To what extent can ASV systems naturally defend against spoofing attacks?
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arXiv
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| Autori principali: | , , , , , , , , |
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| Natura: | Preprint |
| Pubblicazione: |
2024
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| _version_ | 1866929594532102144 |
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| author | Jung, Jee-weon Wang, Xin Evans, Nicholas Watanabe, Shinji Shim, Hye-jin Tak, Hemlata Arora, Sidhhant Yamagishi, Junichi Chung, Joon Son |
| author_facet | Jung, Jee-weon Wang, Xin Evans, Nicholas Watanabe, Shinji Shim, Hye-jin Tak, Hemlata Arora, Sidhhant Yamagishi, Junichi Chung, Joon Son |
| contents | The current automatic speaker verification (ASV) task involves making binary decisions on two types of trials: target and non-target. However, emerging advancements in speech generation technology pose significant threats to the reliability of ASV systems. This study investigates whether ASV effortlessly acquires robustness against spoofing attacks (i.e., zero-shot capability) by systematically exploring diverse ASV systems and spoofing attacks, ranging from traditional to cutting-edge techniques. Through extensive analyses conducted on eight distinct ASV systems and 29 spoofing attack systems, we demonstrate that the evolution of ASV inherently incorporates defense mechanisms against spoofing attacks. Nevertheless, our findings also underscore that the advancement of spoofing attacks far outpaces that of ASV systems, hence necessitating further research on spoofing-robust ASV methodologies. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2406_05339 |
| institution | arXiv |
| publishDate | 2024 |
| record_format | arxiv |
| spellingShingle | To what extent can ASV systems naturally defend against spoofing attacks? Jung, Jee-weon Wang, Xin Evans, Nicholas Watanabe, Shinji Shim, Hye-jin Tak, Hemlata Arora, Sidhhant Yamagishi, Junichi Chung, Joon Son Audio and Speech Processing Artificial Intelligence The current automatic speaker verification (ASV) task involves making binary decisions on two types of trials: target and non-target. However, emerging advancements in speech generation technology pose significant threats to the reliability of ASV systems. This study investigates whether ASV effortlessly acquires robustness against spoofing attacks (i.e., zero-shot capability) by systematically exploring diverse ASV systems and spoofing attacks, ranging from traditional to cutting-edge techniques. Through extensive analyses conducted on eight distinct ASV systems and 29 spoofing attack systems, we demonstrate that the evolution of ASV inherently incorporates defense mechanisms against spoofing attacks. Nevertheless, our findings also underscore that the advancement of spoofing attacks far outpaces that of ASV systems, hence necessitating further research on spoofing-robust ASV methodologies. |
| title | To what extent can ASV systems naturally defend against spoofing attacks? |
| topic | Audio and Speech Processing Artificial Intelligence |
| url | https://arxiv.org/abs/2406.05339 |