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Main Title: Towards automatic music recommendation for audio branding scenarios
Author(s): Herzog, Martin
Lepa, Steffen
Egermann, Hauke
Type: Conference Object
Abstract: 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.
Subject(s): audio branding
music branding
music features
Issue Date: 2016
Date Available: 13-Jul-2017
Language Code: en
DDC Class: 003 Systeme
Sponsor/Funder: EC/H2020/688122/EU/Artist-to-Business-to-Business-to-Consumer Audio Branding System/ABC DJ
Proceedings Title: ISMIR 2016, August 7-11, New York City, USA / LBD contributions
TU Affiliation(s): Fak. 1 Geistes- und Bildungswissenschaften » Inst. Sprache und Kommunikation » FG Audiokommunikation
Appears in Collections:Technische Universit├Ąt Berlin » Publications

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