mlsanityData to 13 Oct 2026

People are poorly equipped to detect AI-powered voice clones

arXiv 2410.03791 ↗First posted 3 Oct 2024cs.HC cs.AI cs.CYcited by 12

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Abstract (arXiv)

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.

Key facts. Cited by 12 papers in the map (data through 13 Oct 2026). Builds on 8 of its 17 references that are in the map. First posted on arXiv 3 Oct 2024.

Builds on

8 of 17 references.

References · 8

  1. 2022Robust Speech Recognition via Large-Scale Weak Supervisioncited by 4,004
  2. 2021TitaNet: Neural Model for speaker representation with 1D Depth-wise separable convolutions and global contextcited by 61
  3. 2021Deepfake Detection by Human Crowds, Machines, and Machine-informed Crowdscited by 58
  4. 2023Warning: Humans Cannot Reliably Detect Speech Deepfakescited by 20
  5. 2022Human Detection of Political Speech Deepfakes across Transcripts, Audio, and Videocited by 16
  6. 2021Human Perception of Audio Deepfakescited by 15
  7. 2022Testing Human Ability To Detect Deepfake Images of Human Facescited by 15
  8. 2023Single and Multi-Speaker Cloned Voice Detection: From Perceptual to Learned Featurescited by 10

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Cited by year (2026 to 13 Oct)

Citing papers per year: 2024: 1; 2025: 5; 2026: 6.

12 papers.

  1. 2025Characterizing Photorealism and Artifacts in Diffusion Model-Generated Imagescited by 13
  2. 2025"It's not a representation of me": Examining Accent Bias and Digital Exclusion in Synthetic AI Voice Servicescited by 9
  3. 2025TrueFake: A Real World Case Dataset of Last Generation Fake Images also Shared on Social Networkscited by 8
  4. 2024Human Action CLIPs: Detecting AI-generated Human Motioncited by 4
  5. 2025Distinguishing Task-Specific and General-Purpose AI in Regulationcited by 3
  6. 2025Curved Worlds, Clear Boundaries: Generalizing Speech Deepfake Detection using Hyperbolic and Spherical Geometry Spacescited by 1
  7. 2026XLSR-MamBo: Scaling the Hybrid Mamba-Attention Backbone for Audio Deepfake Detectioncited by 1
  8. 2026RealityTest: How People Probe AI Identity and Whether Models Disclose Itcited by 1
  9. 2026Speech Generation Speaker Poisoning: Capability Erasure in Zero-Shot Text-to-Speechcited by 0
  10. 2026CAREBench: A Child-Safety Risk Benchmark for Language Modelscited by 0
  11. 2026The Voiceprint Fallacy: Why Voices Are Not Unique Biometric Imprintscited by 0
  12. 2026A survey of AI-generated voices and their detectioncited by 0