TD-VIM creates signal-level morphed voice samples that achieve G-MAP attack success rates up to 99.74% against deep-learning and commercial speaker verification systems.
In2018 IEEE international conference on acoustics, speech and signal processing (ICASSP), 4779–4783 (IEEE, 2018)
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Time-Domain Voice Identity Morphing (TD-VIM): A Signal-Level Approach to Morphing Attacks on Speaker Verification Systems
TD-VIM creates signal-level morphed voice samples that achieve G-MAP attack success rates up to 99.74% against deep-learning and commercial speaker verification systems.