ABSTRACT
Human interacted computational systems have evolved from simple robots to state-of-the-art systems that perform extremely complicated tasks such as teaching, training, technical support, analysis and many others. The increased involvement of artificial intelligence and machine learning has led to this tremendous growth over the past few decades. The analysis of domains where this evolution has occurred is staggering. It has also spread widely and deeply in the domain of music. New applications such as Spotify and Yousician have taken this to an entirely new level. This chapter explores the development of the state of the art in human interacted computation systems in the area of music with a particular emphasis on the design of recommender systems.
