Machine listening: Applications of AI to Music

Andrea Goetzke, Gene Kogan This talk examines present and future
impacts of machine learning applied to music, with a focus on
understanding and using machine learning in the music making
process. AI researchers are rapidly proposing new applications at
every stage of the musical process. On the creative side, bots and
intelligent assistants help musicians fluidly manage their own
compositional tools and sound libraries. Also, novel musical
instruments imbued with smart sensors and circuits greatly lower
the barrier of entry to production and performance, expanding the
ways we interface with our instruments. And enabling richer and
more direct interaction between musicians and their fans as well.
Experimental techniques for synthesizing audio and imitating styles
on-demand are still in their infancy, but could one day
revolutionize production and composition from the ground up. On the
curatorial and business side, music recommender systems are
beginning to scan the "long tail" of large music collections and
automatically make accurate inferences about who is likely to
listen to or buy those songs. As algorithms invade every aspect of
the music creation process, we are asked to reconsider what it
means to be a musician in the 21st century. The talk is hosted by
Music Pool Berlin (https://musicpoolberlin.net/).