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From Content-based Music Emotion Recognition to Emotion Maps of Musical Pieces

The 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 per...

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Detaylı Bibliyografya
Yazar: Grekow, Jacek (Yazar)
Müşterek Yazar: SpringerLink (Online service)
Materyal Türü: e-Kitap
Dil:İngilizce
Baskı/Yayın Bilgisi: Cham : Springer International Publishing : 2018.
Imprint: Springer,
Edisyon:1st ed. 2018.
Seri Bilgileri:Studies in Computational Intelligence, 747
Konular:
Online Erişim:Full-text access
Diğer Bilgiler
Özet:The 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.
Fiziksel Özellikler:XIV, 138 p. 71 illus., 22 illus. in color. online resource.
ISBN:9783319706092
ISSN:1860-9503 ;
DOI:10.1007/978-3-319-70609-2