Analysis of engagement behavior in children during dyadic interactions using prosodic cues

Computer Speech and Language(2016)

引用 26|浏览24
暂无评分
摘要
Child engagement is defined as the interaction of a child with his/her environment in a contextually appropriate manner. Engagement behavior in children is linked to socio-emotional and cognitive state assessment with enhanced engagement identified with improved skills. A vast majority of studies however rely solely, and often implicitly, on subjective perceptual measures of engagement. Access to automatic quantification could assist researchers/clinicians to objectively interpret engagement with respect to a target behavior or condition, and furthermore inform mechanisms for improving engagement in various settings. In this paper, we present an engagement prediction system based exclusively on vocal cues observed during structured interaction between a child and a psychologist involving several tasks. Specifically, we derive prosodic cues that capture engagement levels across the various tasks. Our experiments suggest that a child's engagement is reflected not only in the vocalizations, but also in the speech of the interacting psychologist. Moreover, we show that prosodic cues are informative of the engagement phenomena not only as characterized over the entire task (i.e., global cues), but also in short term patterns (i.e., local cues). We perform a classification experiment assigning the engagement of a child into three discrete levels achieving an unweighted average recall of 55.8% (chance is 33.3%). While the systems using global cues and local level cues are each statistically significant in predicting engagement, we obtain the best results after fusing these two components. We perform further analysis of the cues at local and global levels to achieve insights linking specific prosodic patterns to the engagement phenomenon. We observe that while the performance of our model varies with task setting and interacting psychologist, there exist universal prosodic patterns reflective of engagement.
更多
查看译文
关键词
Classifier decision fusion,Engagement,Global level cues,Local level cues,Prosody
AI 理解论文
溯源树
样例
生成溯源树,研究论文发展脉络
Chat Paper
正在生成论文摘要