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Abstract
In this talk, I will present the development of Clastic Music, a set of musical pieces where I play with the geological concept of a clast: new entities and forms created out of pre-existing fragments. Clastic Music is the result of rhythmic explorations using a machine learning-assisted approach to music-making. To create these rhythmic clasts, I designed a software device that can learn models from small-size datasets of drum patterns and embed them into rhythmic latent spaces. To facilitate the exploration of the models, the device provides a visualizer that generates a dynamic representation of the latent spaces and is based directly on the pulsing rhythmic patterns encoded in the models. Clastic Music was premiered live at the MUTEK festival in Montréal and was packaged as a web-based release, where visuals are rendered in real time on the browser and depend on user and sound input.
Biography
Gabriel Vigliensoni is an electronic music artist, performer, and researcher whose work interrogates the various stages of contemporary music production’s workflow by developing and investigating state-of-the-art and experimental techniques for music-making. He holds a Ph.D. in Music Technology from McGill University and is currently a postdoctoral research fellow in the Department of Computing at Goldsmiths University of London and a visiting researcher at University of the Arts London’s Creative Computing Institute, where he is investigating the creative capabilities and affordances of the machine learning paradigm for assisting musical composition.