Towards automatic music recommendation for audio branding scenarios
Research output: Contribution to conference › Paper › peer-review
Conference | 17th International Society for Music Information Retrieval Conference, |
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Abbreviated title | ISMIR |
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Country/Territory | United States |
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City | New York |
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Conference date(s) | 7/08/16 → 11/08/16 |
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Date | Published - 2016 |
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Number of pages | 3 |
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Original language | English |
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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.
Project: Research project (funded) › Research
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