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JamSketch: improvisation support system with GA-based melody creation from user’s drawing

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dc.contributor.author Kitahara, Tetsuro
dc.contributor.author Giraldo, Sergio
dc.contributor.author Ramírez, Rafael,1966-
dc.date.accessioned 2021-02-05T07:17:22Z
dc.date.available 2021-02-05T07:17:22Z
dc.date.issued 2017
dc.identifier.citation Kitahara T, Giraldo S, Ramírez R. JamSketch: improvisation support system with GA-based melody creation from user’s drawing. In: Aramaki M, Davies MEP, Kronland-Martinet R, Ystad S, editors. Music Technology with swing. 13th International Symposium, CMMR; 2017 Sep 25-28; Matosinhos, Portugal. Berlin: Springer; 2017. p. 509-21. (LNCS ; no. 11265). DOI: 10.1007/978-3-030-01692-0_34
dc.identifier.uri http://hdl.handle.net/10230/46355
dc.description Comunicació presentada al 13th International Symposium (CMMR), celebrat del 25 al 28 de setembre de 2017 a Matosinhos, Portugal.
dc.description.abstract Improvisation is an enjoyable form of music performance but requires advanced skills and knowledge of music because the player has to create melodies immediately during the performance. To support improvisations by people without skills or knowledge of music, we have to develop (1) a human interface that can be used without skills or knowledge of music and (2) automatic melody generation from the user’s input that may be musically abstract or incomplete. In this paper, we develop an improvisation support system based on melodic outlines, which represent the overall contour of melodies, with a function of melody generation using a genetic algorithm (GA). Once the user draws a melodic outline on the piano-roll display with the mouse or touch screen, the system immediately generates a melody using a GA with a fitness function based on the similarity to the outline, an N-gram probability, and entropy. The generated melody is performed expressively based on expression parameters calculated with an machine learning approach. The results of listening tests for comparing human performances and the system’s performances suggest that generated melodies have quality similar to performances by non-expert human performers.
dc.description.sponsorship This work was supported by JSPS KAKENHI Grant Numbers 26240025, 26280089, 16K16180, 16H01744, 16KT0136, and 17H00749 as well as by the Spanish TIMuL Project (TIN2013-48152-C2-2-R), and the TELMI Project of the Horizon 2020 Research and Innovation Programme (grant agreement No. 688269).
dc.format.mimetype application/pdf
dc.language.iso eng
dc.publisher Springer
dc.relation.ispartof Aramaki M, Davies MEP, Kronland-Martinet R, Ystad S, editors. Music Technology with swing. 13th International Symposium, CMMR; 2017 Sep 25-28; Matosinhos, Portugal. Berlin: Springer; 2017. p. 509-21. (LNCS ; no. 11265)
dc.rights © Springer The final publication is available at Springer via http://dx.doi.org/10.1007/978-3-030-01692-0_34
dc.title JamSketch: improvisation support system with GA-based melody creation from user’s drawing
dc.type info:eu-repo/semantics/conferenceObject
dc.identifier.doi http://dx.doi.org/10.1007/978-3-030-01692-0_34
dc.subject.keyword Improvisation
dc.subject.keyword Melodic outline
dc.subject.keyword Melody generation
dc.subject.keyword Algorithmic composition
dc.subject.keyword Genetic algorithm
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/acceptedVersion

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