Impact of user context on song selection

Authors:
Olufisayo Omojokun;Michael Genovese;Charles Isbell, Jr.
Affiliations:
Georgia Tech University, Atlanta, GA, USA;Georgia Tech University, Atlanta, GA, USA;Georgia Tech University, Atlanta, GA, USA
Venue:
MM '08 Proceedings of the 16th ACM international conference on Multimedia
Year:
2008

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Abstract

The rise of digital music has led to a parallel rise in the need to manage music collections of several thousands of songs on a single device. Manual selection of songs for a music listening experience is a cumbersome task. In this paper, we present an initial exploration of the feasibility of using song signal properties and user context information to assist in automatic song selection. Users listened to music over the course of a month while their context and song selections were tracked. Initial results suggest the use of context information can improve automated song selection when patterns are learned for each individual.