9th Joint International Conference on Information Sciences (JCIS-06)

Detecting and Classifying Emotion in Popular Music

Authors
Chia Chu Liu 0, Yi Hsuan Yang, Ping Hao Wu, Homer Chen
Corresponding Author
Chia Chu Liu
0Graduate Institute of Communication Engineering, NTU
Available Online October 2006.
DOI
https://doi.org/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.
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This is an open access article distributed under the CC BY-NC license.

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Proceedings
9th Joint International Conference on Information Sciences (JCIS-06)
Part of series
Advances in Intelligent Systems Research
Publication Date
October 2006
ISBN
978-90-78677-01-7
DOI
https://doi.org/10.2991/jcis.2006.325How to use a DOI?
Open Access
This is an open access article distributed under the CC BY-NC license.

Cite this article

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  - 9th Joint International Conference on Information Sciences (JCIS-06)
PB  - Atlantis Press
UR  - https://doi.org/10.2991/jcis.2006.325
DO  - https://doi.org/10.2991/jcis.2006.325
ID  - Liu2006/10
ER  -