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Towards automatic music recommendation for audio branding scenarios

Herzog, Martin; Lepa, Steffen; Egermann, Hauke

Within the MIR community, most prediction models of musical impact on listeners focus on mood or emotional effects (perceived or induced). The ABC_DJ project investigates the associative impact of music on listeners from the specific perspective of music branding that surrounds us in our everyday lives. We pre-sent a general concept for applying automatic music rec-ommendation within this domain. Creating a scientifically validated basic terminology for communicating brand at-tributes and human emotions in this field is the key chal-lenge. As a first result, we introduce the Music Branding Expert Terminology (MBET), a comprehensive terminology of verbal attributes used in music branding, upon which a pre-diction model will be developed to facilitate automatic mu-sic recommendation in the context of music branding.
Published in: ISMIR 2016, August 7-11, New York City, USA / LBD contributions,