@INPROCEEDINGS{0785Rein2004,
	AUTHOR = {Stephan Rein and Martin Reisslein and Thomas Sikora},
	TITLE = {Audio Content Description with Wavelets and Neural Nets},
	BOOKTITLE = {IEEE ICASSP 2004},
	YEAR = {2004},
	MONTH = may,
	ADDRESS = {Montreal, Canada},
	NOTE = {Martin Reisslein: Arizona State University},
	PDF = {http://elvera.nue.tu-berlin.de/files/0785Rein2004.pdf},
	URL = {http://elvera.nue.tu-berlin.de/files/0785Rein2004.pdf},
	ABSTRACT = {Precision audio content description is one of the key components of next generation internet multimedia search machines.We examine the usability of a combination of 39 different wavelets and three different types of neural nets
for precision audio content description. More specifically,
we develop a novel wavelet dispersion measure that measures
obtained ranks of wavelet coefficients. Our dispersion measure in conjunction with a probabilistic radial basis neural network trained by only three independent example sets obtains a success rate of approximately 78% in identifying unknown complex classical music movements.}
}