From Content-based Music Emotion Recognition to Emotion Maps of Musical Pieces (Studies in Computational Intelligence, 747). This item is unavailable.
Language: English
Published by Springer, 2017
Series: Book 259 of 538 - Studies in Computational Intelligence
- Hardcover
- New

Seller: Ria Christie Collections, Uxbridge, United KingdomRia Christie Collections
AbeBooks seller since March 25, 2015
Condition: New
£ 106.71
Item description from seller
In English.
Seller Inventory # ria9783319706085_new
- Title
- From Content-based Music Emotion Recognition to Emotion Maps of Musical Pieces (Studies in Computational Intelligence, 747)
- Author
- Grekow, Jacek
- Publisher
- Springer
- Publication year
- 2017
- Condition
- New
- Binding
- Hardcover
- Language
- English
- ISBN 10
- 331970608X
- ISBN 13
- 9783319706085
- Item weight
- 517 grams
- Series
- Book 259 of 538: Studies in Computational Intelligence
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."Synopsis" may belong to another edition of this title.
From the Back Cover
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."About the title" may belong to another edition of this title.