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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| Hlavný autor: | |
|---|---|
| Médium: | Elektronický zdroj E-kniha |
| Jazyk: | English |
| Vydavateľské údaje: |
Cham :
Springer International Publishing,
2018.
|
| Vydanie: | 1st ed. 2018. |
| Edícia: | Studies in Computational Intelligence,
747 |
| Predmet: | |
| ISBN: | 9783319706092 |
| ISSN: | 1860-949X ; |
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| LEADER | 00000nam a22000005i 4500 | ||
|---|---|---|---|
| 003 | SK-BrCVT | ||
| 005 | 20220618120443.0 | ||
| 007 | cr nn 008mamaa | ||
| 008 | 171104s2018 gw | s |||| 0|eng d | ||
| 020 | |a 9783319706092 | ||
| 024 | 7 | |a 10.1007/978-3-319-70609-2 |2 doi | |
| 035 | |a CVTIDW09492 | ||
| 040 | |a Springer-Nature |b eng |c CVTISR |e AACR2 | ||
| 041 | |a eng | ||
| 100 | 1 | |a Grekow, Jacek. |4 aut | |
| 245 | 1 | 0 | |a From Content-based Music Emotion Recognition to Emotion Maps of Musical Pieces |h [electronic resource] / |c by Jacek Grekow. |
| 250 | |a 1st ed. 2018. | ||
| 260 | 1 | |a Cham : |b Springer International Publishing, |c 2018. | |
| 300 | |a XIV, 138 p. 71 illus., 22 illus. in color. |b online resource. | ||
| 490 | 1 | |a Studies in Computational Intelligence, |x 1860-949X ; |v 747 | |
| 500 | |a Engineering | ||
| 505 | 0 | |a Introduction -- Representations of Emotions -- Human Annotation -- MIDI Features -- Hierarchical Emotion Detection in MIDI Files. | |
| 516 | |a text file PDF | ||
| 520 | |a 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. | ||
| 650 | 0 | |a Computational intelligence. | |
| 650 | 0 | |a Music. | |
| 650 | 0 | |a Acoustical engineering. | |
| 650 | 0 | |a Emotions. | |
| 650 | 0 | |a Pattern recognition. | |
| 650 | 0 | |a Acoustics. | |
| 856 | 4 | 0 | |u http://hanproxy.cvtisr.sk/han/cvti-ebook-springer-eisbn-978-3-319-70609-2 |y Vzdialený prístup pre registrovaných používateľov |
| 910 | |b ZE06772 | ||
| 919 | |a 978-3-319-70609-2 | ||
| 974 | |a andrea.lebedova |f Elektronické zdroje | ||
| 992 | |a SUD | ||
| 999 | |c 275075 |d 275075 | ||