People are poorly equipped to detect AI-powered voice clones
Sarah Barrington, Emily A. Cooper, Hany Farid
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-generated voice to be the same as its real counterpart approximately [Formula: see text] of the time, and correctly identified a voice as AI generated only about [Formula: see text] of the time.
Topics & Concepts
NaturalnessIdentity (music)Computer scienceSpeech recognitionPerceptionRealismMatching (statistics)Human voiceGenerative grammarArtificial intelligencePsychologyMedicineAestheticsVisual artsArtNeurosciencePhysicsPathologyQuantum mechanicsGenerative Adversarial Networks and Image SynthesisSpeech Recognition and SynthesisTopic Modeling