Please use this identifier to cite or link to this item:
https://dl.ucsc.cmb.ac.lk/jspui/handle/123456789/3685
Full metadata record
DC Field | Value | Language |
---|---|---|
dc.thesis.supervisor | Caldera, H. A. | - |
dc.contributor.author | Nanayakkara, C. V. | - |
dc.date.accessioned | 2016-09-08T11:28:33Z | - |
dc.date.available | 2016-09-08T11:28:33Z | - |
dc.date.issued | 2016-09-08 | - |
dc.identifier.uri | http://hdl.handle.net/123456789/3685 | - |
dc.description.abstract | Existence 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.iso | en | en_US |
dc.title | Prediction of Emotion Stimulated by Music | en_US |
dc.type | Thesis | en_US |
Appears in Collections: | 2009/2010 BIT Undergraduate thesis |
Files in This Item:
File | Description | Size | Format | |
---|---|---|---|---|
Final Thesis_11001984.pdf Restricted Access | 3 MB | Adobe PDF | View/Open Request a copy |
Items in UCSC Digital Library are protected by copyright, with all rights reserved, unless otherwise indicated.