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
–arXiv.org Artificial Intelligence
The current automatic speaker verification (ASV) task involves making binary decisions on two types of trials: target and nontarget. 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 Figure 1: Average Spoof Equal Error Rates (SPF-EERs) on 29 against spoofing attacks. Nevertheless, our findings also different spoofing attacks, chronologically displayed using eight underscore that the advancement of spoofing attacks far outpaces automatic speaker verification (ASV) systems. The SPF-EER that of ASV systems, hence necessitating further research adopts spoof trials in place of conventional non-target trials, on spoofing-robust ASV methodologies.
arXiv.org Artificial Intelligence
Jun-14-2024
- Country:
- North America > United States (0.28)
- Genre:
- Research Report (1.00)
- Industry:
- Information Technology > Security & Privacy (1.00)
- Technology: