Musico: personal playlists through peripheral and implicit interaction

While listening to music has been a part of everyday life for ages, access to unlimited numbers of songs has never been as ubiquitous as it has become with the introduction of streaming services and mobile Internet access. However, creating and updating playlists suitable for different everyday contexts is a tedious activity, which can lead to a decrease in music listening experience. This paper presents the design of Musico, a tangible music player which combines peripheral and implicit interaction. The user's input of skipping and repeating songs is to feed a learning algorithm which autonomously generates and updates personalized playlists based on individual's preferences while requiring minimal effort from the user. Additionally, different playlists are to be generated for different everyday contexts (such as having dinner or studying). As such, Musico aims to merge peripheral (tangible) user input and system intelligence to optimize user experience.