Music Emotion and Genre Recognition Toward New Affective Music Taxonomy

Kim J, Larsen L. Music Emotion and Genre Recognition Toward New Affective Music Taxonomy. In: AES Convention 128. Audio Engineering Society; 2010.pp. 8018:1-8. Available from: https://aes.org/publications/elibrary-page/?id=15315

@inproceedings{Kim2010_15315,
  author = {Kim, Jonghwa and Larsen, Lars},
  title = {{Music Emotion and Genre Recognition Toward New Affective Music Taxonomy}},
  booktitle = {AES Convention 128},
  pages = {8018:1-8},
  url = {https://aes.org/publications/elibrary-page/?id=15315},
  year = {2010},
  month = may,
  publisher = {Audio Engineering Society}
}

TY  - CPAPER
TI  - Music Emotion and Genre Recognition Toward New Affective Music Taxonomy
AU  - Kim, Jonghwa
AU  - Larsen, Lars
T2  - AES Convention 128
SP  - 1
EP  - 8
M1  - Paper 8018
PY  - 2010
DA  - 2010/05/06
UR  - https://aes.org/publications/elibrary-page/?id=15315
PB  - Audio Engineering Society
LA  - en
AB  - Exponentially increasing electronic music distribution creates a natural pressure for fine-grained musical metadata. On the basis of the fact that a primary motive for listening to music is its emotional effect, diversion, and the memories it awakens, we propose a novel affective music taxonomy which combines the global music genre taxonomy, e.g. Classical, Jazz, Rock/Pop, and Rap, with emotion categories such as Joy, Sadness, Anger, and Pleasure, in a complementary way. In this paper, we deal with all essential stages of automatic genre/emotion recognition system, i.e. from reasonable music data collection up to performance evaluation of various machine learning algorithms. Particularly, a novel classification scheme, called as consecutive dichotomous decomposition tree (CDDT) is presented which is specifically parametrized for multi-class classification problem with extremely high number of class, e.g. sixteen music categories in our case. The average recognition accuracy of 75% for the 16 music categories shows a realistic possibility of the affective music taxonomy we proposed.
ER  -