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999			_c102113 _d102113
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007			cr nn 008mamaa
008			170921s2018 gw | s |||| 0|eng d
020			_a9783319634500
024	7		_a10.1007/978-3-319-63450-0 _2doi
040			_bspa _cES-MaUEC _dES-MaUEC
050		4	_aTK5102.9 _bC667 2018 EB
245	1	0	_aComputational Analysis of Sound Scenes and Events _cedited by Tuomas Virtanen, Mark D. Plumbley, Dan Ellis.
264		1	_aCham _bSpringer International Publishing _c2018
300			_a1 recurso en línea (X, 422 páginas 81 ilustraciones, 54 ilustraciones a color.)
336			_2rdacontent _aTexto _btxt
337			_2rdamedia _aelectrónico _bc
338			_2rdacarrier _arecurso electrónico _bcr
347			_atext file _bPDF
490	0		_aEngineering (Springer-11647)
505	0		_aIntroduction to sound scene and event analysis.- The Machine Learning Approach for Analysis of Sound Scenes and Events -- Acoustics and psychacoustics of sound scenes and events -- Acoustic features for environmental sound analysis -- Statistical Methods for Scene and Event Classification -- Datasets and evaluation -- Everyday Sound Categorization -- Approaches to complex sound scene analysis -- Multiview approaches to event detection and scene analysis -- Sound sharing and retrieval -- Computational bioacoustic scene analysis -- Audio Event Recognition in the Smart Home -- Sound Analysis in Smart Cities -- Future Perspective -- Index.
520	3		_aThis book presents computational methods for extracting the useful information from audio signals, collecting the state of the art in the field of sound event and scene analysis. The authors cover the entire procedure for developing such methods, ranging from data acquisition and labeling, through the design of taxonomies used in the systems, to signal processing methods for feature extraction and machine learning methods for sound recognition. The book also covers advanced techniques for dealing with environmental variation and multiple overlapping sound sources, and taking advantage of multiple microphones or other modalities. The book gives examples of usage scenarios in large media databases, acoustic monitoring, bioacoustics, and context-aware devices. Graphical illustrations of sound signals and their spectrographic representations are presented, as well as block diagrams and pseudocode of algorithms. Gives an overview of methods for computational analysis of sounds scenes and events, allowing those new to the field to become fully informed; Covers all the aspects of the machine learning approach to computational analysis of sound scenes and events, ranging from data capture and labeling process to development of algorithms; Includes descriptions of algorithms accompanied by a website from which software implementations can be downloaded, facilitating practical interaction with the techniques.
988			_aEBSPRINGER_2018
650		7	_2embne _9150608 _aProceso de señales
700	1		_aVirtanen, Tuomas. _eeditor literario _4edt _4http://id.loc.gov/vocabulary/relators/edt _0http://id.loc.gov/authorities/names/n2012036368 _1http://viaf.org/viaf/250989495/
700	1		_aPlumbley, Mark D. _eeditor literario _4edt _4http://id.loc.gov/vocabulary/relators/edt _1http://viaf.org/viaf/207171869/
700	1		_aEllis, Dan _0http://id.loc.gov/authorities/names/nb2011027724 _1http://viaf.org/viaf/79227885/ _1http://dbpedia.org/resource/Dan_Ellis _9672046
776	0	8	_iEdición impresa: _z9783319634494
776	0	8	_iEdición impresa: _z9783319634517
776	0	8	_iEdición impresa: _z9783319875590
856	4	0	_uhttps://go.openathens.net/redirector/universidadeuropea.es?url=https://doi.org/10.1007/978-3-319-63450-0 _zAcceso a este recurso digital (usuarios Universidad Europea de Madrid)
942			_2lcc _cLE