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Martin Herzog

Lupe [1]


  • Room: H 3001 A
  • Consultation hours: appointment via mail
  • Phone: +49 (0)30 314-29093 
  • Mail: herzog [at] tu-berlin.de




born in Berlin, Germany, August 20th 
Study of Computer Science at Humboldt University Berlin (Diploma 2011)
Freelance web developer
Student worker at ]init[ AG for Digital Communication
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


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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