dc.contributor.author |
Tissera, Lahiru |
|
dc.date.accessioned |
2024-04-30T07:02:05Z |
|
dc.date.available |
2024-04-30T07:02:05Z |
|
dc.date.issued |
2023 |
|
dc.identifier.citation |
Tissera, Lahiru (2023) MoodifyLK: Sinhala Music Emotion Classification Based on Deep Learning. BSc. Dissertation, Informatics Institute of Technology |
en_US |
dc.identifier.issn |
20191277 |
|
dc.identifier.uri |
http://dlib.iit.ac.lk/xmlui/handle/123456789/2104 |
|
dc.description.abstract |
"In the Sri Lankan context, the classification of Sinhala songs has received limited attention from researchers. Manually classifying music resources can be a tedious and labor-
intensive task. Applying neural networks to the music classification process is a highly
explored machine learning domain. However, compared to the main domain, this sub-
domain is underexplored due to the changing nature of music and a lack of interest in this
area. With the emergence of new technologies in the field of machine learning and the
discovery of new sub-domains of music classification, there is still much to explore in this
field." |
en_US |
dc.language.iso |
en |
en_US |
dc.subject |
Deep Learning |
en_US |
dc.subject |
Machine Learning |
en_US |
dc.subject |
Music emotion classification systems |
en_US |
dc.title |
MoodifyLK: Sinhala Music Emotion Classification Based on Deep Learning |
en_US |
dc.type |
Thesis |
en_US |