Attitudes Toward Signing Avatars Vary Depending on Hearing Status, Age of Signed Language Acquisition, and Avatar Type - Quandt, Lorna C.; Willis, Athena; Schwenk, Melody; Weeks, Kaitlyn; Ferster, Ruthie (Frontiers in Psychology, 2022)
The use of virtual humans (i.e., avatars) holds the potential for inte ractive, automated interaction in domains such as remote communication , customer service, or public announcements. For signed language users , signing avatars could potentially provide accessible content by shar ing information in the signer’s preferred or native language. As the d evelopment of signing avatars has gained traction in recent years, res earchers have come up with many different methods of creating signing avatars. The resulting avatars vary widely in their appearance, the na turalness of their movements, and facial expressions—all of which may potentially impact users’ acceptance of the avatars. We designed a stu dy to test the effects of these intrinsic properties of different sign ing avatars while also examining the extent to which people’s own lang uage experiences change their responses to signing avatars. We created video stimuli showing individual signs produced by 1) a live human si gner (Human), 2) an avatar made using computer-synthesized animation ( CS Avatar), and 3) an avatar made using high-fidelity motion capture ( Mocap avatar). We surveyed 191 American Sign Language users, including Deaf (N = 83), Hard-of-Hearing (N = 34), and Hearing (N= 67) groups. Participants rated the three signers on multiple dimensions, which wer e then combined to form ratings of Attitudes, Impressions, Comprehensi on, and Naturalness. Analyses demonstrated that the Mocap avatar was r ated significantly more positively than the CS avatar on all primary v ariables. Correlations revealed that signers who acquire sign language later in life are more accepting and likely to have positive impressi ons of signing avatars. Finally, those who learned ASL earlier were mo re likely to give lower, more negative ratings to the CS avatar, but w e did not see this association for the Mocap avatar or the Human signe r. Together, these findings suggest that movement quality and appearan ce significantly impact users’ ratings of signing avatars and show tha t signed language users with earlier age of ASL acquisition are the mo st sensitive to movement quality issues seen in computer-generated ava tars. We suggest that future efforts to develop signing avatars consid er retaining the fluid movement qualities integral to signed languages .
Keywords: Avatars; Björn-2026-02-22; Deaf; Signing avatars; sign language; virtual humans