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

Tomi Kinnunen 1 Rosa González Hautamäki 1 Ville Vestman 1 Md Sahidullah 2
2 MULTISPEECH - Speech Modeling for Facilitating Oral-Based Communication
Inria Nancy - Grand Est, LORIA - NLPKD - Department of Natural Language Processing & Knowledge Discovery
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
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Pré-publication, Document de travail
(A slightly shorter version) has been submitted to IEEE ICASSP 2019. 2018
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https://hal.inria.fr/hal-01937767
Contributeur : Md Sahidullah <>
Soumis le : mercredi 28 novembre 2018 - 11:29:12
Dernière modification le : jeudi 17 janvier 2019 - 16:33:24

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  • HAL Id : hal-01937767, version 1

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Tomi Kinnunen, Rosa González Hautamäki, Ville Vestman, Md Sahidullah. Can We Use Speaker Recognition Technology to Attack Itself? Enhancing Mimicry Attacks Using Automatic Target Speaker Selection. (A slightly shorter version) has been submitted to IEEE ICASSP 2019. 2018. 〈hal-01937767〉

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