Sonic Writing: Technologies of Material, Symbolic and Signal Inscriptions
In this lecture I present resent research that explores how contemporary music technologies trace their ancestry to previous forms of instruments and media. I will look at how new digital music technologies trace their origins in traditional instrument design, musical notation, and sound recording. The scope will range from ancient Greek music theory, medieval notation, early modern scientific instrumentation to contemporary multimedia and artificial intelligence.
I will point to a bespoke affinity and similarity between current musical practices and those from before the advent of notation and recording, stressing the importance of instrument design in the study of new music and projecting how new computational technologies, including machine learning, will transform our musical practices.
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Thor Magnusson is a Professor in Future Music at the University of Sussex. His work focusses on the impact digital technologies have on musical creativity and practice, explored equally through practice (software development, composition and performance) and theory (academic publications, lecturing, talks) . He is the co-founder of ixi audio (www.ixi-audio.net), and has developed audio software, systems of generative music composition, written computer music tutorials and created two musical live coding environments. He has taught workshops in creative music coding and sound installations, and given presentations, performances and visiting lectures at diverse art institutions, conservatories, and universities internationally.
In 2019, Bloomsbury Academic published Magnusson’s monograph Sonic Writing: The Technologies of Material, Symbolic and Signal Inscriptions. The book explores how contemporary music technologies trace their ancestry to previous forms of instruments and media, including symbolic musical notation. The book underpins his research in creative AI, where, as part of the MIMIC project (www.mimicproject.com), Magnusson has worked on a system that enables users to design their own live coding languages for machine learning.
Further information here: http://thormagnusson.github.io