English

Can We Use Speaker Recognition Technology to Attack Itself? Enhancing Mimicry Attacks Using Automatic Target Speaker Selection

Audio and Speech Processing 2018-11-12 v1 Computation and Language Machine Learning

Abstract

We consider technology-assisted mimicry attacks in the context of automatic speaker verification (ASV). We use ASV itself to select targeted speakers to be attacked by human-based mimicry. We recorded 6 naive mimics for whom we select target celebrities from VoxCeleb1 and VoxCeleb2 corpora (7,365 potential targets) using an i-vector system. The attacker attempts to mimic the selected target, with the utterances subjected to ASV tests using an independently developed x-vector system. Our main finding is negative: even if some of the attacker scores against the target speakers were slightly increased, our mimics did not succeed in spoofing the x-vector system. Interestingly, however, the relative ordering of the selected targets (closest, furthest, median) are consistent between the systems, which suggests some level of transferability between the systems.

Keywords

Cite

@article{arxiv.1811.03790,
  title  = {Can We Use Speaker Recognition Technology to Attack Itself? Enhancing Mimicry Attacks Using Automatic Target Speaker Selection},
  author = {Tomi Kinnunen and Rosa González Hautamäki and Ville Vestman and Md Sahidullah},
  journal= {arXiv preprint arXiv:1811.03790},
  year   = {2018}
}

Comments

(A slightly shorter version) has been submitted to IEEE ICASSP 2019

R2 v1 2026-06-23T05:09:56.737Z