Benway Nina R, Preston Jonathan L
Department of Electrical and Computer Engineering, University of Maryland, College Park, MD.
Department of Communication Sciences and Disorders, Syracuse University, NY.
Am J Speech Lang Pathol. 2024 Sep 18;33(5):2461-2486. doi: 10.1044/2024_AJSLP-23-00448. Epub 2024 Aug 22.
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.
本可行性试验描述了在进行十次40分钟的训练课程后，残留语音障碍中卷舌音发音的变化，这些课程包括使用ChainingAI进行的基于人工智能（AI）辅助运动的干预，ChainingAI是语音运动链的一个版本，它使用PERCEPT-R分类器（用于语音目标临床评估的感知错误评分）预测临床医生的感知判断。主要目的是评估在使用ChainingAI训练后与使用ChainingAI训练前直接比较的/ɹ/发音情况，并评估与无治疗基线期相比，整体AI辅助治疗方案如何可能导致/ɹ/发音的感知改善。
五名年龄在10岁7个月至19岁3个月之间、对/ɹ/有反应的参与者参加了一项多（无治疗）基线ABA单病例实验。预训练活动由一名人类临床医生指导，基于训练的运动学习练习由ChainingAI自动化。研究结果来自于在基线期、治疗期和治疗后期记录的经过治疗和未经过治疗的话语中，由蒙面专家听众对/ɹ/的感知评分。
与使用ChainingAI训练前直接比较，在没有临床医生参与的情况下，使用ChainingAI训练30分钟后，听众在练习话语中感知到的卷舌音明显更多。与无治疗基线期相比，五名参与者中有三名在治疗阶段表现出/ɹ/对未治疗单词的显著泛化。所有五名参与者在从治疗前到治疗后的过程中，都表现出/ɹ/对未治疗单词的统计学显著泛化。对于五名参与者中的四名，PERCEPT-临床医生评分者一致性（即F1分数）在很大程度上处于人与人之间一致性的范围内。调查数据表明，家长和参与者认为混合计算机化-临床医生服务提供方式有助于在家练习。
本研究提供了证据，证明参与者在接受AI辅助治疗方案后，未治疗单词中的/ɹ/发音得到改善。AI辅助治疗的持续发展可能有一天会减轻阻碍语音障碍患者获得足够强化语音治疗的障碍。
