Caption-Occlusion Severity Judgments across Live-television Genres from Deaf and Hard-of-hearing Viewers
Abstract
Prior work has revealed that Deaf and Hard of Hearing (DHH) viewers are concerned about captions occluding other onscreen content, e.g. text or faces, especially for live television programming, for which captions are generally not manually placed. To support evaluation or placement of captions for several genres of live television, empirical evidence is needed on how DHH viewers prioritize onscreen information, and whether this varies by genre. Nineteen DHH participants rated the importance of various onscreen content regions across 6 genres - News, Interviews, Emergency Announcements, Political Debates, Weather News, and Sports. Importance of content regions varied significantly across several genres, motivating genre-specific caption placement. We also demonstrate how the dataset informs creation of importance-weights for a metric to predict the severity of captions occluding onscreen content. This metric correlated significantly better to 23 DHH participants’ judgements of caption quality, compared to a metric with uniform importance-weights of content regions.
Akhter Al Amin
Software Engineer at Amazon
Saad Hassan
Assistant Professor
My research interests include human-computer interaction (HCI), accessibility, and computational social science.
