Literature DB >> 31893680

Detection and assessment of hypernasality in repaired cleft palate speech using vocal tract and residual features.

Akhilesh Kumar Dubey1, S R Mahadeva Prasanna1, S Dandapat1.   

Abstract

The presence of hypernasality in repaired cleft palate (CP) speech is a consequence of velopharyngeal insufficiency. The coupling of the nasal tract with the oral tract adds nasal formant and antiformant pairs in the hypernasal speech spectrum. This addition deviates the spectral and linear prediction (LP) residual characteristics of hypernasal speech compared to normal speech. In this work, the vocal tract constriction feature, peak to side-lobe ratio feature, and spectral moment features augmented by low-order cepstral coefficients are used to capture the spectral and residual deviations for hypernasality detection. The first feature captures the lower-frequencies prominence in speech due to the presence of nasal formants, the second feature captures the undesirable signal components in the residual signal due to the nasal antiformants, and the third feature captures the information about formants and antiformants in the spectrum along with the spectral envelope. The combination of three features gives normal versus hypernasal speech detection accuracies of 87.76%, 91.13%, and 93.70% for /a/, /i/, and /u/ vowels, respectively, and hypernasality severity detection accuracies of 80.13% and 81.25% for /i/ and /u/ vowels, respectively. The speech data are collected from 30 control normal and 30 repaired CP children between the ages of 7 and 12.

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Year:  2019        PMID: 31893680     DOI: 10.1121/1.5134433

Source DB:  PubMed          Journal:  J Acoust Soc Am        ISSN: 0001-4966            Impact factor:   1.840


  3 in total

1.  A Deep Learning Algorithm for Objective Assessment of Hypernasality in Children With Cleft Palate.

Authors:  Vikram C Mathad; Nancy Scherer; Kathy Chapman; Julie M Liss; Visar Berisha
Journal:  IEEE Trans Biomed Eng       Date:  2021-09-20       Impact factor: 4.756

2.  Evaluation of noise excitation as a method for detection of hypernasality.

Authors:  Kat Young; Triona Sweeney; Rebecca R Vos; Felicity Mehendale; Helena Daffern
Journal:  Appl Acoust       Date:  2022-03-15       Impact factor: 2.639

Review 3.  Clinical Applications of Artificial Intelligence and Machine Learning in Children with Cleft Lip and Palate-A Systematic Review.

Authors:  Mohamed Zahoor Ul Huqh; Johari Yap Abdullah; Ling Shing Wong; Nafij Bin Jamayet; Mohammad Khursheed Alam; Qazi Farah Rashid; Adam Husein; Wan Muhamad Amir W Ahmad; Sumaiya Zabin Eusufzai; Somasundaram Prasadh; Vetriselvan Subramaniyan; Neeraj Kumar Fuloria; Shivkanya Fuloria; Mahendran Sekar; Siddharthan Selvaraj
Journal:  Int J Environ Res Public Health       Date:  2022-08-31       Impact factor: 4.614

  3 in total

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