Detection of hypernasality based on vowel space area

J Acoust Soc Am. 2018 May;143(5):EL412. doi: 10.1121/1.5039718.

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.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Child
  • Cleft Palate / physiopathology*
  • Female
  • Humans
  • Male
  • Phonetics*
  • Speech Acoustics*
  • Speech Intelligibility / physiology*
  • Speech Perception / physiology*
  • Speech Production Measurement / methods*