A Study on the Consonant Classification Using Fuzzy Inference

퍼지추론을 이용한 한국어 자음분류에 관한 연구

This paper proposes algorithm in order to classify Korean consonant phonemes same as polosives, fricatives affricates into la sounds, glottalized sounds, aspirated sounds. This three kinds of sounds are one of distinctive characters of the Korean language which don't eist in language same as English. This is thesis on classfication of 14 Korean consonants(k, t, p, s, c, k', t', p', s', c', kh, ph, ch) as a previous stage for Korean phone recognition. As feature sets for classification, LPC cepstral analysis. The eperiments are two stages. First, using short-time speech signal analysis and Mahalanobis distance, consonant segments are detected from original speech signal, then the consonants are classified by fuzzy inference. As the results of computer simulations, the classification rate of the speech data was come to 93.75%.