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.
- 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 SN - 1951-6851 UR - https://doi.org/10.2991/jcis.2006.325 DO - https://doi.org/10.2991/jcis.2006.325 ID - Liu2006/10 ER -