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Sexualised synthetic personas encode and amplify gendered power asymmetries through voice

Alice Ross, Ariadna Sanchez, Elin Kanhov, Catherine Lai, Éva Székely

arXiv:2606.21366Published June 19, 2026Updated June 23, 20260 citations
  • eess.AS
  • cs.AI
  • cs.CL

Abstract

This work examines sexualised AI-generated English-speaking voices offered by a popular commercial platform. New technologies may enable sexual empowerment and greater diversity in gender expression, yet toxic masculinity, heteronormativity, and the abuse of women and LGBTQ+ people remain pervasive online. Drawing on a Feminist HCI perspective, we examine how commercial voice AI systems reproduce and circulate particular performances of gender. We conducted a listening experiment with a diverse group of listeners, combining quantitative adjective selection, qualitative free-text responses, and acoustic analysis. Participants evaluated male- and female-coded voices presented with either sexualised scripts or neutral text. Results reveal a narrow range of gender expression, largely binary and heteronormative. Female-coded voices are more frequently described using sexualised and submissive terms, while male-coded voices are more often associated with dominance and positive traits.

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