Department of Computer Science Series of Publications A Report A-2016-1 Cover Song Identification Using Compression-based Distance Measures Teppo E. Ahonen To be presented, with the permission of the Faculty of Science of the University of Helsinki, for public criticism in Audito- rium CK112, Exactum, Gustaf H¨allstr¨omin katu 2b, on April 1st, 2016, at twelve o’clock noon. University of Helsinki Finland Supervisors Kjell Lemstr¨om,University of Helsinki, Finland Esko Ukkonen, University of Helsinki, Finland Pre-examiners Juan Pablo Bello, New York University, USA Olli Yli-Harja, Tampere University of Technology, Finland Opponent Petri Toiviainen, University of Jyv¨askyl¨a, Finland Custos Esko Ukkonen, University of Helsinki, Finland Contact information Department of Computer Science P.O. Box 68 (Gustaf H¨allstr¨omin katu 2b) FI-00014 University of Helsinki Finland Email address:
[email protected].fi URL: http://cs.helsinki.fi/ Telephone: +358 2941 911, telefax: +358 9 876 4314 Copyright c 2016 Teppo E. Ahonen ISSN 1238-8645 ISBN 978-951-51-2025-0 (paperback) ISBN 978-951-51-2026-7 (PDF) Computing Reviews (1998) Classification: H.3.3, E.4, J.5, H.5.5 Helsinki 2016 Unigrafia Cover Song Identification Using Compression-based Distance Measures Teppo E. Ahonen Department of Computer Science P.O. Box 68, FI-00014 University of Helsinki, Finland
[email protected].fi PhD Thesis, Series of Publications A, Report A-2016-1 Helsinki, March 2016, 122+25 pages ISSN 1238-8645 ISBN 978-951-51-2025-0 (paperback) ISBN 978-951-51-2026-7 (PDF) Abstract Measuring similarity in music data is a problem with various potential applications.