期刊名称：International Journal of Advanced Computer Science and Applications(IJACSA)
印刷版ISSN：2158-107X
电子版ISSN：2156-5570
出版年度：2016
卷号：7
期号：9
DOI：10.14569/IJACSA.2016.070928
出版社：Science and Information Society (SAI)
摘要：Hypernasality (HP) is observed across voiced phonemes uttered by Cleft-Palate (CP) speakers with defective velopharyngeal (VP) opening. HP assessment using signal processing technique is challenging due to the variability of acoustic features across various conditions such as speakers, speaking style, speaking rate, severity of HP etc. Most of the study for hypernasality (HP) assessment is based on isolated sustained vowels under laboratory conditions. We measure the variability of acoustic features and detect HP using vowel /i/, /a/ and /u/ in continuous read speech with gradually increasing severity of HP of CP speakers. Linear predictive coding (LPC) method is used for acoustic feature extraction. In first part of our study, we observe the variation in acoustic parameters within and across vowel category with gradually increasing HP. We observe that inter-speaker variability in spectral features among CP subjects for vowel /i/ is 0.96, /a/ has 1.13 and vowel /u/ has 2.05. The inter-speaker variability measurement suggests that high back vowel /u/ is mostly affected and has the highest variability. High front vowel /i/ is least affected and has the lowest variability with HP. In the second part, ratio of vowel space area (VSA) of hypernasal and normal speech is calculated and used as a measure for HP detection. We observe that VSA spanned by CP subjects is 0.65 times less than isolated uttered Bangla nasal VSA and 0.43 times less than read speech uttered English oral VSA.
