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Detection of hypernasality based on vowel space area
A.K. Dubey, A. Tripathi, , S. Dandapat
Published in Acoustical Society of America
2018
PMID: 29857767
Volume: 143
   
Issue: 5
Pages: EL412 - EL417
Abstract
This study proposes a method for differentiating hypernasal-speech from normal speech using the vowel space area (VSA). Hypernasality introduces extra formant and anti-formant pairs in vowel spectrum, which results in shifting of formants. This shifting affects the size of the VSA. The results show that VSA is reduced in hypernasal-speech compared to normal speech. The VSA feature plus Mel-frequency cepstral coefficient feature for support vector machine based hypernasality detection leads to an accuracy of 86.89% for sustained vowels and 89.47%, 90.57%, and 91.70% for vowels in contexts of high pressure consonants /k/, /p/, and /t/, respectively. © 2018 Acoustical Society of America.
About the journal
JournalJournal of the Acoustical Society of America
PublisherAcoustical Society of America
ISSN00014966