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008 171104s2018 gw | s |||| 0|eng d
020 _a9783319706092
024 7 _a10.1007/978-3-319-70609-2
_2doi
040 _aES-MaUEC
_bspa
050 4 _aML74
_b.G745 2018 EB
100 1 _aGrekow, Jacek
_eautor
_4aut
_4http://id.loc.gov/vocabulary/relators/aut
_1http://viaf.org/viaf/302749078/
245 1 0 _aFrom Content-based Music Emotion Recognition to Emotion Maps of Musical Pieces
_cby Jacek Grekow.
264 1 _aCham
_bSpringer International Publishing
_c2018
300 _a1 recurso en línea (XIV, 138 páginas 71 ilustraciones, 22 ilustraciones a color)
347 _atext file
_bPDF
490 0 _aStudies in Computational Intelligence
_x1860-949X
_v747
505 0 _aIntroduction -- Representations of Emotions -- Human Annotation -- MIDI Features -- Hierarchical Emotion Detection in MIDI Files.
520 3 _aThe problems it addresses include emotion representation, annotation of music excerpts, feature extraction, and machine learning. The book chiefly focuses on content-based analysis of music files, a system that automatically analyzes the structures of a music file and annotates the file with the perceived emotions. Further, it explores emotion detection in MIDI and audio files. In the experiments presented here, the categorical and dimensional approaches were used, and the knowledge and expertise of music experts with a university music education were used for music file annotation. The automatic emotion detection systems constructed and described in the book make it possible to index and subsequently search through music databases according to emotion. In turn, the emotion maps of musical compositions provide valuable new insights into the distribution of emotions in music and can be used to compare that distribution in different compositions, or to conduct emotional comparisons of different interpretations of the same composition.
650 7 _aMúsica por ordenador
_2embne
_9141144
776 0 8 _iEdición impresa:
_z9783319706085
776 0 8 _iEdición impresa:
_z9783319706108
776 0 8 _iEdición impresa:
_z9783319889689
856 4 0 _uhttps://go.openathens.net/redirector/universidadeuropea.es?url=https://doi.org/10.1007/978-3-319-70609-2
_zAcceso a este recurso digital (usuarios Universidad Europea de Madrid)
490 0 _aEngineering (Springer-11647)
988 _aEBSPRINGER_2018
998 _b02/2019
_dz
_ek
_feng
_ggw
_h0
999 _c102883
_d102883
_x1