Assistive Model to Generate Chord Progressions Using Genetic Programming with Artificial Immune Properties

UDC.coleccionInvestigaciónes_ES
UDC.departamentoHumanidadeses_ES
UDC.journalTitleApplied Scienceses_ES
UDC.startPage6039es_ES
UDC.volume10es_ES
dc.contributor.authorNavarro-Cáceres, María
dc.contributor.authorMerchán Sánchez-Jara, Javier Félix
dc.contributor.authorLeithardt, Valderi R. Q.
dc.contributor.authorGarcía-Ovejero, Raúl
dc.date.accessioned2024-09-30T09:20:33Z
dc.date.available2024-09-30T09:20:33Z
dc.date.issued2020-08
dc.description.abstract[Abstract] InWestern tonal music, tension in chord progressions plays an important role in defining the path that a musical composition should follow. The creation of chord progressions that reflects such tension profiles can be challenging for novice composers, as it depends on many subjective factors, and also is regulated by multiple theoretical principles. This work presents ChordAIS-Gen, a tool to assist the users to generate chord progressions that comply with a concrete tension profile. We propose an objective measure capable of capturing the tension profile of a chord progression according to different tonal music parameters, namely, consonance, hierarchical tension, voice leading and perceptual distance. This measure is optimized into a Genetic Program algorithm mixed with an Artificial Immune System called Opt-aiNet. Opt-aiNet is capable of finding multiple optima in parallel, resulting in multiple candidate solutions for the next chord in a sequence. To validate the objective function, we performed a listening test to evaluate the perceptual quality of the candidate solutions proposed by our system. Most listeners rated the chord progressions proposed by ChordAIS-Gen as better candidates than the progressions discarded. Thus, we propose to use the objective values as a proxy for the perceptual evaluation of chord progressions and compare the performance of ChordAIS-Gen with chord progressions generators. es_ES
dc.identifier.citationNavarro-Cáceres, M.; Merchán Sánchez-Jara, J.F.; Reis Quietinho Leithardt, V.; García-Ovejero, R. Assistive Model to Generate Chord Progressions Using Genetic Programming with Artificial Immune Properties. Appl. Sci. 2020, 10, 6039. https://doi.org/10.3390/app10176039es_ES
dc.identifier.urihttp://hdl.handle.net/2183/39273
dc.language.isoenges_ES
dc.publisherMDPIes_ES
dc.relation.urihttps://doi.org/10.3390/app10176039es_ES
dc.rightsAtribución 3.0 Españaes_ES
dc.rights.accessRightsopen accesses_ES
dc.rights.urihttp://creativecommons.org/licenses/by/3.0/es/*
dc.subjectChord progressiones_ES
dc.subjectTonal tensiones_ES
dc.subjectTonal interval spacees_ES
dc.subjectArtificial immune systemses_ES
dc.subjectGenetic programminges_ES
dc.titleAssistive Model to Generate Chord Progressions Using Genetic Programming with Artificial Immune Propertieses_ES
dc.typejournal articlees_ES
dspace.entity.typePublication
relation.isAuthorOfPublication0cc821b0-890a-48a1-97af-f5b0fa846913
relation.isAuthorOfPublication.latestForDiscovery0cc821b0-890a-48a1-97af-f5b0fa846913

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