Automatic Classification of Musical Pieces into Global Cultural Areas

Kruspe A, Lukashevich H, Abeßer J, Großmann H, Dittmar C. Automatic Classification of Musical Pieces into Global Cultural Areas. In: AES Conference: 42nd International Conference: Semantic Audio. Audio Engineering Society; 2011. Paper P1-3. Available from: https://aes.org/publications/elibrary-page/?id=15958

@inproceedings{Kruspe2011_15958,
  author = {Kruspe, Anna and Lukashevich, Hanna and Abeßer, Jakob and Großmann, Holger and Dittmar, Christian},
  title = {{Automatic Classification of Musical Pieces into Global Cultural Areas}},
  booktitle = {AES Conference: 42nd International Conference: Semantic Audio},
  note = {Paper P1-3},
  year = {2011},
  month = jul,
  publisher = {Audio Engineering Society},
  url = {https://aes.org/publications/elibrary-page/?id=15958}
}

TY  - CPAPER
TI  - Automatic Classification of Musical Pieces into Global Cultural Areas
AU  - Kruspe, Anna
AU  - Lukashevich, Hanna
AU  - Abeßer, Jakob
AU  - Großmann, Holger
AU  - Dittmar, Christian
T2  - AES Conference: 42nd International Conference: Semantic Audio
M1  - Paper P1-3
PY  - 2011
DA  - 2011/07/06
UR  - https://aes.org/publications/elibrary-page/?id=15958
PB  - Audio Engineering Society
LA  - en
AB  - Music Information Retrieval (MIR) has a large variety of applications. One aspect that has not gathered a lot of attention yet is the application to non-western music ("world music"). In a task comparable to genre classification, this work's goal is the classification of musical pieces into their corresponding cultural regions of origin. As a basis for such a classification, a three-tier taxonomy based on musical and geographic properties is created. A database consisting of approximately 4400 musical pieces representing the taxonomical classes is assembled and annotated. Based on rhythmic, tonal, and timbre-related audio features, different classification experiments are performed. We achieved an accuracy of approx. 70% for the classification of musical pieces into nine large world regions. Twelve new features that are especially suited for non-western music are implemented. They improve the classification result slightly. For the purpose of comparison, we carried out a listening test with musical laymen with an average accuracy of 52%.
ER  -