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Promoting unfamiliar music through data science

Mars, the music affect recommender system for digital library engagement

Bibliographic Data

ID10278576
AuthorsDaryl Bainbridge (0000-0002-0603-5728, David Bainbridge, School of Computing and Mathematical Sciences, University of Waikato, Hamilton, Private Bag 3105, New Zealand. Email: [email protected].), Roger T Dean (0000-0002-8859-8902, Roger T. Dean, MARCS Institute for Brain, Behaviour and Development, Music Science Group, Western Sydney University, Locked Bag 1757, Penrith, NSW 2751, Australia. Email: [email protected].)
Year2025
Volume58
Issue6
Pages1-9
Publication date2025-03-31
Peer ReviewedYes
Open AccessNo
TypeARTICLE
VenueLeonardo (JOURNAL)
Journal identifiersISSN: 0024-094X • E-ISSN: 1530-9282
PublisherMIT Press (PUBLISHER • US)
DOI10.1162/leon_a_02705
OpenAlexW4409011549
LanguageEN
References cited2

This article describes a personal music recommender system designed to overcome the ‘cold start’ problem that affects the visibility of recent works of composition and improvisation outside popular music. The approach builds upon our experimental results that showed increased levels of engagement by subjects with unfamiliar music through a focus on acoustic properties and emotional response. Set in the context of a digital music library, the developed recommender component provides two visual acoustic representations of the piece, and additionally allows users to record their own continuous affect responses. These interface elements are designed to invoke the behaviours observed in our experiments, meaning visitors stay engaged with the online resource for longer and so experience a broader range of music

Affect (linguistics) · Art · Astrobiology · Biology · Data science · Mars Exploration Program · Recommender system · Visual arts · World Wide Web · Communication · Computer Science · Music and Audio Processing · Music Technology and Sound Studies · Psychology

  • Influence of a continuous affect ratings task on listening time for unfamiliar art music

    John R Taylor, Roger T Dean•Journal of New Music Research•2021

  • A circumplex model of affect

    James A Russell•Journal of Personality and Social…•1980

Citation velocityhistorical
Highly citedNo

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