Please use this identifier to cite or link to this item: https://dl.ucsc.cmb.ac.lk/jspui/handle/123456789/3685
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dc.thesis.supervisorCaldera, H. A.-
dc.contributor.authorNanayakkara, C. V.-
dc.date.accessioned2016-09-08T11:28:33Z-
dc.date.available2016-09-08T11:28:33Z-
dc.date.issued2016-09-08-
dc.identifier.urihttp://hdl.handle.net/123456789/3685-
dc.description.abstractExistence of a mechanism for predicting musically induced emotions is of value to the music therapy domain, while being a study of considerable interest. Despite numerous studies having been conducted in this area, certain limitations as the lack of a music specific emotion model has direly affected the conclusions of those studies. This research has focused on creation of a music specific emotion model, whereas an array of experiments have been conducted to realize a fair music emotion prediction model. The best prediction model was realized to be audio feature based music emotion prediction incorporating oversampling and Random Forest algorithm.en_US
dc.language.isoenen_US
dc.titlePrediction of Emotion Stimulated by Musicen_US
dc.typeThesisen_US
Appears in Collections:2009/2010 BIT Undergraduate thesis

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