Video accessibility is essential for people with visual impairments.
Audio descriptions describe what is happening on-screen, e.g., physical actions, facial expressions, and scene changes. Generating highquality audio descriptions requires a lot of manual description
generation [50]. To address this accessibility obstacle, we built a
system that analyzes the audiovisual contents of a video and generates the audio descriptions. The system consisted of three modules:
AD insertion time prediction, AD generation, and AD optimization.
We evaluated the quality of our system on five types of videos by
conducting qualitative studies with 20 sighted users and 12 users
who were blind or visually impaired. Our findings revealed how
audio description preferences varied with user types and video
types. Based on our study’s analysis, we provided recommendations for the development of future audio description generation
technologies.