Composition-aware music recommendation system for music production
Music recommender systems (MRSs) have to date primarily focused on song or playlist recommendation for listening purposes, but much less work has been done on the recommendation of audio content for music production. Contemporary music production tools commonly include large digital audio libraries of loops (repeatable musical parts typically used in grid-based music), virtual instrument samples (based on synthesis or recordings) and sound packs (collections of sounds). Such richness of content can however impede creativity as it can be daunting for musicians to navigate tens of thousands of sounds to find items matching the style of their production and intent.
This PhD will research, develop and assess composition-aware music recommendation systems for music production enabling musicians get the best musical value out of their creative digital audio libraries.
C4DM theme affiliation:
Music Informatics, Audio Engineering, Sonic Interaction Design