Detecting the Undetectable: Human Judgments and the Challenge of Synthetic Voices
- Synthetic voices generated using artificial intelligence (AI) are becoming increasingly indistinguishable from human voices, raising important concerns about trust, deception, and detection in digital communication. This preliminary work synthesizes the current landscape of research on human perception in detecting synthetic voices. We reviewed 13 papers from databases including ACM, IEEE, Springer, and MDPI, and identified five main types of perceptual cues that users rely on to detect voice synthesis: Intuition/Gut Feeling, Liveliness, Emotions, Linguistic Features, and Acoustic and Environmental Features. Our findings highlight the need for further empirical user studies to better understand how individuals perceive and assess the risks posed by synthetic voices. Such research can inform both educational and regulatory strategies aimed at increasing awareness and mitigating the potential harms of synthetic voice technologies.
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| Document Type: | Conference Object |
|---|---|
| Language: | English |
| Author: | Sima Amirkhani, Gunnar Stevens, Md Shajalal, Alexander Boden |
| Parent Title (English): | Proceedings of the 12th International Conference on Communities & Technologies (C&T 2025), Siegen, Germany, 21–23 July, 2025 |
| Number of pages: | 6 |
| URN: | urn:nbn:de:hbz:1044-opus-91186 |
| DOI: | https://doi.org/10.48340/ct2025-1030 |
| Publisher: | European Society for Socially Embedded Technologies (EUSSET) |
| Publishing Institution: | Hochschule Bonn-Rhein-Sieg |
| Date of first publication: | 2025/07/16 |
| Funding: | This work was supported by the German Federal Ministry of Education and Research (BMBF) as part of the AntiScam project [13] (Grant NO. 16KIS2214). |
| Tag: | AI-generated speech; Human Perception; Synthetic voices; deception; detection cues; user studies; voice deepfakes |
| Departments, institutes and facilities: | Fachbereich Wirtschaftswissenschaften |
| Institut für Verbraucherinformatik (IVI) | |
| Projects: | AntiScam - Verbundprojekt: Abwehr von Conversational Scams zum Schutz der digitalen Identität von Verbraucher:innen (DE/BMFTR/16KIS2214) |
| Dewey Decimal Classification (DDC): | 0 Informatik, Informationswissenschaft, allgemeine Werke / 00 Informatik, Wissen, Systeme / 005 Computerprogrammierung, Programme, Daten |
| Entry in this database: | 2025/07/28 |
| Licence (German): |  Creative Commons - CC BY - Namensnennung 4.0 International |
