我听见，故我信任：人类作为合成语音检测器的社会技术研究
I Hear, Therefore I Trust: A Socio-Technical Investigation of Humans as Synthetic Speech Detectors
AI总结：
通过定位任务实验，研究人类在感知和语境中检测语音深度伪造的能力，发现话语类别是检测准确性和感知质量的主要决定因素，信任线索无主效应但影响检测行为，完全合成语音的检测低于随机水平。
摘要：
自动深度伪造检测已受到大量研究关注，然而人类实际遇到合成语音的社会技术环境仍知之甚少。我们将语音深度伪造检测作为感知和语境过程进行研究，呈现一个定位任务，其中47名参与者在三种操纵的信任线索下（指导框架、情感启动和来源标注）标记真实、完全合成和部分合成话语中的疑似合成片段。参与者提供了关于机械性、表现力、可懂度、清晰度、平静度和评估自信度的质量评分。话语类别是检测准确性和感知质量的主要决定因素；信任线索未产生主效应，但激发了检测行为。完全合成语音的检测低于随机水平。质量评分与话语类型相关，表明在显性检测失败时存在隐性区分。
英文摘要：
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.
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