Abstract
The dominant approach in the research area of Music Information Retrieval (MIR) for audio signals has been to characterize musical content information using overall statistics over time-frequency representations such as the “classic” Mel-Frequency Cepstral Coefficients (MFCC). Although this approach has yielded impressive results in various applications including genre classification, similarity retrieval and music browsing it seems to have reached a plateau. In this talk I will describe the efforts of my research group at the University of Victoria to go beyond this “classic” approach in two main directions: 1) extracting and analyzing specific “types” of sound sources from audio music mixtures 2) connecting MIR techniques with the process of music creation, production, and performance. In addition I will describe in more detail two specific projects: 1) formulating dominant melody separation from polyphonic audio using perceptually-informed cues as a graph partitioning problem 2) a system for capturing and analyzing indian sitar performance for interaction with a robotic drummer.
Biography
George Tzanetakis is an assistant Professor of Computer Science (also cross-listed in Music and Electrical and Computer Engineering) at the University of Victoria, Canada. He received his PhD degree in Computer Science from Princeton Uiversity in May 2002 was a PostDoctoral Fellow at Carnegie Mellon University working on query-by-humming systems with Prof. Dannenberg and on video retrieval with the Informedia group.
His research deals with all stages of audio content analysis such as feature extraction, segmentation, classification with specific focus on Music Information Retrieval (MIR). His pioneering work on musical genre classification is frequently cited and received an IEEE Signal Processing Society Young Author Award in 2004. He is the principal designer and developer of the Marsyas open source audio processing frameworkwhich has been used for MIR projects both in academia and industry.
He has presented tutorials on MIR and audio feature extraction at several international conferences. He is also an active musician and has studied saxophone performance, music theory and composition. More information can be found at http://www.cs.uvic.ca/~gtzan.
