Music Informatics


Please visit the member's personal pages for current research activities and opportunities for final theses (Abschlussarbeiten).


CI Methods for Music Information Retrieval

  • Optimization of music classification chain
  • Intelligent feature selection methods
  • Learning of personal music categories
  • Fuzzy methods using high-level feature analysis

Development of AMUSE (Advanced MUSic Explorer)

  • Java open source framework for different MIR tasks
  • Multi-tool extendable environment with shared interfaces and data interchange formats
  • Algorithm evaluation and optimization methods

Music Test Database

For the evaluation of music classification tasks we use a database of 120 commercial music albums purchased for our research group. The CDs are distributed among 6 AllMusicGuide genres:

Classic Electronica Jazz Pop/Rock R&B Rap
CD number 15 15 15 45 15 15

  • Test set OS120 (optimization set for experiments, with focus on evolutionary multi-objective feature selection)
  • Test set TS120 (song-independent test set from the same albums as OS120 for the evaluation of optimized models)
  • Test set TAS120 (artist-independent test set with the same genre distribution)

The following audio features are used for classification (for definitions and the difference between low-level and high-level features see

Instrument Sample Database

Currently, the following instrument samples are used for the experiments on instrument recognition:


Completed Project Groups

Completed Diploma Theses

  • Michael Deppner: Aktuelle Ansätze für Musikempfehlungssysteme. February 2011.
    Advisors: Jannach, Vatolkin.
  • Verena Mattern: Ableitung Partitur-basierter Merkmale aus Audiosignaldaten. October 2010.
    Advisors: Rudolph, Vatolkin.
  • Thorsten Deinert: Tempoerkennung aus Audiosignalen langsamer Musikstücke. October 2010.
    Advisors: Rudolph, Vatolkin.
  • Tobias Hein: Erkennung musikalischer Sequenzen mit selbstorganisierenden Karten. April 2010.
    Advisors: Rudolph, Kramer.
  • Bernd Schmidt: Vorhersage emotionaler Auswirkungen von Musik anhand signalbasierter Merkmale. September 2008.
    Advisors: Rudolph, Vatolkin.
  • Roman Klinger: Automatische Komposition von Musik mit Methoden der Computational Intelligence. June 2006.
    Advisors: Rudolph, Hildebrand.

Completed Bachelor Theses

  • Christian Büscher: Abbildung von Musiksignaldaten auf n-Gramme moderater Größe. September 2011.
    Advisors: Rudolph, Vatolkin.
  • Fabian Bock: Automatische Harmonisierung populärer Melodien. September 2013.
    Advisors: Rudolph, Vatolkin.
  • Boris Arnaud Fosso Ngounou: Auswahl und Mischung von Musikstücken zur Erzeugung von Medleys.
    Advisors: Rudolph, Vatolkin.

Completed Seminar

  • Kreative Algorithmen (WS 2009/10)
  • Aktuelle Forschungsgebiete der Musikdatenanalyse (WS 2008/09)
  • Computational Intelligence und Musikinformatik (SS 2008)
  • Musikinformatik (SS 2007)

Supplementary Material

GECCO 2011

Last modified: 2023-03-16 13:29 by Fabian Ostermann