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.
& Khudanpur, S
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UNVERDICTED 2representative citing papers
Truncated SSL backbone with logistic classifier detects audio deepfakes on-device, claimed to outperform AASIST by 10% while running 40% faster, packaged as a browser plugin.
citing papers explorer
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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.
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Detecting Audio Deepfakes on the Edge:Lightweight SSL-Based Detection in a Browser Plugin
Truncated SSL backbone with logistic classifier detects audio deepfakes on-device, claimed to outperform AASIST by 10% while running 40% faster, packaged as a browser plugin.