Peter Knees, Markus Schedl

Music Similarity and Retrieval (eBook, PDF)

An Introduction to Audio- and Web-based Strategies

• Format: PDF

Produktbeschreibung

This book provides a summary of the manifold audio- and web-based approaches to music information retrieval (MIR) research. In contrast to other books dealing solely with music signal processing, it addresses additional cultural and listener-centric aspects and thus provides a more holistic view. Consequently, the text includes methods operating on features extracted directly from the audio signal, as well as methods operating on features extracted from contextual information, either the cultural context of music as represented on the web or the user and usage context of music.

Following the prevalent document-centered paradigm of information retrieval, the book addresses models of music similarity that extract computational features to describe an entity that represents music on any level (e.g., song, album, or artist), and methods to calculate the similarity between them. While this perspective and the representations discussed cannot describe all musical dimensions, theyenable us to effectively find music of similar qualities by providing abstract summarizations of musical artifacts from different modalities.

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Produktdetails

• Verlag: Springer Berlin Heidelberg
• Seitenzahl: 299
• Erscheinungstermin: 28. Mai 2016
• Englisch
• ISBN-13: 9783662497227
• Artikelnr.: 46927804

Autorenporträt

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.

Inhaltsangabe

1 Introduction to Music Similarity and Retrieval.- 2 Basic Methods of Audio Signal Processing.- 3 Audio Feature Extraction for Similarity Measurement.- 4 Semantic Labeling of Music.- 5 Contextual Music Meta-data: Comparison and Sources.- 6 Contextual Music Similarity, Indexing, and Retrieval.- 7 Listener-centered Data Sources and Aspects: Traces of Music Interaction.- 8 Collaborative Music Similarity and Recommendation.- 9 Applications.- 10 Grand Challenges and Outlook.- Appendix.

Rezensionen

"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)