Phonetic and Lexical Discovery of a Canine Language using HuBERT
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arXiv
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| Autores principales: | , , , , |
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| Formato: | Preprint |
| Publicado: |
2024
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| Materias: | |
| Acceso en línea: | |
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| _version_ | 1866911783876296704 |
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| author | Li, Xingyuan Wang, Sinong Xie, Zeyu Wu, Mengyue Zhu, Kenny Q. |
| author_facet | Li, Xingyuan Wang, Sinong Xie, Zeyu Wu, Mengyue Zhu, Kenny Q. |
| contents | This paper delves into the pioneering exploration of potential communication patterns within dog vocalizations and transcends traditional linguistic analysis barriers, which heavily relies on human priori knowledge on limited datasets to find sound units in dog vocalization. We present a self-supervised approach with HuBERT, enabling the accurate classification of phoneme labels and the identification of vocal patterns that suggest a rudimentary vocabulary within dog vocalizations. Our findings indicate a significant acoustic consistency in these identified canine vocabulary, covering the entirety of observed dog vocalization sequences. We further develop a web-based dog vocalization labeling system. This system can highlight phoneme n-grams, present in the vocabulary, in the dog audio uploaded by users. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2402_15985 |
| institution | arXiv |
| publishDate | 2024 |
| record_format | arxiv |
| spellingShingle | Phonetic and Lexical Discovery of a Canine Language using HuBERT Li, Xingyuan Wang, Sinong Xie, Zeyu Wu, Mengyue Zhu, Kenny Q. Sound Computation and Language Machine Learning Audio and Speech Processing This paper delves into the pioneering exploration of potential communication patterns within dog vocalizations and transcends traditional linguistic analysis barriers, which heavily relies on human priori knowledge on limited datasets to find sound units in dog vocalization. We present a self-supervised approach with HuBERT, enabling the accurate classification of phoneme labels and the identification of vocal patterns that suggest a rudimentary vocabulary within dog vocalizations. Our findings indicate a significant acoustic consistency in these identified canine vocabulary, covering the entirety of observed dog vocalization sequences. We further develop a web-based dog vocalization labeling system. This system can highlight phoneme n-grams, present in the vocabulary, in the dog audio uploaded by users. |
| title | Phonetic and Lexical Discovery of a Canine Language using HuBERT |
| topic | Sound Computation and Language Machine Learning Audio and Speech Processing |
| url | https://arxiv.org/abs/2402.15985 |