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

, , , and . ICASSP, page 6146-6150. IEEE, (2019)

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Can We Use Speaker Recognition Technology to Attack Itself? Enhancing Mimicry Attacks Using Automatic Target Speaker Selection., , , and . ICASSP, page 6146-6150. IEEE, (2019)Automatic versus human speaker verification: The case of voice mimicry., , , and . Speech Commun., (2015)I-vectors meet imitators: on vulnerability of speaker verification systems against voice mimicry., , , , and . INTERSPEECH, page 930-934. ISCA, (2013)Articulation During Voice Disguise: A Pilot Study., , , , and . SPECOM, volume 12997 of Lecture Notes in Computer Science, page 680-691. Springer, (2021)Can We Use Speaker Recognition Technology to Attack Itself? Enhancing Mimicry Attacks Using Automatic Target Speaker Selection., , , and . CoRR, (2018)Automatic voice activity detection in different speech applications., , and . e-Forensics, page 12. ICST/ACM, (2008)Why Did the x-Vector System Miss a Target Speaker? Impact of Acoustic Mismatch Upon Target Score on VoxCeleb Data., and . INTERSPEECH, page 4313-4317. ISCA, (2020)Age-Related Voice Disguise and its Impact on Speaker Verification Accuracy., , , and . Odyssey, page 277-282. ISCA, (2016)Acoustical and perceptual study of voice disguise by age modification in speaker verification., , , and . Speech Commun., (2017)Robust Voice Liveness Detection and Speaker Verification Using Throat Microphones., , , , , , and . IEEE ACM Trans. Audio Speech Lang. Process., 26 (1): 44-56 (2018)