Author:
Bodur Kübra,Nikolaus Mitja,Prévot Laurent,Fourtassi Abdellah
Abstract
Understanding children's conversational skills is crucial for understanding their social, cognitive, and linguistic development, with important applications in health and education. To develop theories based on quantitative studies of conversational development, we need (i) data recorded in naturalistic contexts (e.g., child-caregiver dyads talking in their daily environment) where children are more likely to show much of their conversational competencies, as opposed to controlled laboratory contexts which typically involve talking to a stranger (e.g., the experimenter); (ii) data that allows for clear access to children's multimodal behavior in face-to-face conversations; and (iii) data whose acquisition method is cost-effective with the potential of being deployed at a large scale to capture individual and cultural variability. The current work is a first step to achieving this goal. We built a corpus of video chats involving children in middle childhood (6–12 years old) and their caregivers using a weakly structured word-guessing game to prompt spontaneous conversation. The manual annotations of these recordings have shown a similarity in the frequency distribution of multimodal communicative signals from both children and caregivers. As a case study, we capitalize on this rich behavioral data to study how verbal and non-verbal cues contribute to the children's conversational coordination. In particular, we looked at how children learn to engage in coordinated conversations, not only as speakers but also as listeners, by analyzing children's use of backchannel signaling (e.g., verbal “mh” or head nods) during these conversations. Contrary to results from previous in-lab studies, our use of a more spontaneous conversational setting (as well as more adequate controls) revealed that school-age children are strikingly close to adult-level mastery in many measures of backchanneling. Our work demonstrates the usefulness of recent technology in video calling for acquiring quality data that can be used for research on children's conversational development in the wild.
Subject
Computer Science Applications,Computer Vision and Pattern Recognition,Human-Computer Interaction,Computer Science (miscellaneous)
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