Artificial Intelligence-Assisted Speech Therapy for /ɹ/: A Single-Case Experimental Study

• Published in: American journal of speech-language pathology Vol. 33; no. 5; p. 2461
• Main Authors: Benway, Nina R, Preston, Jonathan L
• Format: Journal Article
• Language: English
• Published: United States 18-09-2024
• Subjects: Adolescent; Artificial Intelligence; Child; Feasibility Studies; Female; Humans; Male; Phonetics; Speech Production Measurement - methods; Speech Sound Disorder - diagnosis; Speech Sound Disorder - therapy; Speech Therapy - methods; Therapy, Computer-Assisted - methods; Treatment Outcome; Young Adult
• ISSN: 1558-9110
• DOI: 10.1044/2024_AJSLP-23-00448

This feasibility trial describes changes in rhotic production in residual speech sound disorder following ten 40-min sessions including artificial intelligence (AI)-assisted motor-based intervention with ChainingAI, a version of Speech Motor Chaining that predicts clinician perceptual judgment using the PERCEPT-R Classifier (Perceptual Error Rating for the Clinical Evaluation of Phonetic Targets). The primary purpose is to evaluate /ɹ/ productions directly after practice with ChainingAI versus directly before ChainingAI and to evaluate how the overall AI-assisted treatment package may lead to perceptual improvement in /ɹ/ productions compared to a no-treatment baseline phase.
Five participants ages 10;7-19;3 (years;months) who were stimulable for /ɹ/ participated in a multiple (no-treatment)-baseline ABA single-case experiment. Prepractice activities were led by a human clinician, and drill-based motor learning practice was automated by ChainingAI. Study outcomes were derived from masked expert listener perceptual ratings of /ɹ/ from treated and untreated utterances recorded during baseline, treatment, and posttreatment sessions.
Listeners perceived significantly more rhoticity in practiced utterances after 30 min of ChainingAI, without a clinician, than directly before ChainingAI. Three of five participants showed significant generalization of /ɹ/ to untreated words during the treatment phase compared to the no-treatment baseline. All five participants demonstrated statistically significant generalization of /ɹ/ to untreated words from pretreatment to posttreatment. PERCEPT-clinician rater agreement (i.e., F1 score) was largely within the range of human-human agreement for four of five participants. Survey data indicated that parents and participants felt hybrid computerized-clinician service delivery could facilitate at-home practice.
This study provides evidence of participant improvement for /ɹ/ in untreated words in response to an AI-assisted treatment package. The continued development of AI-assisted treatments may someday mitigate barriers precluding access to sufficiently intense speech therapy for individuals with speech sound disorders.
https://doi.org/10.23641/asha.26662807.