Assessment of hypernasality for children with cleft palate based on cepstrum analysis

Hypernasality is a frequently occurring resonance disorder in children with cleft palate. In general, an operation is necessary to reduce the hypernasality and therefore an assessment of hypernasality is imperative to quantify the effect of the surgery and design the speech therapy sessions, which are crucial after surgery. In this paper, a new quantitative method is proposed to estimate hypernasality. The proposed method used the fact that an autoregressive (AR) model for vocal tract system of a patient with hypernasal speech is not accurate; because of the zeros appear in the frequency response of the vocal tract system. Therefore in our method, hypernasality was estimated by a quantity calculated from comparing the distance between the sequences of cepstrum coefficients extracted from AR model and autoregressive moving average model. K-means and Bayes theorem were utilized to classify the utterances of subjects by means of proposed index. We achieved the accuracy up to 81.12% on utterances and 97.14% on subjects. Since the proposed method needs only computer processing of speech data, compared with other clinical methods it provides a simple evaluation of hypernasality.