AI-Assisted Treatment for Residual Speech Sound Disorders

Обзор

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.

Подробное описание

Artificial Intelligence-assisted treatment that detects mispronunciations within an evidence-based motor learning framework could increase access to sufficiently intense, efficacious treatment despite provider shortages. A successful Artificial intelligencesystem that can predict the clinical gold standard of trained listeners' perceptions could not only improve access to clinical care but also mitigate known confounds to accurate clinical feedback, including clinical experience and drift due to increasing familiarity between the speaker and listener. The Artificial intelligence tool used in this study includes a speech classifier trained to predict clinician judgment of American English "r" that is integrated into an existing evidence-based treatment software called Speech Motor Chaining.

Вмешательства

• Поведенческое Speech-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 i
• Поведенческое Artificial 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 co

Первичные конечные точки

• Change in percent correct for the /ɹ/ sound in untreated words, rated by blinded listeners. [Срок оценки: Before the initiation of treatment and again 5 weeks later.]

Вторичные конечные точки (6)

• Retention of percent correct for the /ɹ/ sound in untreated words, rated by blinded listeners. [Срок оценки: Before the initiation of treatment and again 10 weeks later.]
• Change in percent correct for the /ɹ/ sound in untreated words, rated by blinded listeners. [Срок оценки: After 5 weeks of treatment and again 10 weeks later.]
• Survey evaluating impacts of speech disorder on participants' social, emotional, and academic well-being. [Срок оценки: Before the initiation of treatment and again 5 weeks later.]
• Change in percent correct for the /ɹ/ sound in practiced words, rated by blinded listeners. [Срок оценки: Before the initiation of treatment and again 5 weeks later.]
• Change in percent correct for the /ɹ/ sound in practiced words, rated by blinded listeners. [Срок оценки: Before the initiation of treatment and again 10 weeks later.]
• Change in percent correct for the /ɹ/ sound in practiced words, rated by blinded listeners. [Срок оценки: After 5 weeks of treatment and again 10 weeks later.]

Критерии участия

Критерии включения

• 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

Критерии исключения

• 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.

Критерии приведены из реестра в оригинале (на английском). Окончательную оценку соответствия проводит исследовательский центр.

Здоровые добровольцы: Да

Дизайн исследования

Распределение

Рандомизированное

Модель

Параллельные группы

Маскирование

Простое слепое

Основная цель

Лечение

Центры проведения

США · 1 центр

• Syracuse University — Syracuse

Идентификаторы

NCT: NCT05988515 · 22-426b · 1R01DC020959-01

Первоисточники (государственные реестры)

• ClinicalTrials.gov (NIH, США)

Открыть это исследование на ClinicalTrials.gov ↗