Uploaded June 2019 | Updated September 2026, 1 week ago

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Owen Green discusses his attempts to avoid modelling musical time by pushing audio descriptors to their limits via creative coding at the first FluCoMa plenary

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The first FluCoMa plenary saw the eight creative coders involved in the early testing and refinement of the FluCoMa toolboxes, as well as two external specialists and the project team, come together for three days of discussion, brainstorming, and critical engagement with the FluCoMa project. As a part of this, each participant was asked to present an element of their techno-fluent practice in depth: a recent creative technological usage that would be inspiring, clever, and subversive.


/// CREDITS

Video camera operator: Andie Brown, James Bradbury, Jacob Hart, and Sam Gillies
Video edited by Jacob Hart and Sam Gillies
Audio edited by Pierre Alexandre Tremblay
FluCoMa video bumper by Angela Guyton

Recorded September 20-22, 2018, University of Huddersfield


/// BIOGRAPHY

Owen is Research Fellow in Creative Coding on the FluCoMa project, funded by the European Research Council. Owen ia active in a number of groups, including RawGreenRust, with Jules Rawlinson and Dave Murray-Rust; Sileni, with Ali Maloney; and Grey Area, with Sean Williams, Emma Lloyd, Shiori Usui, Nikki Moran, Armin Sturm and Dave Murray-Rust.


/// FluCoMa

The Fluid Corpus Manipulation project (FluCoMA) instigates new musical ways of exploiting ever-growing banks of sound and gestures within the digital composition process, by bringing breakthroughs of signal decomposition DSP and machine learning to the toolset of techno-fluent computer composers, creative coders and digital artists.

These potent algorithms are currently partially available in closed bespoke software, or in laboratories, but not at a suitable level of modularity within the main coding environments used by the creative researchers, namely Max, Pd and SuperCollider, to allow groundbreaking sonic research into a rich unexploited area: the manipulation of large sound corpora. Indeed, with access to, genesis of, and storage of large sound banks now commonplace, novel ways of abstracting and manipulating them are needed to mine their inherent potential.

FluCoMa proposes to tackle this issue by empowering techno-fluent aesthetic researchers with a toolset for signal decomposition, and one for machine learning, as well as support material, in order to experiment with new sound and gesture design untapped in large corpora from within their high-level creative coding workflow. Three degrees of manipulations are set to be explored: (1) expressive browsing and descriptor-based taxonomy, (2) remixing, component replacement, and hybridisation by concatenation, and (3) pattern recognition at component level, with interpolating and variation-making potential. These novel manipulations will yield new sounds, new musical ideas, and new approaches to large corpora.

As with previous HISS projects, FluCoMa will deliver its findings open source, in the form of software (standalone and extensions) with extensive documentation and examples, as well as the underlying libraries in C++. Moreover, musical works commissioned to challenge these new methodologies will be released, through concerts and plenaries on surrounding subjects, and documented in academic papers. A users forum will also be at the centre of this emerging research community.

FluCoMa is based within the Department of Music and Music Technology, with its Centre for Research in New Music, on the Queensgate Campus of the University of Huddersfield. This project has received funding from the European Union's Horizon 2020 research and innovation programme under grant agreement No 725899.