Lecturer: Bob L.T. Sturm, associate professor of computer science at KTH, Stockholm
”I will discuss my engineering and creative work in building and collaborating with “musical” machine learning systems. Such fancy statistical machines can engage or they can impede. While they are always “on", ready to suggest output, they may not always be helpful.
What’s worse: such machines can provide innumerable possibilities and automate away the banal. Or are those good things? Sometimes the most interesting musical opportunities arise when the machine crashes – which is contrary to the goal of engineering away failure.
I will discuss in particular my work reconciling the origin of a particular music machine with the source of its data, and how I have ended up using it to write folk tunes about our dog.
Bob L. T. Sturm has degrees in physics, music, multimedia, and engineering, and specializes in signal processing and machine learning applied to music data. Sturm is the PI of the project "MUSAiC (Music at the Frontiers of Artificial Creativity and Criticism) ERC Consolidator grant (No. 864189).” More information: https://www.kth.se/profile/bobs
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