Identification of Individual Cattle Using Vocalization Despite Intra-individual Variation in Acoustic Features
Yua Nishio, Kazuya Tsubokura, Shusuke Kojima, S. Sato, Makoto Morishita, Yurie Iribe · IEEJ Transactions on Electronics Information and Systems · 2024
Individual identification methods using ICT are required to reduce the workload of dairy farmers. Our research focuses on animal vocalizations as one of the resources useful for individual identification. In previous studies, the vocalizations during only hunger periods have been targeted. However, variations in acoustic information due to environmental and physiological differences may adversely affect individual identification. In this paper, we extract various kinds of acoustic information considering intra-individual differences of cattle and clear the acoustic differences in vocalizations between cattle states to identify individuals. As a result of the statistical tests, significant differences in acoustic information were observed between the hungry and estrus periods, revealing that cows exhibit acoustic variations depending on their states. We also conducted individual identification using i-vector and x-vector to account for such differences. The results showed that the x-vector achieved an accuracy of 92.2%. The x-vector demonstrated robustness, confirming its resilience to intra-individual differences.