Freitag, 9. Oktober 2020 | Friday, October 9, 2020
18:20–19:00 Discussion (w/ Roshanak Kheshti)
A new generation of software tools claiming to use artificial intelligence and machine learning have emerged in recent years in the production of popular music. These tools are based less on an aesthetic or cognitive understanding of music or musical practices than on the processing of data – big data. The data-driven tools thus reflect the ways in which software designers define and think about music differently from musicians and sound engineers. This paper will examine how new approaches to sound mixing and mastering raise questions about the increasing role of data-based AI applications not only in music production but in consumption as well.Paul Théberge
is a Canada Research Professor, cross appointed to the Institute for Comparative Studies in Literature, Art and Culture and to the School for Studies in Art and Culture (Music), at Carleton University, Ottawa. Théberge has published widely on issues concerning music, technology and culture, and is author of Any Sound You Can Imagine: Making Music / Consuming Technology
(Wesleyan, 1997), and co-editor of Living Stereo: Histories and Cultures of Multichannel Sound
(Bloomsbury Academic, 2015). In 2012, he produced and engineered a set of experimental recordings from the Glenn Gould archive – Glenn Gould: The Acoustic Orchestrations – for Sony Classical.