Lrn2Cre8, which is funded by the Future and Emerging Technologies (FET) programme within the Seventh Framework Programme for Research of the European Commission [FET grant number 610859]; the European Union Horizon 2020 research and innovation programme [grant agreement number 688269].
dc.format.mimetype application/pdf
dc.language.iso eng
dc.publisher Taylor & Francis
dc.relation.ispartof Journal of Mathematics and Music: Mathematical and Computational Approaches to Music Theory, Analysis, Composition and Performance. 2016 Oct 17;10(2):87-91
dc.rights © This is an Accepted Manuscript of an article published by Taylor & Francis in Journal of Mathematics and Music: Mathematical and Computational Approaches to Music Theory, Analysis, Composition and Performance on 2016 Oct 17, available online: http://www.tandfonline.com/10.1080/17459737.2016.1216369
dc.title Machine learning and music generation
dc.type info:eu-repo/semantics/article
dc.identifier.doi http://dx.doi.org/10.1080/17459737.2016.1216369
dc.relation.projectID info:eu-repo/grantAgreement/ES/1PE/TIN2013-48152-C2-1-R
dc.relation.projectID info:eu-repo/grantAgreement/ES/1PE/TIN2013-48152-C2-2-R
dc.relation.projectID info:eu-repo/grantAgreement/EC/FP7/610859
dc.relation.projectID info:eu-repo/grantAgreement/EC/H2020/688269
dc.rights.accessRights info:eu-repo/semantics/openAccess
dc.type.version info:eu-repo/semantics/acceptedVersion

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