LEADER 05133nam 22006855 450 001 9910254982203321 005 20200710134900.0 010 $a3-662-49722-0 024 7 $a10.1007/978-3-662-49722-7 035 $a(CKB)3710000000718375 035 $a(DE-He213)978-3-662-49722-7 035 $a(MiAaPQ)EBC4533869 035 $a(PPN)19407482X 035 $a(EXLCZ)993710000000718375 100 $a20160528d2016 u| 0 101 0 $aeng 135 $aurnn#008mamaa 181 $ctxt$2rdacontent 182 $cc$2rdamedia 183 $acr$2rdacarrier 200 10$aMusic Similarity and Retrieval $eAn Introduction to Audio- and Web-based Strategies /$fby Peter Knees, Markus Schedl 205 $a1st ed. 2016. 210 1$aBerlin, Heidelberg :$cSpringer Berlin Heidelberg :$cImprint: Springer,$d2016. 215 $a1 online resource (XX, 299 p. 82 illus., 47 illus. in color.) 225 1 $aThe Information Retrieval Series,$x1871-7500 ;$v36 311 $a3-662-49720-4 320 $aIncludes bibliographical references and index. 327 $a1 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. 330 $aThis book provides a summary of the manifold audio- and web-based approaches to music information retrieval (MIR) research. In contrast to other books dealing solely with music signal processing, it addresses additional cultural and listener-centric aspects and thus provides a more holistic view. Consequently, the text includes methods operating on features extracted directly from the audio signal, as well as methods operating on features extracted from contextual information, either the cultural context of music as represented on the web or the user and usage context of music. Following the prevalent document-centered paradigm of information retrieval, the book addresses models of music similarity that extract computational features to describe an entity that represents music on any level (e.g., song, album, or artist), and methods to calculate the similarity between them. While this perspective and the representations discussed cannot describe all musical dimensions, they enable us to effectively find music of similar qualities by providing abstract summarizations of musical artifacts from different modalities. The text at hand provides a comprehensive and accessible introduction to the topics of music search, retrieval, and recommendation from an academic perspective. It will not only allow those new to the field to quickly access MIR from an information retrieval point of view but also raise awareness for the developments of the music domain within the greater IR community. In this regard, Part I deals with content-based MIR, in particular the extraction of features from the music signal and similarity calculation for content-based retrieval. Part II subsequently addresses MIR methods that make use of the digitally accessible cultural context of music. Part III addresses methods of collaborative filtering and user-aware and multi-modal retrieval, while Part IV explores current and future applications of music retrieval and recommendation.>. 410 0$aThe Information Retrieval Series,$x1871-7500 ;$v36 606 $aInformation storage and retrieval 606 $aApplication software 606 $aSignal processing 606 $aImage processing 606 $aSpeech processing systems 606 $aBig data 606 $aInformation Storage and Retrieval$3https://scigraph.springernature.com/ontologies/product-market-codes/I18032 606 $aComputer Appl. in Arts and Humanities$3https://scigraph.springernature.com/ontologies/product-market-codes/I23036 606 $aSignal, Image and Speech Processing$3https://scigraph.springernature.com/ontologies/product-market-codes/T24051 606 $aBig Data/Analytics$3https://scigraph.springernature.com/ontologies/product-market-codes/522070 615 0$aInformation storage and retrieval. 615 0$aApplication software. 615 0$aSignal processing. 615 0$aImage processing. 615 0$aSpeech processing systems. 615 0$aBig data. 615 14$aInformation Storage and Retrieval. 615 24$aComputer Appl. in Arts and Humanities. 615 24$aSignal, Image and Speech Processing. 615 24$aBig Data/Analytics. 676 $a025.04 700 $aKnees$b Peter$4aut$4http://id.loc.gov/vocabulary/relators/aut$0929210 702 $aSchedl$b Markus$4aut$4http://id.loc.gov/vocabulary/relators/aut 801 0$bMiAaPQ 801 1$bMiAaPQ 801 2$bMiAaPQ 906 $aBOOK 912 $a9910254982203321 996 $aMusic Similarity and Retrieval$92088414 997 $aUNINA