Representation and classi cation of unvoiced sounds using adaptive
نویسندگان
چکیده
In this paper, we describe a method to represent and classify unvoiced sounds using the concept of super wavelets. Super wavelet is a linear combination of wavelets that itself can be treated as a wavelet. Since unvoiced sounds are high frequency and noise like, we use Daubechies' wavelet of order three to generate the super wavelet. The parameters of the wavelet for representation and classiication of unvoiced sounds are generated using neural networks. Even though this paper address the problems of both signal representation and classiication, emphasis is on classiication problem since some kind of classiier is needed to select the wavelet coeecients which contain the most information for discriminating between the classes. We demonstrate the applicability of this method for the representation and classiication of unvoiced sounds with representative examples.
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