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001			85146
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008			151027s2016 gw | s |||| 0|eng d
020			_a9783319259314
040			_aES-MaUEC
050		4	_aML3800 _b.C667 2016
082	0	4	_a004
245	1	0	_aComputational Music Analysis _cedited by David Meredith
250			_a1st ed.
260			_aCham _bSpringer International Publishing _c2016
300			_a1 recurso en línea (XV, 480 páginas) _b184 ilustraciones, 143 ilustraciones en color
336			_aTexto _btxt _2rdacontent
337			_aelectrónico _bc _2rdamedia
338			_arecurso electrónico _bcr _2rdacarrier
505	0		_aMusic Analysis by Computer Ontology and Epistemology -- The Harmonic Musical Surface and Two Novel Chord Representation Schemes -- Topological Structures in Computer-Aided Music Analysis -- Contextual Set-Class Analysis -- Computational Analysis of Musical Form -- Chord- and Note-Based Approaches to Voice Separation -- Analysing Symbolic Music with Probabilistic Grammars -- Interactive Melodic Analysis -- Implementing Methods for Analysing Music Based on Lerdahl and Jackendoff�s Generative Theory of Tonal Music -- An Algebraic Approach to Time-Span Reduction -- Automated Motivic Analysis An Exhaustive Approach Based on Closed and Cyclic Pattern Mining in Multidimensional Parametric Spaces -- A Wavelet-Based Approach to Pattern Discovery in Melodies -- Analysing Music with Point-Set Compression Algorithms -- Composer Classification Models for Music-Theory Building -- Contrast Pattern Mining in Folk Music Analysis -- Pattern and Antipattern Discovery in Ethiopian Bagana Songs -- Using Geometric Symbolic Fingerprinting to Discover Distinctive Patterns in Polyphonic Music Corpora -- Index.
520	3		_aThis book provides an in-depth introduction and overview of current research in computational music analysis. Its seventeen chapters, written by leading researchers, collectively represent the diversity as well as the technical and philosophical sophistication of the work being done today in this intensely interdisciplinary field. A broad range of approaches are presented, employing techniques originating in disciplines such as linguistics, information theory, information retrieval, pattern recognition, machine learning, topology, algebra and signal processing. Many of the methods described draw on well-established theories in music theory and analysis, such as Forte's pitch-class set theory, Schenkerian analysis, the methods of semiotic analysis developed by Ruwet and Nattiez, and Lerdahl and Jackendoff's Generative Theory of Tonal Music. The book is divided into six parts, covering methodological issues, harmonic and pitch-class set analysis, form and voice-separation, grammars and hierarchical reduction, motivic analysis and pattern discovery and, finally, classification and the discovery of distinctive patterns. As a detailed and up-to-date picture of current research in computational music analysis, the book provides an invaluable resource for researchers, teachers and students in music theory and analysis, computer science, music information retrieval and related disciplines. It also provides a state-of-the-art reference for practitioners in the music technology industry.
710	2		_aSpringerLink (Online service) _0Local _9106996
942			_2lcc _cLE
988			_aEBOOK, asignarmaterias , EBSPRINGER
650		7	_aMúsica _0comprobar BNE19900961860 _2embne _9138603
650	0	7	_aSoftware de aplicación _2embne _9419596
700	1		_aMeredith, David. _eeditor literario _923769 _0comprobar BNE19961158892
856	4	0	_uhttps://go.openathens.net/redirector/universidadeuropea.es?url=https://link.springer.com/book/10.1007/978-3-319-25931-4 _zAcceso a este recurso digital (usuarios Universidad Europea de Madrid)
901			_ai9783319259314
907			_a.b12944245 _b10-10-17 _c21-11-16
998			_am _a_alco _a_vill _b - - _cm _dz _e- _feng _ggw _h0
945			_aML3800 .C667 2016 EB _g1 _ieBOOK _j0 _lmae _o- _pEUR0.00 _q- _r- _sb _t15 _u0 _v0 _w0 _x0 _y.i11588354 _z06-04-17
999			_c85146 _d85146 _x1