Speech Sound Disorder
Conditions
Brief 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.
Detailed description
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.
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.
Sponsors
National Institutes of Health (NIH)
State University of New York - Upstate Medical University
National Institute on Deafness and Other Communication Disorders (NIDCD)
Syracuse University
Study design
Allocation
RANDOMIZED
Intervention model
PARALLEL
Primary purpose
TREATMENT
Masking
SINGLE (Outcomes Assessor)
Masking description
All perceptual ratings will be obtained from trained listeners who are blinded to treatment group and to timepoint. Binary rating of accuracy of the r sound (i.e., judgments of correct or incorrect) will be obtained from three listeners per token.
Intervention model description
Participants will be randomized across two conditions, CONCURRENT and SEQUENTIAL Participants randomized to receive CONCURRENT treatment will receive speech lessons with a human clinician once per week for five weeks, along with 3 sessions per week of parent-supervised Chaining-AI (15 Chaining-AI sessions). Therefore, clinician-led and Chaining-AI are completed concurrently. Participants randomized to receive SEQUENTIAL treatment will receive speech lessons with a human clinician once per week for five weeks, followed by three sessions per week of parent-supervised Chaining-AI for the NEXT five weeks. Therefore, clinician-led and Chaining-AI are completed sequentially.
Eligibility
Sex/Gender
ALL
Age
9 Years to 17 Years
Healthy volunteers
Yes
Inclusion criteria
* 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 criteria
* 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.
Design outcomes
Primary
| Measure | Time frame | Description |
|---|---|---|
| Change in percent correct for the /ɹ/ sound in untreated words, rated by blinded listeners. | Before the initiation of treatment and again 5 weeks later. | To assess generalization of treatment gains to untreated words, participants will read a word list eliciting /ɹ/. Stimuli in each list will be presented individually in randomized order. Individual words will be isolated from the audio record of each word probe and presented in randomized order for perceptual rating by trained listeners who are blind to treatment condition and time point (but will see the written representation of each target word). We will use the change in percent correct as our primary measure of perceptually rated accuracy. |
Secondary
| Measure | Time frame | Description |
|---|---|---|
| Retention of percent correct for the /ɹ/ sound in untreated words, rated by blinded listeners. | Before the initiation of treatment and again 10 weeks later. | To assess generalization of treatment gains to untreated words, participants will read a word list eliciting /ɹ/. Stimuli in each list will be presented individually in randomized order. Individual words will be isolated from the audio record of each word probe and presented in randomized order for perceptual rating by trained listeners who are blind to treatment condition and time point (but will see the written representation of each target word). We will use the change in percent correct as our primary measure of perceptually rated accuracy. The timeframe of 10 weeks differs from the primary outcome of 5 weeks, and assesses longer-term retention and captures the effects after both groups have received both interventions. |
| Change in percent correct for the /ɹ/ sound in untreated words, rated by blinded listeners. | After 5 weeks of treatment and again 10 weeks later. | To assess generalization of treatment gains to untreated words, participants will read a word list eliciting /ɹ/. Stimuli in each list will be presented individually in randomized order. Individual words will be isolated from the audio record of each word probe and presented in randomized order for perceptual rating by trained listeners who are blind to treatment condition and time point (but will see the written representation of each target word). We will use the change in percent correct as our primary measure of perceptually rated accuracy. This timeframe compares the rate of improvement with Chaining-AI for the SEQUENTIAL group and the retention after a 5 week break for the CONCURRENT group. |
| Survey evaluating impacts of speech disorder on participants' social, emotional, and academic well-being. | Before the initiation of treatment and again 5 weeks later. | This survey asks parents and participants to report the impact of speech disorder on their child's/their social, emotional, and academic well-being along a 5-point scale. A higher score indicates a greater degree of negative impact of speech disorder on social, emotional, or academic well-being. |
| Change in percent correct for the /ɹ/ sound in practiced words, rated by blinded listeners. | Before the initiation of treatment and again 5 weeks later. | Participants will read word list eliciting /ɹ/ in practiced words to assess acquisition. Stimuli in each list will be presented individually in randomized order. Individual words will be isolated from the audio record of each word probe and presented in randomized order for perceptual rating by trained listeners who are blind to treatment condition and time point (but will see the written representation of each target word). We will use the change in percent correct as our primary measure of perceptually rated accuracy. |
Countries
United States
Contacts
Primary ContactJonathan Preston, PhD
Backup ContactNina Benway, PhD
Outcome results
None listed