A Data-driven Approach to the Longitudinal Study of Canine Vocal Pattern Development

摘要

Longitudinal studies of animal vocalizations provide crucial insights into developmental patterns and communicative evolution. To aid such investigations in canines, this paper introduces the Canine Age Transition Vocalization Dataset, a large-scale collection of dog vocalizations featuring meticulously verified metadata (including precise birthdate, breed, and individual dog ID) for 125 dogs across 6 common breeds. Our in-depth longitudinal analysis of this dataset then reveals novel findings on how key vocal parameters, encompassing defined bark types and finer-grained acoustic components (Elemental Dog Bark Units, or EDBUs), change as dogs mature. This work, therefore, offers both a significant new resource and foundational data that enable deeper, more nuanced investigations into the lifelong vocal development of dogs and other animal communication.