Detecting and Classifying Emotion in Popular Music

DOI

10.2991/jcis.2006.325How to use a DOI?

Keywords

Music emotion, Music classifier

Abstract

Music expresses emotion. However, analyzing the emotion in music by computer is a difficult task. Some work can be found in the literature, but the results are not satisfactory. In this paper, an emotion detection and classification system for pop music is presented. The system extracts feature values from the training music files by PsySound2 and generates a music model from the resulting feature dataset by a classification algorithm. The model is then used to detect the emotion perceived in music clips. To further improve the classification accuracy, we evaluate the significance of each music feature and remove the insignificant features. The system uses a database of 195 music clips to enhance reliability and robustness.

Copyright

© 2006, the Authors. Published by Atlantis Press.

Open Access

This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

Download article (PDF)

TY  - CONF
AU  - Chia Chu Liu
AU  - Yi Hsuan Yang
AU  - Ping Hao Wu
AU  - Homer Chen
PY  - 2006/10
DA  - 2006/10
TI  - Detecting and Classifying Emotion in Popular Music
BT  - Proceedings of the 9th Joint International Conference on Information Sciences (JCIS-06)
PB  - Atlantis Press
SN  - 1951-6851
UR  - https://doi.org/10.2991/jcis.2006.325
DO  - 10.2991/jcis.2006.325
ID  - Liu2006/10
ER  -