Personalized affective music player

J.H. Janssen, E.L. Broek, van den, J.H.D.M. Westerink

Research output: Chapter in Book/Report/Conference proceedingConference contributionAcademicpeer-review

18 Citations (Scopus)
4 Downloads (Pure)

Abstract

We introduce and test an affective music player (AMP) that selects music for mood enhancement. Through a concise overview of content, construct, and ecological validity, we elaborate five considerations that form the foundation of the AMP. Based on these considerations, computational models are developed, using regression and kernel density estimation. We show how these models can be used for music selection and how they can be extended to fit in other systems. Subsequently, the success of the models is illustrated with a user test. The AMP augments music listening, where its techniques, in general, enable automated affect guidance. Finally, we argue that our AMP is readily applicable to real-world situations as it can 1) cope with noisy situations, 2) handle the large inter-individual differences apparent in the musical domain, and 3) integrate context or other information, all in real-time.
Original languageEnglish
Title of host publicationProceedings of the 3rd International IEEE Conference on Affective Computing and Intelligent Interaction (ACII), September 10-12, 2009
Place of PublicationAmsterdam
PublisherInstitute of Electrical and Electronics Engineers
Pages472-477
ISBN (Print)978-1-4244-4799-2
Publication statusPublished - 2009
Event2009 International IEEE Conference on Affective Computing and Intelligent Interaction -
Duration: 10 Sep 200912 Sep 2009

Conference

Conference2009 International IEEE Conference on Affective Computing and Intelligent Interaction
Period10/09/0912/09/09
Other3rd International IEEE Conference on Affective Computing and Intelligent Interaction

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