arXiv: cs.AI preprintsInternational5 November 2026
VIPBench: A Human-Aligned Benchmark for Voice Identity Perception in the Age of Voice Cloning
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arXiv:2611.05638v1 Announce Type: cross Abstract: Speaker-recognition benchmarks test how accurately a model recovers the speaker label of a recording, treating voice identity as a property of the person who produced it. However, these benchmarks do not evaluate how humans perceive voice identity. Whether a listener hears two voices as the same person has consequences for intellectual property rights, cybersecurity, and everyday life. We introduce the Voice Identity Perception benchmark (VIPBench), which contains 124,876 same-or-different judgments from 1,290 listeners on 9,800 recording pairs
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