Peculiarities of Wiener Class Systems and their Exploitation for Speech Signal Prediction
AbstractIn this paper Wiener class system consisting of infinite impulse response dynamic subsystem and sigmoid nonlinearity is employed for speech modelling. The experiments on Lithuanian vowel "ū" with different initial phase of the signal are done. The average of mean square errors of prediction with the Wiener system model are smaller approximately by 18 % for the training dataset, 17 % for the validation dataset and 14 % for the testing dataset in comparison to Linear Prediction Coding model. Additional experiments with 6 different Lithuanian vowels on average showed more than 13 % improvement in MSE of prediction with the Wiener system model. Moreover, the use of Wiener system instead of IIR model showed improvement in MSE of long-term prediction for five Lithuanian vowels on average by more than 5 %. Application of results in telecommunication systems could possibly decrease data transfer rates, increase speech intelligibility and naturalness of speech synthesis. Ill. 5, bibl. 8, tabl. 2 (in English; abstracts in English and Lithuanian).
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