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Audio content description with wavelets and neural nets

S. Rein, M. Reisslein, T. Sikora
2004 IEEE International Conference on Acoustics, Speech, and Signal Processing  
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
more » ... ned by only three independent example sets obtains a success rate of approximately 78% in identifying unknown complex classical music movements.
doi:10.1109/icassp.2004.1326833 dblp:conf/icassp/ReinRS04 fatcat:t3tceotoczahhg6moze76y6gdm