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The paper describes one approach of the selection of the most indicative wavelets for each of the vowels in the author’s native language. Analysis is performed on the correct and incorrect vowels. On each of the sample multiresolution decomposition is applied. For each of the detail and approximation the most indicative wavelet is selected using value of the variance as the criteria. Some interesting results are obtained and biorthogonal wavelets have been select as the most appropriate for the multiresolution of the vowels. Using this criterion, any further analysis of the samples can be done using only coefficients of the discrete wavelet transformation on the level of approximation or any level of the detail, with enough guarantees that they are most appropriate for each vowel.
