Abstract

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.

Highlights

  • Speech is the acoustic end product of the thoughts which is originated in the brain

  • This study explores the variation in acoustic parameters and HP assessment in read speech with gradually increasing VP opening of caused by physical defects (CP) speakers

  • This paper examines the variability of CP speakers characteristics using Linear predictive coding (LPC) based acoustic features for HP assessment measured by vowel space area (VSA) in read speech

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Summary

INTRODUCTION

Disordered speech in which speech quality is reduced may hamper normal communication. A specific example of a vocal tract dysfunction that reduces the speech quality is defective VP mechanism [2] which can be caused by physical defects (CP) [3]. Voice pathologies are usually diagnosed by invasive techniques using different instruments which may bring discomfort to the patients. This is not recommended by health physicians as they can produce psychological stress in patients. Acoustic features contain information regarding voice source and vocal tract behavior. Any abnormality in speech arising from physical defect may be assessed appropriately using speech features of vocal tract or voice source.

ACOUSTIC ANALYSIS OF SPEECH
SPEECH MATERIALS
Preprocessing of the Speech Signal
LPC Analysis Technique
Acoustic Analysis
Variability of Acoustic Features
Variability of VSA and HP Assessment
CONCLUSION
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