Full Product Details
Author: Peter Knees ,
Markus Schedl
Publisher: Springer-Verlag Berlin and Heidelberg GmbH & Co. KG
Imprint: Springer-Verlag Berlin and Heidelberg GmbH & Co. K
Edition: 1st ed. 2016
Volume: 36
Dimensions:
Width: 15.50cm
, Height: 1.90cm
, Length: 23.50cm
Weight: 6.033kg
ISBN: 9783662497203
ISBN 10: 3662497204
Pages: 299
Publication Date: 03 June 2016
Audience:
College/higher education
,
Undergraduate
,
Postgraduate, Research & Scholarly
Format: Hardback
Publisher's Status: Active
Availability: Manufactured on demand
We will order this item for you from a manufactured on demand supplier.
Reviews
“Knees and Schedl’s book on Music similarity and retrieval differs from other books on the topic in that the authors have focused on music rather than acoustical signal processing, adding several cultural- and listener-centric aspects thereby rendering a holistic view. As a result, we find not only methods working on musical characteristics retrieved from the audio signal, but also techniques working on characteristics obtained from contextual information … Although not a textbook, I would definitely recommend it as handy reference material for music researchers, postgraduate students, and teachers of music or musicology.” (Soubhik Chakraborty, Computing Reviews, February, 2017)
Knees and Schedl's book on Music similarity and retrieval differs from other books on the topic in that the authors have focused on music rather than acoustical signal processing, adding several cultural- and listener-centric aspects thereby rendering a holistic view. As a result, we find not only methods working on musical characteristics retrieved from the audio signal, but also techniques working on characteristics obtained from contextual information ... Although not a textbook, I would definitely recommend it as handy reference material for music researchers, postgraduate students, and teachers of music or musicology. (Soubhik Chakraborty, Computing Reviews, February, 2017)
Author Information
Peter Knees holds a doctorate degree in computer science and is currently assistant professor of the Department of Computational Perception of the Johannes Kepler University Linz in Austria. For over a decade, he has been an active member of the music information retrieval research community, branching out to the related areas of multimedia, text IR, recommender systems, and digital media arts. Markus Schedl is an associate professor of the Johannes Kepler University Linz / Department of Computational Perception. His main research interests include music and multimedia information retrieval, web and social media mining, and recommender systems. In addition to regularly publishing in and offering scientific services to top-tier conferences and journals of these fields, he is associate editor of the Springer International Journal of Multimedia Information Retrieval. He is also a keen lecturer and taught classes at the Universitat Pompeu Fabra Barcelona, QueenMary University London, and Kungliga Tekniska Högskolan Stockholm, among others.
