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020 _a9783319634500
_9978-3-319-63450-0
024 7 _a10.1007/978-3-319-63450-0
_2doi
050 4 _aTK5102.9
072 7 _aTJF
_2bicssc
072 7 _aUYS
_2bicssc
072 7 _aTEC008000
_2bisacsh
072 7 _aTJF
_2thema
072 7 _aUYS
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082 0 4 _a621.382
_223
245 1 0 _aComputational Analysis of Sound Scenes and Events
_h[electronic resource] /
_cedited by Tuomas Virtanen, Mark D. Plumbley, Dan Ellis.
250 _a1st ed. 2018.
264 1 _aCham :
_bSpringer International Publishing :
_bImprint: Springer,
_c2018.
300 _aX, 422 p. 81 illus., 54 illus. in color.
_bonline resource.
336 _atext
_btxt
_2rdacontent
337 _acomputer
_bc
_2rdamedia
338 _aonline resource
_bcr
_2rdacarrier
347 _atext file
_bPDF
_2rda
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 _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.
650 0 _aSignal processing.
_94052
650 0 _aAcoustical engineering.
_99499
650 0 _aSocial sciences—Data processing.
_931812
650 0 _aUser interfaces (Computer systems).
_911681
650 0 _aHuman-computer interaction.
_96196
650 1 4 _aSignal, Speech and Image Processing .
_931566
650 2 4 _aEngineering Acoustics.
_931982
650 2 4 _aComputer Application in Social and Behavioral Sciences.
_931815
650 2 4 _aUser Interfaces and Human Computer Interaction.
_931632
700 1 _aVirtanen, Tuomas.
_eeditor.
_4edt
_4http://id.loc.gov/vocabulary/relators/edt
_930795
700 1 _aPlumbley, Mark D.
_eeditor.
_0(orcid)0000-0002-9708-1075
_1https://orcid.org/0000-0002-9708-1075
_4edt
_4http://id.loc.gov/vocabulary/relators/edt
_939094
700 1 _aEllis, Dan.
_eeditor.
_4edt
_4http://id.loc.gov/vocabulary/relators/edt
_930344
710 2 _aSpringerLink (Online service)
_939095
773 0 _tSpringer Nature eBook
776 0 8 _iPrinted edition:
_z9783319634494
776 0 8 _iPrinted edition:
_z9783319634517
776 0 8 _iPrinted edition:
_z9783319875590
856 4 0 _uhttps://doi.org/10.1007/978-3-319-63450-0
912 _aZDB-2-ENG
912 _aZDB-2-SXE
942 _cEBK
999 _c76487
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