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.

Authors: Heydarian, Peyman; Jones, Lewis; Seago, Allan
Affiliation: London Metropolitan University, London, UK
AES Convention: 133 (October 2012) Paper Number: 8794
Publication Date: October 25, 2012 Import into BibTeX
Subject: Analysis and Synthesis of Sound
Permalink: https://www.aes.org/e-lib/browse.cfm?elib=16536

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