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Gender and accent stereotypes in communication with an intelligent virtual assistant
Lee, Sun Kyong
Lee, Sun Kyong
Abstract
People are using intelligent virtual assistants (IVAs) more than ever before. Today's IVAs can be customized with unique voices including both gender and accent cues. Following evidence that people treat others differently based on their gender and accent, we ask: How do gender and accent of Siri, an IVA, affect users' trust? Students from two institutions (N = 270) participated in a two (Siri's voice gender: male or female) by two (Siri's voice accent: American or Indian) by two (task type: social or functional) fully crossed experiment, including a supplemental quasi-experimental condition for gender match between participants’ and Siri's voice. Results show little effect for gender or accent alone, but the functional tasks condition received higher ratings in reliability, understandability, and faith dimensions of trust. Interactions reveal nuanced effects regarding gender match and varying across accent types. Implications for human-machine communication, in particular differences between human-human and human-machine interaction scripts are presented.
Description
Date
2025-1
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Volume Title
Publisher
Elsevier BV
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Archive Status
This item contains archived web content.
Files
Piercy et al., 2025, IJHCIMP_GenderandAccent.pdf
Adobe PDF, 568.48 KB
- Embargoed until 2028-03-09
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Keywords
Intelligent virtual assistant, Trust, Accents, Stereotype, Gender, Experiment
Citation
Piercy, C. W., Montgomery-Vestecka, G., & Lee, S. K. (2025). Gender and Accent Stereotypes in Communication with an Intelligent Virtual Assistant. International Journal of Human-Computer Studies, 103407. https://doi.org/10.1016/j.ijhcs.2024.103407