Performance-based interpreter identification in saxophone audio recordings

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• dc.contributor.author Ramírez, Rafael,1966-ca
• dc.contributor.author Maestre Gómez, Estebanca
• dc.contributor.author Pertusa, Antonioca
• dc.contributor.author Gómez Gutiérrez, Emilia, 1975-ca
• dc.contributor.author Serra, Xavierca
• dc.date.accessioned 2018-03-08T08:16:16Z
• dc.date.available 2018-03-08T08:16:16Z
• dc.date.issued 2007
• dc.description.abstract We propose a novel approach to the task of identifying performers from their playing styles. We investigate how skilled musicians (Jazz saxophone players in particular) express and communicate their view of the musical and emotional content of musical pieces and how to use this information in order to automatically identify performers. We study deviations of parameters such as pitch, timing, amplitude and timbre both at an inter-note level and at an intra-note level. Our approach to performer identification consists of establishing a performer dependent mapping of inter-note features (essentially a "score" whether or not the score physically exists) to a repertoire of inflections characterized by intra-note features. We present a successful performer identification case study.
• dc.description.sponsorship This work was supported in part by the Spanish Ministry of Education and Science under Grants TINC2003-07776-C02-01 ProMusic Project and TIN2006-14932-C02-01 ProSeMus Project.
• dc.format.mimetype application/pdf
• dc.identifier.citation Ramirez R, Maestre E, Pertusa A, Gómez E, Serra X. Performance-based interpreter identification in saxophone audio recordings. In: IEEE Trans Circuits Syst Video Technol. 2007;17(3):356-64. DOI: 10.1109/TCSVT.2007.890862
• dc.identifier.doi http://dx.doi.org/10.1109/TCSVT.2007.890862
• dc.identifier.issn 1558-2205
• dc.identifier.uri http://hdl.handle.net/10230/34065
• dc.language.iso eng
• dc.publisher Institute of Electrical and Electronics Engineers (IEEE)ca
• dc.relation.ispartof IEEE transactions on circuits and systems for video technology. 2007;17(3):356-64.
• dc.relation.projectID info:eu-repo/grantAgreement/ES/1PN/TINC2003-07776-C02-01
• dc.relation.projectID info:eu-repo/grantAgreement/ES/2PN/TIN2006-14932-C02-01
• dc.rights © 2007 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works. The final published article can be found at http://ieeexplore.ieee.org/document/4118245/
• dc.rights.accessRights info:eu-repo/semantics/openAccess
• dc.subject.keyword Artificial intelligence
• dc.subject.keyword Audio recordings
• dc.subject.keyword Music
• dc.subject.keyword Signal processing
• dc.title Performance-based interpreter identification in saxophone audio recordingsca
• dc.type info:eu-repo/semantics/article
• dc.type.version info:eu-repo/semantics/acceptedVersion