R.I.P.
๐ป
Ghosted
Sexualised synthetic personas encode and amplify gendered power asymmetries through voice
June 19, 2026 ยท Grace Period ยท ๐ Interspeech 2026
Authors
Alice Ross, Ariadna Sanchez, Elin Kanhov, Catherine Lai, Eva Szekely
arXiv ID
2606.21366
Category
eess.AS: Audio & Speech
Cross-listed
cs.AI,
cs.CL
Citations
0
Venue
Interspeech 2026
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.
Community Contributions
Found the code? Know the venue? Think something is wrong? Let us know!
๐ Similar Papers
In the same crypt โ Audio & Speech
R.I.P.
๐ป
Ghosted
LPCNet: Improving Neural Speech Synthesis Through Linear Prediction
R.I.P.
๐ป
Ghosted
VoiceFilter: Targeted Voice Separation by Speaker-Conditioned Spectrogram Masking
R.I.P.
๐ป
Ghosted
TERA: Self-Supervised Learning of Transformer Encoder Representation for Speech
R.I.P.
๐ป
Ghosted
Mockingjay: Unsupervised Speech Representation Learning with Deep Bidirectional Transformer Encoders
R.I.P.
๐ป
Ghosted