A personality-based adaptive system for visualizing classical music performances

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• dc.contributor.author Schedl, Markusca
• dc.contributor.author Melenhorst, Markca
• dc.contributor.author Liem, Cynthia C. S.ca
• dc.contributor.author Martorell Domínguez, Agustínca
• dc.contributor.author Mayor, Oscarca
• dc.contributor.author Tkalčič, Markoca
• dc.date.accessioned 2018-02-21T11:54:48Z
• dc.date.available 2018-02-21T11:54:48Z
• dc.date.issued 2016
• dc.description.abstract To enhance the experience of listening to classical orchestra music, either in the concert hall or at home, we present a personalized system that integrates three visualization/interaction concepts: Score Follower (points to the current position in the score), Orchestra Layout (illustrates instruments that are currently playing and their dynamics), and Structure Visualization (visualizes structural elements such as themes or motifs). Motivated by previous literature that found evidence for connections between personality and music consumption and preference, we first assessed in a user study to which extent personality traits and music visualization preferences correlate. Measuring preference via pragmatic quality and personality traits according to the Big Five Inventory (BFI) questionnaire, we found substantial interconnections between them. These translate into rules relating certain personality traits (e.g., extraversion or agreeableness) to preference rankings of the visualizations. In the proposed personality-based system, users are grouped into four clusters according to their answers to the most significant personality questions determined in the study. The order of the visualizations for a given user is adapted with respect to the ranking preferred by other users in the same cluster. Evaluation of the system was carried out by a second user study that showed a significantly higher normalized discounted cumulative gain (NDCG) for the personalized system in comparison to a system with randomized order of the visualizations.
• dc.description.sponsorship This work is supported by the EU FP7-ICT-2011-9 project 601166 (“PHENICX”) and the Austrian Science Fund (FWF): P25655.
• dc.format.mimetype application/pdf
• dc.identifier.citation Schedl M, Melenhorst M, Liem CCS, Martorell A, Mayor Ó, Tkalčič M. A personality-based adaptive system for visualizing classical music performances. In: Proceedings of the 7th International Conference on Multimedia Systems (MMSys'16); 2016 May 10-13; Klagenfurt, Austria. New York (NY): ACM; 2016. p. 157-63. DOI: 10.1145/2910017.2910604
• dc.identifier.doi http://dx.doi.org/10.1145/2910017.2910604
• dc.identifier.isbn 978-1-4503-4297-1
• dc.identifier.uri http://hdl.handle.net/10230/33955
• dc.language.iso eng
• dc.publisher ACM Association for Computer Machineryca
• dc.relation.ispartof Proceedings of the 7th International Conference on Multimedia Systems (MMSys'16); 2016 May 10-13; Klagenfurt, Austria. New York (NY): ACM; 2016.
• dc.relation.projectID info:eu-repo/grantAgreement/EC/FP7/601166
• dc.rights © 2016 Association for Computing Machinery
• dc.rights.accessRights info:eu-repo/semantics/openAccess
• dc.subject.keyword Music visualization
• dc.subject.keyword Recommender systems
• dc.subject.keyword Personality
• dc.title A personality-based adaptive system for visualizing classical music performancesca
• dc.type info:eu-repo/semantics/conferenceObject
• dc.type.version info:eu-repo/semantics/acceptedVersion