The Pursuit Of Happiness In Music: Retrieving Valence With Contextual Music Descriptors

dc.creatorFornari J.
dc.creatorEerola T.
dc.date2009
dc.date2015-06-26T13:36:30Z
dc.date2015-11-26T15:36:33Z
dc.date2015-06-26T13:36:30Z
dc.date2015-11-26T15:36:33Z
dc.date.accessioned2018-03-28T22:45:03Z
dc.date.available2018-03-28T22:45:03Z
dc.identifier364202517X; 9783642025174
dc.identifierLecture Notes In Computer Science (including Subseries Lecture Notes In Artificial Intelligence And Lecture Notes In Bioinformatics). , v. 5493 LNCS, n. , p. 119 - 133, 2009.
dc.identifier3029743
dc.identifier10.1007/978-3-642-02518-1_8
dc.identifierhttp://www.scopus.com/inward/record.url?eid=2-s2.0-68749111173&partnerID=40&md5=851f82ed2b03ac3612f33dd9d884605c
dc.identifierhttp://www.repositorio.unicamp.br/handle/REPOSIP/92562
dc.identifierhttp://repositorio.unicamp.br/jspui/handle/REPOSIP/92562
dc.identifier2-s2.0-68749111173
dc.identifier.urihttp://repositorioslatinoamericanos.uchile.cl/handle/2250/1263465
dc.descriptionIn the study of music emotions, Valence is usually referred to as one of the dimensions of the circumplex model of emotions that describes music appraisal of happiness, whose scale goes from sad to happy. Nevertheless, related literature shows that Valence is known as being particularly difficult to be predicted by a computational model. As Valence is a contextual music feature, it is assumed here that its prediction should also require contextual music descriptors in its predicting model. This work describes the usage of eight contextual (also known as higher-level) descriptors, previously developed by us, to calculate happiness in music. Each of these descriptors was independently tested using the correlation coefficient of its prediction with the mean rating of Valence, reckoned by thirty-five listeners, over a piece of music. Following, a linear model using this eight descriptors was created and the result of its prediction, for the same piece of music, is described and compared with two other computational models from the literature, designed for the dynamic prediction of music emotion. Finally it is proposed here an initial investigation on the effects of expressive performance and musical structure on the prediction of Valence. Our descriptors are then separated in two groups: performance and structural, where, with each group, we built a linear model. The prediction of Valence given by these two models, over two other pieces of music, are here compared with the correspondent listeners' mean rating of Valence, and the achieved results are depicted, described and discussed. © 2009 Springer Berlin Heidelberg.
dc.description5493 LNCS
dc.description
dc.description119
dc.description133
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dc.languageen
dc.publisher
dc.relationLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
dc.rightsfechado
dc.sourceScopus
dc.titleThe Pursuit Of Happiness In Music: Retrieving Valence With Contextual Music Descriptors
dc.typeActas de congresos


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