Automated Video Description for Blind and Low Vision Users
Aditya Bodi, Pooyan Fazli, Shasta Ihorn, Yue-Ting Siu, Andrew Taylor Scott, Lothar Narins, Yash Kant, Abhishek Das, Ilmi Yoon
Abstract
Video accessibility is crucial for blind and low vision users for equitable engagements in education, employment, and entertainment. Despite the availability of professional description services and tools for amateur description, most human-generated descriptions are expensive and time consuming, and the rate of human-generated descriptions simply cannot match the speed of video production. To overcome the increasing gaps in video accessibility, we developed a system to automatically generate descriptions for videos and answer blind and low vision users’ queries on the videos. Results from a pilot study with eight blind video aficionados indicate the promise of this system for meeting needs for immediate access to videos and validate our efforts in developing tools in partnership with the individuals we aim to benefit. Though the results must be interpreted with caution due to the small sample size, participants overall reported high levels of satisfaction with the system, and all preferred use of the system over no support at all.