AI RESEARCH

Eroding Trust in Real Speech: A Large-Scale Study of Human Audio Deepfake Perception

arXiv CS.AI

ArXi:2605.26136v1 Announce Type: cross Audio deepfakes have improved rapidly recently, yet their effect on human trust in real speech remains unstudied. We present the largest listening study on audio deepfake perception to date, collecting 35,532 judgments from 1,768 participants across 138 text-to-speech and voice conversion systems. Our central finding is a skepticism shift: compared to a 2021 baseline, human accuracy on fake samples barely changed (72.9% to 71.2%), but accuracy on real samples dropped from 72.7% to 64.1.