Automatic Mode Estimation of Persian Musical Signals

Heydarian P, Jones L, Seago A. Automatic Mode Estimation of Persian Musical Signals. In: AES Convention 133. Audio Engineering Society; 2012. Paper 8794. Available from: https://aes.org/publications/elibrary-page/?id=16536

@inproceedings{Heydarian2012_16536,
  author = {Heydarian, Peyman and Jones, Lewis and Seago, Allan},
  title = {{Automatic Mode Estimation of Persian Musical Signals}},
  booktitle = {AES Convention 133},
  note = {Paper 8794},
  year = {2012},
  month = oct,
  publisher = {Audio Engineering Society},
  url = {https://aes.org/publications/elibrary-page/?id=16536}
}

TY  - CPAPER
TI  - Automatic Mode Estimation of Persian Musical Signals
AU  - Heydarian, Peyman
AU  - Jones, Lewis
AU  - Seago, Allan
T2  - AES Convention 133
M1  - Paper 8794
PY  - 2012
DA  - 2012/10/06
UR  - https://aes.org/publications/elibrary-page/?id=16536
PB  - Audio Engineering Society
LA  - en
AB  - Musical mode is central to maqamic musical traditions that span from Western China to Southern Europe. A mode usually represents the scale and is to some extent an indication of the emotional content of a piece. Knowledge of the mode is useful in searching multicultural archives of maqamic musical signals. Thus, the modal information is worth inclusion in metadata of a file. An automatic mode classification algorithm will have potential applications in music recommendation and play list generation, where the pieces can be ordered based on a perceptually accepted criterion such as the mode. It has the possibility of being used as a framework for music composition and synthesis. This paper presents an algorithm for classification of Persian audio musical signals, based on a generative approach, i.e., Gaussian Mixture Models (GMM), where chroma is used as the feature. The results will be compared with a chroma-based method with a Manhattan distance measure that was previously developed by ourselves.
ER  -