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/).