@inproceedings{vega-hidalgo-etal-2025-acoustic,
    title = "Acoustic Individual Identification of White-Faced Capuchin Monkeys Using Joint Multi-Species Embeddings",
    author = "Vega-Hidalgo, {\'A}lvaro  and
      Abzaliev, Artem  and
      Bergman, Thore  and
      Mihalcea, Rada",
    editor = "Che, Wanxiang  and
      Nabende, Joyce  and
      Shutova, Ekaterina  and
      Pilehvar, Mohammad Taher",
    booktitle = "Proceedings of the 63rd Annual Meeting of the Association for Computational Linguistics (Volume 2: Short Papers)",
    month = jul,
    year = "2025",
    address = "Vienna, Austria",
    publisher = "Association for Computational Linguistics",
    url = "https://preview.aclanthology.org/mtsummit-25-ingestion/2025.acl-short.51/",
    doi = "10.18653/v1/2025.acl-short.51",
    pages = "645--659",
    ISBN = "979-8-89176-252-7",
    abstract = "Acoustic individual identification of wild animals is an essential task for understanding animal vocalizations within their social contexts, and for facilitating conservation and wildlife monitoring efforts. However, most of the work in this space relies on human efforts, as the development of methods for automatic individual identification is hindered by the lack of data. In this paper, we explore cross-species pre-training to address the task of individual classification in white-faced capuchin monkeys. Using acoustic embeddings from birds and humans, we find that they can be effectively used to identify the calls from individual monkeys. Moreover, we find that joint multi-species representations can lead to further improvements over the use of one representation at a time. Our work demonstrates the potential of cross-species data transfer and multi-species representations, as strategies to address tasks on species with very limited data."
}