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From Scores to Evidence: Auditable Decisions Can Improve Speech Deepfake Detection

arXiv · AI, language, vision and robotics · article · Sep 8, 2026 · UTC

Speech deepfakes can mimic a speaker's voice convincingly enough to deceive listeners and automated systems. This has driven strong progress in speech deepfake detection, but most detectors still end with one score per utterance. That score is useful for ranking systems, yet it says little about why a borderline item should be trusted, deferred, or reviewed. Two utterances can fall in the same score band for different reasons, for example because passive and retrieval evidence disagree or because the keyed probe is unavailable. We ask whether the final decision can remain scalar without discar

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Evidence & attribution

First collected: 2026-09-20T20:02:11.508Z. This is not the publication date.