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A Real-time feedback learning tool to visualize sound quality in violin performances

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dc.contributor.author Giraldo, Sergio
dc.contributor.author Ramírez, Rafael,1966-
dc.contributor.author Waddell, George
dc.contributor.author Williamon, Aaron
dc.date.accessioned 2019-12-19T09:35:53Z
dc.date.available 2019-12-19T09:35:53Z
dc.date.issued 2017
dc.identifier.citation Giraldo S, Ramirez R, Waddell G, Williamon A. A Real-time feedback learning tool to visualize sound quality in violin performances. In: Ramirez R, Conklin D, Iñesta JM, editors. 10th International Workshop on Machine Learning and Music; 2017 Oct 6; Barcelona, Spain. Barcelona: MML; 2017. p. 19-24.
dc.identifier.uri http://hdl.handle.net/10230/43210
dc.description Comunicació presentada a: 10th International Workshop on Machine Learning and Music (MML), celebrat a Barcelona (Espanya), el 6 d'octubre de 2017.
dc.description.abstract The assessment of the sound properties of a performed mu- sical note has been widely studied in the past. Although a consensus exist on what is a good or a bad musical performance, there is not a formal de nition of performance tone quality due to its subjectivity. In this study we present a computational approach for the automatic assess- ment of violin sound production. We investigate the correlations among extracted features from audio performances and the perceptual quality of violin sounds rated by listeners using machine learning techniques. The obtained models are used for implementing a real-time feedback learning system.
dc.description.sponsorship This work has been partly sponsored by the Spanish TIN project TIMUL (TIN2013-48152-C2-2-R), the European Union Horizon 2020 research and inno- vation programme under grant agreement No. 688269 (TELMI project), and the Spanish Ministry of Economy and Competitiveness under the Maria de Maeztu Units of Excellence Programme (MDM-2015-0502).
dc.format.mimetype application/pdf
dc.language.iso eng
dc.publisher Machine Learning and Music (MML)
dc.relation.ispartof Ramirez R, Conklin D, Iñesta JM, editors. 10th International Workshop on Machine Learning and Music; 2017 Oct 6; Barcelona, Spain. Barcelona: MML; 2017.
dc.rights The Authors. CC BY-NC 4.0. Reconocimiento-No comercial 4.0 Internacional
dc.rights.uri https://creativecommons.org/licenses/by-nc/4.0/
dc.title A Real-time feedback learning tool to visualize sound quality in violin performances
dc.type info:eu-repo/semantics/conferenceObject
dc.subject.keyword Machine learning
dc.subject.keyword Violin sound quality
dc.subject.keyword Automatic assessment
dc.subject.keyword Timbre dimensions
dc.subject.keyword Audio features
dc.relation.projectID info:eu-repo/grantAgreement/EC/H2020/688269
dc.relation.projectID info:eu-repo/grantAgreement/ES/1PE/TIN2013-48152-C2-2-R
dc.rights.accessRights info:eu-repo/semantics/openAccess
dc.type.version info:eu-repo/semantics/publishedVersion

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