@ARTICLE{0777Burred2004,
	AUTHOR = {Juan José Burred and Alexander Lerch},
	TITLE = {Hierarchical Automatic Audio Signal Classification},
	JOURNAL = {Journal of the Audio Engineering Society},
	YEAR = {2004},
	MONTH = jul,
	PAGES = {724--739},
	VOLUME = {52},
	NUMBER = {7/8},
	NOTE = {A. Lerch: zplane.development},
	PDF = {http://elvera.nue.tu-berlin.de/files/0777Burred2004.pdf},
	URL = {http://elvera.nue.tu-berlin.de/files/0777Burred2004.pdf},
	ABSTRACT = {The design, implementation, and evaluation of a system for automatic audio signal classification is presented. The signals are classified according to audio type, differentiating between three speech classes, 13 musical genres, and background noise. A large number of audio features are evaluated for their suitability in such a classification task, including MPEG-7 descriptors and several new features. The selection of the features is carried out systematically with regard to their robustness to noise and bandwidth changes, as well as to their ability to distinguish a given set of audio types. Direct and hierarchical approaches for the feature selection and for the classification are evaluated and compared.}
}