  Previous research underscored the potential of danmaku--a text-based
commenting feature on videos--in engaging hearing audiences. Yet, for many Deaf
and hard-of-hearing (DHH) individuals, American Sign Language (ASL) takes
precedence over English. To improve inclusivity, we introduce "Signmaku," a new
commenting mechanism that uses ASL, serving as a sign language counterpart to
danmaku. Through a need-finding study (N=12) and a within-subject experiment
(N=20), we evaluated three design styles: real human faces, cartoon-like
figures, and robotic representations. The results showed that cartoon-like
signmaku not only entertained but also encouraged participants to create and
share ASL comments, with fewer privacy concerns compared to the other designs.
Conversely, the robotic representations faced challenges in accurately
depicting hand movements and facial expressions, resulting in higher cognitive
demands on users. Signmaku featuring real human faces elicited the lowest
cognitive load and was the most comprehensible among all three types. Our
findings offered novel design implications for leveraging generative AI to
create signmaku comments, enriching co-learning experiences for DHH
individuals.
