Sunday 27 November 2022, 2pm
With the explosion in music technologies offering 'artificial intelligence', artists and musicians are exploring original and meaningful ways to adapt them to creative ends -- often in ways that critique their underlying assumptions. In this series of two concerts showcasing leading artist-researchers experimenting with AI and complex systems models — attached to the European Research Council-funded project Music and AI: Building Critical Interdisciplinary Studies — computational systems will be used to explore themes of agency and performative creativity, and to find new ways to control spatialisation, compose algorithmic patterns, and respond to bodily gesture. The performances will be followed by open Q & A and discussion with the artists about how and why they are using AI/machine learning.
- Anna Xambo
- P.A. Tremblay and Owen Green
- Feedback Cell featuring Ollie Bown
Anna Xambó is an experimental electronic music producer and researcher. Biased for being passionate about extreme digital minimalism and a past performer on bass guitar, she likes to explore the boundaries of digital sound focusing on low frequencies, compulsive rhythms, and noisy textures. Her research and practice concentrate on creating sound and music computing systems looking at novel approaches to collaborative, participatory, and live coding experiences. She is currently a Senior Lecturer in Music and Audio Technology as well as a member of the Music, Technology and Innovation - Institute of Sonic Creativity (MTI2) at De Montfort University.
Seasoned improvisers Owen Green and Pierre Alexandre Tremblay will play, dance and maybe fight with artificial agents in their first public musicking ever (despite having worked together almost symbiotically on the Fluid Corpus Manipulation project for the last 5 years).
Owen Green is an improviser, composer, performer, and systems-maker. He does unspeakable things with cardboard and machine listening technologies, as well as more speakable things alongside other humans, such as John Bowers and the groups RawGreenRust (with Jules Rawlinson and Dave Murray Rust) and Sileni (with Ali Maloney). Owen has worked as a Research Fellow in Creative Coding at the University of Huddersfield on the Fluid Corpus Manipulation project, which aims to help other people do things with machine listening.
Pierre Alexandre Tremblay (Montréal, 1975) is a composer and performer on bass guitar and electronic devices, in solo and group settings, between electroacoustic music, contemporary jazz, mixed music and improvised music. He also worked in popular music, and practises creative coding. His music is available on empreintes DIGITALes.
He is currently Professor of Composition and Improvisation at the University of Huddersfield (England, UK). He likes spending time with his family, reading prose, and going on long walks. As a founding member of the no-tv collective, he does not own a working television set.
Feedback Cell is the open-ended experimental luthiary and performance project of Chris Kiefer and Alice Eldridge. The project develops Feedback Musicianship through iteratively making, playing, measuring, and thinking about feedback resonator instruments. Following the design of the Halldorophone by Halldór Ulfarsson, feedback cellos are made from acoustic cellos that are custom fitted with pick-ups, built-in speakers and on-body transducers and analogue and digital processing, to create hybrid instruments that self-resonate.
For this improvisation two self-resonating feedback celli are coupled via audio and adaptive machine listening and learning algorithms to create a shared, self-willed instrument. Learning to play the instrument becomes a lesson in complexity literacy and intersubjective attunement. In this one-off performance they are joined by Ollie Bown, bringing a further complex system to the feedback loop: a continuous-time recurrent neural network that has been evolved to generate complex patterns via a process of "novelty search". The trio explore hybrid complex adaptive musical systems, intuitively.
