Projects

The MusAI program is composed of 10 research projects, designed to be complementary, which take place over five years

Two projects (‘Sonic-Social Genre’ and ‘Interdisciplinary Interventions in the Design of Music Recommender Systems’) are radically interdisciplinary; each stages experimental collaborations between computer scientists and scholars from the social sciences and humanities with the aim of transcending current disciplinary limits and introducing novel approaches to AI.

The final project (‘Prototyping Radically Interdisciplinary Music AI Pedagogies’) translates the findings of the earlier research projects into experiments in new kinds of AI training and public outreach through music.

WP1a: Music Recommender Systems and the Development of Aesthetic Experience

WP1b: Sonic-Social Genre: Towards Multimodal Computational Music Genre Modelling

WP2a: Cultural Economies of Adaptive and Affective Music AI

WP2b: Commercial Generative Music: A Practice-Based Study of AI Music Production

WP3a: Critical Interdisciplinarity: Musician-Engineer Collaboration in Music AI Research

WP3b: Automating Signal Processing, Automating Aesthetic Labour and Decision-Making

WP3c: Permeable Interdisciplinary: Algorithmic Composition, Subverted

WP4a: ‘Localising’ Recommendation: Serving Middle Eastern Listeners and Music

WP4b: Interdisciplinary Interventions in the Design of Music Recommender Systems

WP5: Prototyping Radically Interdisciplinary Music AI Pedagogies