Lizzie Wilson Research Page

Lizzie Wilson is currently studying a PhD as part of the Media & Arts Technology centre for doctoral training and part of the Centre for Digital Music and Cognitive Science research groups at Queen Mary, University of London.

Research

Co-creation strategies for human-machine collaboration have been explored in various creative disciplines. Recent developments in music technology and artificial intelligence have made these creative interactions applicable to the domain of computer music, meaning it is now possible to interface with algorithms as creative partners. The application of computational creativity research is beginning to be incorporated within the context of live algorithmic music known as live coding. However, as music is inherently coupled with affective response, it is crucial for any artificial musical intelligence system to consider how to incorporate emotional meaning into collaborative musical actions. This work will look at bestowing machine musicians within interactive live coding systems the ability to create affective musical collaborations and examine new ways of interfacing with musical algorithms.

Talks

Algorithmic Art Assembly, SF: Algorithms, Music and Machines (video available on request)

Papers and Posters

[Paper] Collaborative human and machine creative interaction driven through affective response in live coding systems - Elizabeth Wilson

[Poster] FlowLissajous An environment for *meta* live code performance - Elizabeth Wilson and Andrew Thompson

Press

  • [[Remix]] Sampler as a Time Machine
  • FACT mag -- Sonic Futures
  • CYCLING 74 -- On The Road: The Algorithmic Art Assembly
  • Audio Commons -- Unspoken Word
  • ARS Electronica Festival 2018 - Unspoken Word
  • Workshops

  • Masterclass in Live Coding Music @ Sound & Music
  • Music Hackspace Online Workshop 2-Part Series, Creating Music and Visuals with Code
  • Northern Sound Collective Hackathon
  • Introduction to Live Coding Music with Gibber @ V & A Friday Late
  • Introduction to Live Coding Music with Tidal Cycles @ Intersections