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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 threedoi:10.1109/icassp.2004.1326833 dblp:conf/icassp/ReinRS04 fatcat:t3tceotoczahhg6moze76y6gdm