Abstract

Entrainment is a social adaptive mechanism which in human spoken interaction includes interlocutors unconsciously adjusting their vocal patterns and related behaviors to match those of their conversation partner. Entrainment offers important insights toward understanding the socio-cognitive characteristics of an individual. Quantifying entrainment patterns can also inform clinical diagnosis, long-term monitoring, and individualized interventions in neuro-developmental disorders characterized by deficits in communication and social interaction, such as Autism Spectrum Disorder (ASD). In this work, we model vocal entrainment in dyadic child-inclusive conversations to analyze behavioral traits of children with and without an autism diagnosis. Specifically, we explore contrastive-learning based unsupervised modeling to learn representations related to entrainment from speech features. We validate the proposed …

Date

2026

Authors

Rimita Lahiri, So Hyun Kim, Somer Bishop, Catherine Lord, Helen Tager-Flusberg, Shrikanth Narayanan

Journal

Computer Speech & Language

Pages

101993

Publisher

Academic Press