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Aesthetics, Modern. --- Illusion (Philosophy) --- Illusion in literature. --- Representation (Philosophy) --- Information theory in aesthetics. --- Aesthetics --- Cybernetics --- Perception --- Psychology --- Representationalism (Philosophy) --- Representationism (Philosophy) --- Culture --- Philosophy --- Hallucinations and illusions --- Knowledge, Theory of --- Modern aesthetics

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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, 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.>.

Computer science. --- Big data. --- Information storage and retrieval. --- Application software. --- Computer Science. --- Information Storage and Retrieval. --- Computer Appl. in Arts and Humanities. --- Signal, Image and Speech Processing. --- Big Data/Analytics. --- Information retrieval. --- Music --- Information theory in music. --- Information technology. --- Art music --- Art music, Western --- Classical music --- Musical compositions --- Musical works --- Serious music --- Western art music --- Western music (Western countries) --- Data retrieval --- Data storage --- Discovery, Information --- Information discovery --- Information storage and retrieval --- Retrieval of information --- Information theory in aesthetics --- Documentation --- Information science --- Information storage and retrieval systems --- Information storage and retrieva. --- Information systems. --- Information storage and retrieval systems. --- Signal processing. --- Image processing. --- Speech processing systems. --- Data sets, Large --- Large data sets --- Data sets --- Computational linguistics --- Electronic systems --- Information theory --- Modulation theory --- Oral communication --- Speech --- Telecommunication --- Singing voice synthesizers --- Pictorial data processing --- Picture processing --- Processing, Image --- Imaging systems --- Optical data processing --- Processing, Signal --- Information measurement --- Signal theory (Telecommunication) --- Application computer programs --- Application computer software --- Applications software --- Apps (Computer software) --- Computer software