The Manipulative Power of Voice Characteristics: Investigating Deceptive Patterns in Mandarin Chinese Female Synthetic Speech
Pervasive voice interaction enables deceptive patterns through subtle voice characteristics, yet empirical investigation into this manipulation lags behind, especially within major non-English language contexts. Addressing this gap, our study presents the first systematic investigation into voice characteristic-based dark patterns employing female synthetic voices in Mandarin Chinese. This focus is crucial given the prevalence of female personas in commercial assistants and the prosodic significance in the Chinese language. Guided by the conceptual framework identifying key influencing factors, we systematically evaluate effectiveness variations by manipulating voice characteristics (five characteristics, three intensities) across different scenarios (shopping vs. question-answering) with different commercial aims. A preliminary study (N=24) validated the experimental materials and the main study (N=36) revealed significant behavioral manipulation (up to +2027.6%). Crucially, the analysis showed that effectiveness varied significantly with voice characteristics and scenario, mediated by user perception (of tone, intonation, timbre) and user demographics (individual preferences, though limited demographic impact). These interconnected findings offer evidence-based insights for ethical design.
Authors
- Hewu Li (ORCID: https://orcid.org/0000-0002-6331-6542)
- Shuning Zhang (ORCID: https://orcid.org/0000-0002-4145-117X)
- Yuanyuan Wu
- Xin Yi (ORCID: https://orcid.org/0000-0001-8041-7962)
- Shixuan Li (ORCID: https://orcid.org/0009-0008-6828-6347)
- Y M Wang
- Y. Xu (ORCID: https://orcid.org/0009-0004-9774-9129)
- Han Chen
- Jiaqi Bai (ORCID: https://orcid.org/0009-0003-9792-3556)
- Chunhui Wang
Institutions
- Shanghai Jiao Tong University (CN)
- China Astronaut Research and Training Center (CN)
- Wuhan Institute of Technology (CN)
- Tsinghua University (CN)
Publication Details
- Journal
- Proceedings of the ACM on Interactive Mobile Wearable and Ubiquitous Technologies
- Published
- 2025-09-03
- DOI
- https://doi.org/10.1145/3749510
- Primary Topic
- Hate Speech and Cyberbullying Detection
- Type
- article
- Field-Weighted Citation Impact
- 0.00
Funders
- National Key Laboratory of Human Factors Engineering
- National Natural Science Foundation of China