Computational Music Analysis ― Algorithms, Applications and Methodologies

This book gives a balanced, coherent overview of current computational approaches to music analysis. It includes chapters by leading researchers that, collectively, give an exciting picture of the diversity and depth of the field. The approaches represented include methods of analysis based on information theory, geometric pattern matching, wavelets, string algorithmics and statistical learning. Methods are described based on a variety of well-established theories of musical structure and music perception.

David Meredith is an Associate Professor in the Dept. of Architecture, Design and Media Technology at Aalborg University. He has Bachelor's and Master's degrees in natural sciences and music from the University of Cambridge and a D.Phil. from the Faculty of Music of the University of Oxford. His research focuses on algorithms for analysing musical structure. He developed the first practical algorithms for discovering repeated patterns in polyphonic music and the most accurate pitch spelling algorithm to date. He is the lead investigator at Aalborg University on the EU collaborate project, "Learning to Create" (Lrn2Cre8).