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MoodifyLK: Sinhala Music Emotion Classification Based on Deep Learning

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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


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