I Hear, Therefore I Trust: A Socio-Technical Investigation of Humans as Synthetic Speech Detectors
Fuente:
arXiv
Gespeichert in:
| Hauptverfasser: | , |
|---|---|
| Format: | Preprint |
| Veröffentlicht: |
2026
|
| Schlagworte: | |
| Online-Zugang: | |
| Tags: |
Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
|
| _version_ | 1866914607151448064 |
|---|---|
| author | Erscoi, Lelia Kinnunen, Tomi |
| author_facet | Erscoi, Lelia Kinnunen, Tomi |
| contents | Automatic deepfake detection has received considerable research attention, yet the socio-technical environment in which humans actually encounter synthetic speech remains poorly understood. We investigate voice deepfake detection as a perceptual and contextual process, presenting a localization task in which 47 participants marked suspected synthetic segments across authentic, fully synthetic, and partially synthetic utterances under three manipulated trust cues: instructional framing, affective priming, and provenance labeling. Participants provided quality ratings on mechanicalness, expressiveness, intelligibility, clarity, calmness, and confidence of evaluation. Utterance class was the primary determinant of detection accuracy and perceptual quality; trust cues produced no main effects but motivated detection behavior. Fully synthetic speech was detected at below-chance levels. Quality ratings tracked utterance type, indicating implicit discrimination where overt detection failed. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2605_28064 |
| institution | arXiv |
| publishDate | 2026 |
| record_format | arxiv |
| spellingShingle | I Hear, Therefore I Trust: A Socio-Technical Investigation of Humans as Synthetic Speech Detectors Erscoi, Lelia Kinnunen, Tomi Audio and Speech Processing Artificial Intelligence Human-Computer Interaction Automatic deepfake detection has received considerable research attention, yet the socio-technical environment in which humans actually encounter synthetic speech remains poorly understood. We investigate voice deepfake detection as a perceptual and contextual process, presenting a localization task in which 47 participants marked suspected synthetic segments across authentic, fully synthetic, and partially synthetic utterances under three manipulated trust cues: instructional framing, affective priming, and provenance labeling. Participants provided quality ratings on mechanicalness, expressiveness, intelligibility, clarity, calmness, and confidence of evaluation. Utterance class was the primary determinant of detection accuracy and perceptual quality; trust cues produced no main effects but motivated detection behavior. Fully synthetic speech was detected at below-chance levels. Quality ratings tracked utterance type, indicating implicit discrimination where overt detection failed. |
| title | I Hear, Therefore I Trust: A Socio-Technical Investigation of Humans as Synthetic Speech Detectors |
| topic | Audio and Speech Processing Artificial Intelligence Human-Computer Interaction |
| url | https://arxiv.org/abs/2605.28064 |