Optimization of music classification chain
Intelligent feature selection methods
Learning of personal music categories
Fuzzy methods using high-level feature analysis
Java open source framework for different MIR tasks
Multi-tool extendable environment with shared interfaces and data interchange formats
Algorithm evaluation and optimization methods
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 (used as optimization set for optimization experiments)
Test set TS120 (used as independent test set for optimization experiments)
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.
Kreative Algorithmen (WS 2009/10)
Aktuelle Forschungsgebiete der Musikdatenanalyse (WS 2008/09)
Computational Intelligence und Musikinformatik (SS 2008)
Musikinformatik (SS 2007)