The complexity of music is a challenging but also a very interesting property that has apparent connections with aesthetics and preference. It therefore has a lot of potential for applications in the music information retrieval context. In this talk we will first shed some light on what music complexity is and what it can tell us. We will then present several computational approaches to its estimation.
These approaches target a naive notion of complexity resembling a "common sense" understanding. They address individual facets focusing on acoustics, timbre, tonality, and rhythm. Finally, we will briefly review different evaluation methods for testing the usefulness of the developed algorithms.
Dr. Sebastian Streich graduated from Ilmenau Technical University (Germany) in 2002 earning his engineering diploma in Media Technology. After his graduation he worked on music metadata extraction as a research engineer at the Fraunhofer Institute under Prof. Karlheinz Brandenburg. In 2003 he enrolled in the PhD program of Computer Science and Digital Communication at Pompeu Fabra University in Barcelona (Spain).
There he conducted research on music complexity analysis in Prof. Xavier Serra's Music Technology Group. Upon the submission of his PhD thesis in the end of 2006, Dr. Streich joined Yamaha Corporation in Hamamatsu (Japan), where he is currently working as a researcher in digital music analysis for interactive systems.
