@inproceedings{wang-etal-2024-phonetic,
    title = "Phonetic and Lexical Discovery of Canine Vocalization",
    author = "Wang, Theron S.  and
      Li, Xingyuan  and
      Zhang, Chunhao  and
      Wu, Mengyue  and
      Zhu, Kenny Q.",
    editor = "Al-Onaizan, Yaser  and
      Bansal, Mohit  and
      Chen, Yun-Nung",
    booktitle = "Findings of the Association for Computational Linguistics: EMNLP 2024",
    month = nov,
    year = "2024",
    address = "Miami, Florida, USA",
    publisher = "Association for Computational Linguistics",
    url = "https://preview.aclanthology.org/fix-sig-urls/2024.findings-emnlp.816/",
    doi = "10.18653/v1/2024.findings-emnlp.816",
    pages = "13972--13983",
    abstract = "This paper attempts to discover communication patterns automatically within dog vocalizations in a data-driven approach, which breaks the barrier previous approaches that rely on human prior knowledge on limited data. We present a self-supervised approach with HuBERT, enabling the accurate classification of phones, and an adaptive grammar induction method that identifies phone sequence patterns that suggest a preliminary vocabulary within dog vocalizations. Our results show that a subset of this vocabulary has substantial causality relations with certain canine activities, suggesting signs of stable semantics associated with these ``words''."
}