People are poorly equipped to detect AI-powered voice clones

October 03, 2024 Β· Declared Dead Β· πŸ› Scientific Reports

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Authors Sarah Barrington, Emily A. Cooper, Hany Farid arXiv ID 2410.03791 Category cs.HC: Human-Computer Interaction Cross-listed cs.AI, cs.CY, cs.SD, eess.AS Citations 30 Venue Scientific Reports Last Checked 4 months ago
Abstract
As generative artificial intelligence (AI) continues its ballistic trajectory, everything from text to audio, image, and video generation continues to improve at mimicking human-generated content. Through a series of perceptual studies, we report on the realism of AI-generated voices in terms of identity matching and naturalness. We find human participants cannot consistently identify recordings of AI-generated voices. Specifically, participants perceived the identity of an AI-voice to be the same as its real counterpart approximately 80% of the time, and correctly identified a voice as AI generated only about 60% of the time.
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