A noninvasive estimation of hypernasality using a linear predictive model.

Abstract

The pronunciation of a speaker with a defective soft palate is marked by hypernasality and an operation may be necessary to repair the defective soft palate to reduce this hypernasality. An assessment of hypernasality is necessary to quantify the effect of the surgery. The current clinical methods for assessing hypernasality are uncomfortable or require expensive equipment. In this paper, a new quantitative method is proposed to estimate hypernasality. This method requires only a microphone and a personal computer equipped with a sound card. Zeros in the frequency response of the vocal tract system are one of the major characteristics of hypernasality. The proposed method made use of the fact that a linear predictive model with a typical order for the human vocal tract system is not accurate when the vocal tract system has zeros in its frequency response. Hypernasality was estimated by comparing the distance between the sequences of linear predictive cepstrum of low- and high-order linear predictive models. The proposed method provides a better correlation (0.58) with nasalance measured by a nasometer than Teager method (0.44) for all the data. Furthermore, the proposed method showed higher correlation of 0.84 than 0.71 of the Teager method for data with a nasalance higher than 35%. Since the proposed method needs only digitized speech data, it is much less invasive and provides an easy and cost-effective evaluation of hypernasality.