Music Emotion Recognition
Providing a comprehensive review of existing work in music emotion developed in psychology and engineering, this book explains how to account for the subjective nature of emotion perception in the development of automatic music emotion recognition (MER) systems. Among the first publications dedicated to automatic MER, it begins with a complete introduction to the essential aspects of MER-including background, key techniques, and applications. This ground-breaking reference examines emotion from a dimensional perspective. It defines emotions in music as points in a 2D plane in terms of two of the most fundamental emotion dimensions according to psychologists-valence and arousal.
1102250485
Music Emotion Recognition
Providing a comprehensive review of existing work in music emotion developed in psychology and engineering, this book explains how to account for the subjective nature of emotion perception in the development of automatic music emotion recognition (MER) systems. Among the first publications dedicated to automatic MER, it begins with a complete introduction to the essential aspects of MER-including background, key techniques, and applications. This ground-breaking reference examines emotion from a dimensional perspective. It defines emotions in music as points in a 2D plane in terms of two of the most fundamental emotion dimensions according to psychologists-valence and arousal.
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Music Emotion Recognition

Music Emotion Recognition

Music Emotion Recognition

Music Emotion Recognition

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Overview

Providing a comprehensive review of existing work in music emotion developed in psychology and engineering, this book explains how to account for the subjective nature of emotion perception in the development of automatic music emotion recognition (MER) systems. Among the first publications dedicated to automatic MER, it begins with a complete introduction to the essential aspects of MER-including background, key techniques, and applications. This ground-breaking reference examines emotion from a dimensional perspective. It defines emotions in music as points in a 2D plane in terms of two of the most fundamental emotion dimensions according to psychologists-valence and arousal.

Product Details

ISBN-13: 9781040059685
Publisher: CRC Press
Publication date: 02/22/2011
Series: Multimedia Computing, Communication and Intelligence
Sold by: Barnes & Noble
Format: eBook
Pages: 261
File size: 6 MB

About the Author

Yi-Hsuan Yang received a Ph.D. in Communication Engineering from National Taiwan University in 2010. His research interests include multimedia information retrieval, music analysis, machine learning, and affective computing. He has published over 30 technical papers in the above areas. Dr. Yang was awarded MediaTek Fellowship in 2009 and Microsoft Research Asia Fellowship in 2008.

Homer H. Chen received a Ph.D. in Electrical and Computer Engineering from the University of Illinois at Urbana- Champaign. Since August 2003, he has been with the College of Electrical Engineering and Computer Science, National Taiwan University, where he is Irving T. Ho Chair Professor. Prior to that, he held various R&D management and engineering positions with US companies over a period of 17 years, including AT&T Bell Labs, Rockwell Science Center, iVast, and Digital Island. He was a US delegate for ISO and ITU standards committees and contributed to the development of many new interactive multimedia technologies that are now part of the MPEG-4 and JPEG-2000 standards. His professional interests lie in the broad area of multimedia signal processing and communications.

Dr. Chen is an Associate Editor of IEEE Transactions on Circuits and Systems for Video Technology. He served as Associate Editor of IEEE Transactions on Image Processing from 1992 to 1994, Guest Editor of IEEE Transactions on Circuits and Systems for Video Technology in 1999, and an Associate Editorial of Pattern Recognition from 1989 to 1999. He is an IEEE Fellow.

Table of Contents

Overview of Emotion Description and Recognition. Music Features. Dimensional MER by Regression. Ranking-Based Emotion Annotation and Model Training. Fuzzy Classification of Music Emotion. Personalized MER and Groupwise MER. Two-Layer Personalization. Probability Music Emotion Distribution Prediction. Lyrics Analysis and Its Application to MER. Chord Recognition and Its Application to MER. Genre Classification and Its Application to MER. Music Retrieval in the Emotion Plane. Future Research Directions.
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