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School of Electronic Engineering and Computer Science


Project title: Probabilistic learning of sequential structures in music cognition 

Theme affiliation: Music Cognition 

Abstract: Current computational models for how we perceive, and experience music are incomplete and are not empirically mapped onto the neural substrates by which people differentially translate complex auditory inputs into meaningful behaviours and experiences based on their unique previous musical exposures. Comprehensive AI models for how people perform this task are highly valuable because they can help us pinpoint precise neural and psychological aetiologies of complex aesthetic and emotional responses to a deeply personal and universally shared auditory phenomenon. The main goal of the project is to develop a fully representative computational model of music cognition. 


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