Contrastive Self-supervised learning for music
Organization
Computational Music Analysis and Recommendation
Abstract
Contrastive learning is very promising for music because it doesn't require labels. Or doesn't it? Still, we need categories that would define the contrast - albums, artists, genres, instruments. This thesis is an exploratory work to find which contrastive learning scheme works best for taste profiles prediction.
Graduation Theses defence year
2022-2023
Supervisor
Anna Aljanaki
Spoken language (s)
Estonian, English
Requirements for candidates
Level
Bachelor, Masters
Keywords
Application of contact
Name
Anna Aljanaki
Phone
E-mail