arxiv
PublishedJuly 27, 2026 at 4:00 AM
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Probing Speaker Identity Sensitivity in Audio Deepfake Detectors
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arXiv:2607.21820v1 Announce Type: cross Abstract: Audio deepfake detectors are trained to distinguish genuine speech from synthetic speech and often perform well on standard benchmarks. Yet the same detector that achieves less than 1% error on one dataset can see its error rate increase twentyfold w
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Originally published on arxiv ↗