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Basser Seminar Series

Computational Methods for Analysis and Generation of Musical Rhythm Timelines

Godfried Toussaint
School of Computer Science, McGill University

Wednesday 13 April 2005, 2-3pm

Basser Conference Room (Madsen Room G92)

Abstract

Computational methods for the analysis and generation of rhythm timelines are described. Mathematical measures of rhythm preference are compared. Several methods for representing rhythm, and for measuring rhythm similarity, are reviewed. Tools from bioinformatics are used to perform phylogenetic analyses of families of rhythms that are common in African and Afro-American music. Several computational open problems related to the problems mentioned above as well as the "reconstruction" of "ancestral" rhythms are outlined.

Speaker's biography

Godfried T. Toussaint received the B.Sc. degree from the University of Tulsa, in Tulsa, Oklahoma, U.S.A. and the M.A.Sc. and Ph.D. degrees from the University of British Columbia, Vancouver, B.C., Canada in 1968, 1970, and 1972, respectively, all in Electrical Engineering.

Since 1972 he has been teaching and doing research in the School of Computer Science at McGill University in the areas of information theory, pattern recognition, and computational geometry. Godfried Toussaint has been Visiting Scholar / Researcher / Professor at a wide variety of research institutions, such as Stanford University, University of Montreal, University of Amsterdam or the Universidad Politecnica de Madrid. In the fall of 1995 he was a Vice-Chancellor's Research Best Practice Fellow at the University of Newcastle, Australia.

Dr. Toussaint is Associate Editor of Computational Geometry: Theory and Applications, Associate Editor of the International Journal of Computational Geometry and Applications and Associate Editor of The Visual Computer. He is also on the Editorial Boards of the journals Discrete & Computational Geometry and Forma as well as on the Advisory Board of the IEEE Transactions on Pattern Analysis and Machine Intelligence. He is a member of several learned societies including the Pattern Recognition Society and the New York Academy of Sciences.