In my sound art work I explore concrete materials and textures uncovering their innate patterns and inherent properties through close miccing and amplification. My work is inspired by musique concrete, working with fragments of sound and recordings that are taken out from their context (acousmatic sound) and manipulated electronically to create new thoughts, spaces and worlds. Space and sound are inherently linked and in my exploration of sound sculpture through this sample based approach, I like to consider how both playing with material physical form and reconfiguring sound fragments can create space for new sonic forms of expression and meaning. I have always loved working with sound collage, randomness and chance occurrences through graphical scores and am now starting to work these out as systems (slowly) through maths and code.
I’m fascinated with the idea of a hidden sound world waiting to be revealed and uncovered and that sound phenomena though not always immediately present are held within spaces that need to be tuned into on a different frequency as listeners or activated and unlocked in a different way, unleashing their potential. Sound is the movement of particles through space, as such we as humans are in a perpetual flow state and relational dynamic with sound sources and material environments, sound is determined by space and we experience this phenomena in a deeply personal manner through proximity and individual resonance.
I’m reading a lot about machine learning at the moment, teaching myself to code with Python and MaxMSP for a new year long residency I’m doing with NOVARS, Centre for Innovation in Sound at the University of Manchester, part of European Art Science network for Digital Culture. I’m exploring machine learning and musique concrete for performance and composition. My research question is “How can concrete materials and neural networks project future sonic realities?”. I’m creating training datasets of concrete sounds to process through generative neural networks and will be creating new sound sculptures for live processing. Themes of hidden systems and processes are evident within machine learning writing which are often referred to as a ‘blackbox’ or thought about as some sort of dark art especially with the huge amount of neural network layers required within deep learning. This level of computation and statistical modelling is impossible for humans to process and understand. It is early on in my machine learning skills development but conceptually I am interested in how using neural networks and concrete sounds could question the idea of an object and how we perceive matter, thinking about Walter Benjamin’s Aura of an object, also how these experiments of sounds in latent space could pose new sonic aesthetics. You can see the framework set out for the AURAMACHINE residency here in a recent talk at ZKM, the project is part of a wider AI research project i’ve been working on called SleepStates.
GLASS EXPERIMENTS THIS WEEK
This week I have been experimenting with developing some 3D virtual textures, creating glass textures and marrying them with some glass samples from my MATERIALITY project a couple of years back. The sound on the piece above is me rummaging through a vat of glass shards at the National Glass Centre in Sunderland, you can hear the low hum of the machinery on the audio, which is left untreated. I’m testing how it feels to consider and combine material as a form of 3D digital materiality with an acoustic recording of the same matter . Working in an online space, i’m going to start testing panning and spatial parameters to explore how these objects use the spaces within our screens.