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Commercial voice assistants are largely feminized and associated with stereotypically feminine traits such as warmth and submissiveness.
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A crowd-based evaluation of abuse response strategies in conversational agents
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Intelligent Voice Instructor-Assistant System for Collaborative and Interactive Classes
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Female by Default?–Exploring the Effect of Voice Assistant Gender and Pitch on Trait and Trust Attribution. In Extended Abstracts of the 2021 CHI Conference on Human Factors in Computing Systems . 1–7
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EQUALS Skills Coalition UNESCO. 2019 · 2021
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The effect of gender stereotypes on artificial intelligence recommendations
Jungyong Ahn, Jungwon Kim, and Yongjun Sung. 2022 · 2022
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Form Follows Function: Designing For Tensions Of Conversational Agents In Service Encounters
Andreas Bucher, Dario Staehelin, Mateusz Dolata, and Gerhard Schwabe. 2022 · 2022
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Owning Mistakes Sincerely: Strategies for Mitigating AI Errors. In CHI Conference on Human Factors in Computing Systems . 1–11
Amama Mahmood, Jeanie W Fung, Isabel Won, and Chien-Ming Huang. 2022 · 2022
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Does Social Presence Increase Perceived Competence? Evaluating Conversational Agents in Advice Giving Through a Video-Based Survey
Damaris Schmid, Dario Staehelin, Andreas Bucher, Mateusz Dolata, and Gerhard Schwabe. 2022 · 2022
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Modeling human response to robot errors for timely error detection. In 2022 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS) . IEEE, 676–683
Maia Stiber, Russell Taylor, and Chien-Ming Huang. 2022 · 2022
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It’s not what you say but how you say it: Examining the influence of perceived voice assistant gender and pitch on trust and reliance
Kylie L Goodman and Christopher B Mayhorn. 2023 · 2023
Closest in time.
On using social signals to enable flexible error-aware HRI. In Proceedings of the 2023 ACM/IEEE International Conference on Human-Robot Interaction . 222–230
Maia Stiber, Russell H Taylor, and Chien-Ming Huang. 2023 · 2023
Closest in time.