Deaf and hard-of-hearing users' prioritization of genres of online video content requiring accurate captions

Abstract

Online video is an important information source, yet its pace of growth, including user-submitted content, is so rapid that automatic captioning technologies are needed to make content accessible for people who are Deaf or Hard-of-Hearing (DHH). To support future creation of a research dataset of online videos, we must prioritize which genres of online video content DHH users believe are of greatest importance to be accurately captioned. Our first contribution is to validate that the Best-Worst Scaling (BWS) methodology is able to accurately gather judgments on this topic by conducting an in-person study with 25 DHH users, using a card-sorting methodology to rank the importance for various YouTube genres of online video to be accurately captioned. Our second contribution is to identify video genres of highest captioning importance via an online survey with 151 DHH individuals, and those participants highly ranked: News and Politics, Education, and Technology and Science.