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School of Electronic Engineering and Computer Science

Alexander Williams



Project title: User-driven deep music generation in digital audio workstations

Abstract: The project will investigate AI-based music production assistive techniques that integrate seamlessly to user workflows in digital audio workstations and offer flexible editing control. Interviews with musicians will be conducted to identify creative affordances desired by users. The knowledge gained will inform the design of deep learning models that can be constrained based on high-level user controls and domain-specific knowledge. Several computational music creativity tasks will be considered including music inpainting (continuation of a musical composition in context) and harmonisation. Previous work on piano inpainting will be extended to small ensembles (e.g. jazz trio). Training will combine symbolic and audio datasets by developing models yielding suitable mid-level representations 


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