Results from using automatic speech recognition in cleft speech therapy with children

Zachary Rubin, Sri Kurniawan, Travis Tate Tollefson

Research output: Chapter in Book/Report/Conference proceedingConference contribution

5 Scopus citations

Abstract

Most children with cleft are required to undertake speech therapy after undergoing surgery to repair their craniofacial defect. However, the untrained ear of a parent can lead to incorrect practice resulting in the development of compensatory structures. Even worse, the boring nature of the cleft speech therapy often causes children to abandon home exercises and therapy altogether. We have developed a simple recognition system capable of detecting impairments on the phoneme level with high accuracy. We embed this into a game environment and provide it to a cleft palate specialist team for pilot testing with children 2 to 5 years of age being evaluated for speech therapy. The system consistently detected cleft speech in high-pressure consonants in 3 out of our 5 sentences. Doctors agreed that this would improve the quality of therapy outside of the office. Children enjoyed the game overall, but grew bored due to the delays of phrase-based speech recognition.

Original languageEnglish (US)
Title of host publicationLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
PublisherSpringer Verlag
Pages283-286
Number of pages4
Volume8548 LNCS
EditionPART 2
ISBN (Print)9783319085982
DOIs
Publication statusPublished - 2014
Event14th International Conference on Computers Helping People with Special Needs, ICCHP 2014 - Paris, France
Duration: Jul 9 2014Jul 11 2014

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
NumberPART 2
Volume8548 LNCS
ISSN (Print)03029743
ISSN (Electronic)16113349

Other

Other14th International Conference on Computers Helping People with Special Needs, ICCHP 2014
CountryFrance
CityParis
Period7/9/147/11/14

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Keywords

  • Child Speech Therapy
  • Therapeutic Games

ASJC Scopus subject areas

  • Computer Science(all)
  • Theoretical Computer Science

Cite this

Rubin, Z., Kurniawan, S., & Tollefson, T. T. (2014). Results from using automatic speech recognition in cleft speech therapy with children. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (PART 2 ed., Vol. 8548 LNCS, pp. 283-286). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 8548 LNCS, No. PART 2). Springer Verlag. https://doi.org/10.1007/978-3-319-08599-9_43