Shreejata Gupta


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CHICA: A Developmental Corpus of Child-Caregiver’s Face-to-face vs. Video Call Conversations in Middle Childhood
Dhia Elhak Goumri | Abhishek Agrawal | Mitja Nikolaus | Hong Duc Thang Vu | Kübra Bodur | Elias Emmar | Cassandre Armand | Chiara Mazzocconi | Shreejata Gupta | Laurent Prévot | Benoit Favre | Leonor Becerra-Bonache | Abdellah Fourtassi
Proceedings of the 2024 Joint International Conference on Computational Linguistics, Language Resources and Evaluation (LREC-COLING 2024)

Existing studies of naturally occurring language-in-interaction have largely focused on the two ends of the developmental spectrum, i.e., early childhood and adulthood, leaving a gap in our knowledge about how development unfolds, especially across middle childhood. The current work contributes to filling this gap by introducing CHICA (for Child Interpersonal Communication Analysis), a developmental corpus of child-caregiver conversations at home, involving groups of French-speaking children aged 7, 9, and 11 years old. Each dyad was recorded twice: once in a face-to-face setting and once using computer-mediated video calls. For the face-to-face settings, we capitalized on recent advances in mobile, lightweight eye-tracking and head motion detection technology to optimize the naturalness of the recordings, allowing us to obtain both precise and ecologically valid data. Further, we mitigated the challenges of manual annotation by relying – to the extent possible – on automatic tools in speech processing and computer vision. Finally, to demonstrate the richness of this corpus for the study of child communicative development, we provide preliminary analyses comparing several measures of child-caregiver conversational dynamics across developmental age, modality, and communicative medium. We hope the current corpus will allow new discoveries into the properties and mechanisms of multimodal communicative development across middle childhood.