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Abstruct・ Sophisticatedpr, ∞edures and fast analyzing method have been n民 dedfor analyzing也estop consonants. Because the features ofthe stop consonants are involved in 血eshort transitional portion between出e∞nsonantand the vowel segments. An adaptive signal processing algorithm only needs a simple procedure. Moreover, a fast∞nvergmg adaptive algorithm is obtained by utilizing the ASA method which is improved by authors The estimated parameters are converted into the critical band spectra which are useful for reco伊lZmgsp田 ch.And,出ecritical band spectra are converted into dynamic critical band spectra with time-varying characteristics. 百lesespectra are inputted into a thr田・layered neural network for recognizing the stop∞nsonants.In出ispaper, an improving method of the learning properties of the neural network is also described.

Recognition of Stop Consonants Using Dynamic Critical Band Spectra and Neural Network