Abstract
How animals communicate and whether they have languages is a persistent curiosity of human beings. However, the study of animal communications has been largely restricted to data from field recordings or in a controlled environment, which is expensive and limited in scale and variety. In this paper, we take domestic Shiba Inu dogs as an example, and extract their vocal communications from large amount of YouTube videos of Shiba Inu dogs. We classify these clips into different scenarios and locations, and further transcribe the audio into phonetically symbolic scripts through a systematic process. We discover consistent phonetic symbols among their expressions, which indicates that Shiba Inu dogs can have systematic verbal communication patterns. This reusable framework produces the first-of-its-kind Shiba Inu vocal communication dataset that will be valuable to future research in both zoology and linguistics.- Anthology ID:
- 2023.findings-acl.869
- Volume:
- Findings of the Association for Computational Linguistics: ACL 2023
- Month:
- July
- Year:
- 2023
- Address:
- Toronto, Canada
- Editors:
- Anna Rogers, Jordan Boyd-Graber, Naoaki Okazaki
- Venue:
- Findings
- SIG:
- Publisher:
- Association for Computational Linguistics
- Note:
- Pages:
- 13819–13832
- Language:
- URL:
- https://aclanthology.org/2023.findings-acl.869
- DOI:
- 10.18653/v1/2023.findings-acl.869
- Cite (ACL):
- Jieyi Huang, Chunhao Zhang, Mengyue Wu, and Kenny Zhu. 2023. Transcribing Vocal Communications of Domestic Shiba lnu Dogs. In Findings of the Association for Computational Linguistics: ACL 2023, pages 13819–13832, Toronto, Canada. Association for Computational Linguistics.
- Cite (Informal):
- Transcribing Vocal Communications of Domestic Shiba lnu Dogs (Huang et al., Findings 2023)
- PDF:
- https://preview.aclanthology.org/nschneid-patch-5/2023.findings-acl.869.pdf