RecruitingNot ApplicableNCT05988515

AI-Assisted Treatment for Residual Speech Sound Disorders


Sponsor

Syracuse University

Enrollment

26 participants

Start Date

Sep 5, 2024

Study Type

INTERVENTIONAL

Conditions

Summary

The goal of this randomized-controlled trial is to determine how artificial intelligence-assisted home practice may enhance speech learning of the "r" sound in school-age children with residual speech sound disorders. All child participants will receive 1 speech lesson per week, via telepractice, for 5 weeks with a human speech-language clinician. Some participants will receive 3 speech sessions per week with an Artificial Intelligence (AI)-clinician during the same 5 weeks as the human clinician sessions (CONCURRENT treatment order group), whereas others will receive 3 speech sessions per week with an AI-clinician after the human clinician sessions end (SEQUENTIAL treatment order group.


Eligibility

Min Age: 9 YearsMax Age: 17 Years

Inclusion Criteria13

  • Must speak a rhotic dialect of American English as a dominant language.
  • Must have begun learning English by at least the age of 3 years.
  • Must be between 9;0 to 17;11 years of age.
  • Must have reported difficulty with /ɹ/ production.
  • Must have reported hearing within normal limits.
  • Must receive a Scaled Score of 5 or above on both the Listening Comprehension and Story Retelling subtests from the Test of Integrated Language \& Literacy Skills (TILLS).
  • Must receive a percentile score of 8 or below on the Goldman-Fristoe Test of Articulation-3 (GFTA-3) Sounds in Words subtest.
  • Must have 1 scorable response with 5+ consecutive correct /pataka/ with \> 3.4 syllables per second in the MRR-Tri task of the Maximum Performance Tasks OR must demonstrate no childhood apraxia of speech (CAS-only) features in BOTH articulatory and rate/prosody domains of the ProCAD.
  • Must score \<40% accurate based on word-level items from our /ɹ/ probe list.
  • Must score \>=15% accuracy on /ɹ/ on 45 syllables following Dynamic Assessment.
  • Must express interest in changing their /ɹ/ production.
  • Must have oral structure and function that are appropriate for /ɹ/ production.
  • Must have access to broadband internet with videoconferencing capabilities

Exclusion Criteria5

  • Must have no known history of autism spectrum disorder, Down Syndrome, cerebral palsy, intellectual disability, permanent hearing loss, epilepsy/antiepileptic medication, or brain injury/neurosurgery/stroke.
  • Must not have diagnosis of attention deficit disorder, attention deficit hyperactivity disorder, Tourette's, or Obsessive-compulsive disorder.
  • Must have no orthodontic appliances that block the roof of the mouth (e.g., palate expanders).
  • Must not have current cleft palate, fluency disorder, or voice disorder.
  • Must not demonstrate childhood apraxia of speech (CAS-only) features in BOTH articulatory and rate/prosody domains of the ProCAD.

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Interventions

BEHAVIORALSpeech-Language Pathologist-led Speech Motor Chaining

Sessions begin with Pre-practice to elicit the /r/ sound. During Structured Practice, the same utterance is practiced several times in a row (with systematic increases in difficulty based on performance). Our web-based software manipulates the principles of motor learning, including feedback prompts for the clinician, the complexity of the utterance, and the variability in the practice trial; the software will analyze the clinician's rating to increase the difficulty of practice when the child is more accurate. Randomized Practice will also be guided by the software and includes all linguistic levels that were produced correctly during Structured Practice, with items presented in random order. A trained speech-language pathologist is involved in all practice trials to provide feedback throughout the session.

BEHAVIORALArtificial Intelligence-led Speech Motor Chaining (CHAINING-AI)

Sessions include Structured Practice and Randomized Practice using our web-based software with an Artificial Intelligence clinician to address the /r/ sound. Within a practice session, participants speak into a microphone, and the audio file is sent to a server to be analyzed by a classifier, which returns a binary accurate/inaccurate rating of productions in a fashion similar to SLP judgment. Our web-based software manipulates the principles of motor learning, including feedback prompts, the complexity of the utterance, and the variability in the practice trial. The software will analyze the child's accuracy as determined by the classifier to increase the difficulty of practice when the child is more accurate.


Locations(1)

Syracuse University

Syracuse, New York, United States

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NCT05988515


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