mlsanityData to 7 Oct 2026

To what extent can ASV systems naturally defend against spoofing attacks?

arXiv 2406.05339 ↗First posted 8 Jun 2024eess.AS cs.AIcited by 1

Not on the map. Why?

Abstract (arXiv)

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.

Key facts. Cited by 1 paper in the map (data through 7 Oct 2026). Builds on 24 of its 40 references that are in the map. First posted on arXiv 8 Jun 2024.

Builds on

24 of 40 references.

References · 24

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12 more
  1. 2021How do Voices from Past Speech Synthesis Challenges Compare Today?cited by 21
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  6. 2023Towards single integrated spoofing-aware speaker verification embeddingscited by 7
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  8. 2022Baseline Systems for the First Spoofing-Aware Speaker Verification Challenge: Score and Embedding Fusioncited by 6
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  10. 2023The ID R&D VoxCeleb Speaker Recognition Challenge 2023 System Descriptioncited by 4
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  12. 2023Can spoofing countermeasure and speaker verification systems be jointly optimised?cited by 1

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Citing papers per year: 2024: 1.

1 paper.

  1. 2024SpoofCeleb: Speech Deepfake Detection and SASV In The Wildcited by 22