Psychophysiological Arousal in Young Children Who Stutter: An Interpretable AI Approach
Psychophysiological Arousal in Young Children Who Stutter: An Interpretable AI Approach
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DOI：
10.1145/3550326
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发表时间：
2022-08
影响因子：
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通讯作者：
Harshit Sharma;Y. Xiao;V. Tumanova;Asif Salekin
中科院分区：
文献类型：
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作者：
Harshit Sharma;Y. Xiao;V. Tumanova;Asif Salekin
这项首次提出的研究有效地识别并可视化了学龄前儿童在两种具有挑战性的条件下，在有知觉地流利地说话时，发生口吃(CWS)和不口吃(CWNS)时，生理唤醒的每秒模式的差异：在有压力的情况下说话和叙述。第一种情况可能会因为高唤醒而影响儿童的言语；后者对说话人提出了语言、认知和交际要求。我们收集了70名儿童在两种目标状态下的生理参数数据。首先，我们采用了一种新的通道多实例学习(MI-MIL)方法来有效地对不同条件下的CWS和CWN进行分类。这个分类器的评估解决了四个关键的研究问题，这些问题与最先进的语音科学研究的兴趣相一致。稍后，我们利用Shap分类器解释来可视化CWS在群体/组级别和个性化级别独有的显著、细粒度和时间生理参数。群体水平的不同模式识别将增强我们对口吃病因和发展的理解，而个性化水平的识别将使我们能够远程、连续和实时地评估口吃儿童的生理觉醒，这可能导致个性化的、及时的干预，从而提高言语流利性。提出的MI-MIL方法新颖，可推广到不同的领域，可实时执行。最后，对多个数据集、提出的框架和几个基线进行了全面的评估，确定了对CWSS在言语产生过程中的生理唤醒的显著见解。
The presented first-of-its-kind study effectively identifies and visualizes the second-by-second pattern differences in the physiological arousal of preschool-age children who do stutter (CWS) and who do not stutter (CWNS) while speaking perceptually fluently in two challenging conditions: speaking in stressful situations and narration. The first condition may affect children's speech due to high arousal; the latter introduces linguistic, cognitive, and communicative demands on speakers. We collected physiological parameters data from 70 children in the two target conditions. First, we adopt a novel modality-wise multiple-instance-learning (MI-MIL) approach to classify CWS vs. CWNS in different conditions effectively. The evaluation of this classifier addresses four critical research questions that align with state-of-the-art speech science studies' interests. Later, we leverage SHAP classifier interpretations to visualize the salient, fine-grain, and temporal physiological parameters unique to CWS at the population/group-level and personalized-level. While group-level identification of distinct patterns would enhance our understanding of stuttering etiology and development, the personalized-level identification would enable remote, continuous, and real-time assessment of stuttering children's physiological arousal, which may lead to personalized, just-in-time interventions, resulting in an improvement in speech fluency. The presented MI-MIL approach is novel, generalizable to different domains, and real-time executable. Finally, comprehensive evaluations are done on multiple datasets, presented framework, and several baselines that identified notable insights on CWSs' physiological arousal during speech production.