arXiv:2605.26136v1 Announce Type: cross Abstract: 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%. Participants are not worse at detecting synthesis artifac
The rapid advancement in audio deepfake technology necessitates assessing its societal impact, especially as these technologies become more accessible and sophisticated.
This study quantifies a significant erosion of trust in real human speech, posing a fundamental challenge to societal communication, evidence, and public discourse.
Human listeners are becoming significantly less accurate at identifying real speech, indicating a rising skepticism that will alter how audio information is perceived and verified.
- · Deepfake detection companies
- · Cybersecurity firms
- · Digital watermarking technologies
- · Journalism and media
- · Judicial systems reliant on audio evidence
- · Individuals requiring verified communication
Increased demand for robust authentication and verification tools for audio content.
Potential for systematic disinformation campaigns to become more difficult to counteract due to widespread public skepticism.
Long-term erosion of interpersonal and institutional trust if objective reality becomes increasingly difficult to discern across media.
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Read at arXiv cs.AI