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dc.contributor.authorNavarro Cáceres, María 
dc.contributor.authorCaetano, Marcelo
dc.contributor.authorBernardes, Gilberto
dc.contributor.authorSánchez Barba, Mercedes 
dc.contributor.authorMerchán Sánchez Jara, Javier Félix 
dc.date.accessioned2026-01-19T08:31:53Z
dc.date.available2026-01-19T08:31:53Z
dc.date.issued2020
dc.identifier.citationNavarro-Cáceres, M.; Caetano, M.; Bernardes, G.; Sánchez-Barba, M.; Merchán Sánchez-Jara, J. A Computational Model of Tonal Tension Profile of Chord Progressions in the Tonal Interval Space. Entropy 2020, 22, 1291. https://doi.org/10.3390/e22111291es_ES
dc.identifier.urihttp://hdl.handle.net/10366/168955
dc.description.abstract[EN]In tonal music, musical tension is strongly associated with musical expression, particularly with expectations and emotions. Most listeners are able to perceive musical tension subjectively, yet musical tension is difficult to be measured objectively, as it is connected with musical parameters such as rhythm, dynamics, melody, harmony, and timbre. Musical tension specifically associated with melodic and harmonic motion is called tonal tension. In this article, we are interested in perceived changes of tonal tension over time for chord progressions, dubbed tonal tension profiles. We propose an objective measure capable of capturing tension profile according to different tonal music parameters, namely, tonal distance, dissonance, voice leading, and hierarchical tension. We performed two experiments to validate the proposed model of tonal tension profile and compared against Lerdahl’s model and MorpheuS across 12 chord progressions. Our results show that the considered four tonal parameters contribute differently to the perception of tonal tension. In our model, their relative importance adopts the following weights, summing to unity: dissonance (0.402), hierarchical tension (0.246), tonal distance (0.202), and voice leading (0.193). The assumption that listeners perceive global changes in tonal tension as prototypical profiles is strongly suggested in our results, which outperform the state-of-the-art models.es_ES
dc.format.mimetypeapplication/pdf
dc.language.isoenges_ES
dc.publisherMDPIes_ES
dc.rightsAttribution-NonCommercial-NoDerivatives 4.0 Internacional*
dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/4.0/*
dc.subjectMusices_ES
dc.subjectBioinspired algorithmses_ES
dc.subjectTonal Modeles_ES
dc.titleA Computational Model of Tonal Tension Profile of Chord Progressions in the Tonal Interval Spacees_ES
dc.typeinfo:eu-repo/semantics/articlees_ES
dc.relation.publishversionhttps://doi.org/10.3390/e22111291es_ES
dc.subject.unesco1203 Ciencia de los ordenadoreses_ES
dc.subject.unesco6203.06 Música, Musicologíaes_ES
dc.identifier.doi10.3390/E22111291
dc.rights.accessRightsinfo:eu-repo/semantics/openAccesses_ES
dc.identifier.essn1099-4300
dc.journal.titleEntropyes_ES
dc.volume.number22es_ES
dc.issue.number11es_ES
dc.page.initial1291es_ES
dc.type.hasVersioninfo:eu-repo/semantics/publishedVersiones_ES


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