Theron Wang


2024

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Phonetic and Lexical Discovery of Canine Vocalization
Theron Wang | Xingyuan Li | Chunhao Zhang | Mengyue Wu | Kenny Zhu
Findings of the Association for Computational Linguistics: EMNLP 2024

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”.