| 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 |