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Martin Herzog
[1]
- © privat
Contact
- Room: H 3001 A
- Consultation hours: appointment via mail
- Phone: +49 (0)30 314-29093
- Mail: herzog [at] tu-berlin.de
[2]
Vita
1984 | born in
Berlin, Germany, August 20th |
2004-2011 | Study of Computer Science at
Humboldt University Berlin (Diploma 2011) |
2006-2008 | Freelance web
developer |
2010-2011 | Student worker at ]init[ AG
for Digital Communication |
2011 | Diploma thesis: „Harmony
Analysis of MIDI Data as a Basis for the Extraction of Harmonic
High-Level-Features“ |
since 2011 | Consultant at ]init[ AG for
Digital Communication |
since
2016 | Research associate at TU Berlin Current project: ABC_DJ [3] (Artist-to-Business-to-Business-to-Consumer Audio Branding System) PhD project: Predicting Musical Meaning from High-Level Music Features |
PhD Project
Predicting Musical Meaning from High-Level Music Features
What is the link between musical content on one hand and perceived musical meaning on the other?
In my PhD project I investigate the question which features – derived from music theory – play an important role in predicting perceived musical meaning. Using data from a large-scale lsitening experiment, I aim to develop a Multilevel Linear Regression Model for the prediction of perceived semantics in popular music.
Supervisors: Prof. Dr. Stefan Weinzierl (TU Berlin), Dr. Hauke Egermann (University of York, UK)
Research Interests
- Music perception and processing
- Music and emotion
- Music information retrieval
- Audio branding
Publications
Herzog, M., Lepa, S., Steffens, J., Schönrock, A. & Egermann, H. (2017): Predicting musical meaning in audio branding scenarios. [4] Proceedings of the 25th Anniversary Conference of the European Society for Cognitive Science of Music, Ghent, Belgium, 2017
Steffens, J., Lepa, S., Egermann, H., Schönrock, A. & Herzog, M. (2017): Entwicklung eines Systems zur automatischen Musikempfehlung im Kontext des Audio Brandings. [5] In: Fortschritte der Akustik: Tagungsband d. 43. DAGA. Deutsche Gesellschaft für Akustik, 2017
Herzog, M., Lepa, S. & Egermann, H. (2016): Towards automatic music recommendation for audio branding scenarios. [6] Proceedings of the ISMIR 2016 conference, New York, USA, 2016
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