Designing and Experimentally Evaluating a Video-based American Sign Language Look-up System

Abstract

Despite some prior research and commercial systems, if someone sees an unfamiliar American Sign Language (ASL) word and wishes to look up its meaning in a dictionary, this remains a difficult task. There is no standard label a user can type to search for a sign, and formulating a query based on linguistic properties is challenging for students learning ASL. Advances in sign-language recognition technology will soon enable the design of a search system for ASL word look-up in dictionaries, by allowing users to generate a query by submitting a video of themselves performing the word they believe they encountered somewhere. Users would then view a results list of video clips or animations, to seek the desired word. In this research, we are investigating the usability of such a proposed system, a webcam-based ASL dictionary system, using a Wizard-of-Oz prototype and enhanced the design so that it can support sign language word look-up even when the performance of the underlying sign-recognition technology is low. We have also investigated the requirements of students learning ASL in regard to how results should be displayed and how a system could enable them to filter the results of the initial query, to aid in their search for a desired word. We compared users’ satisfaction when using a system with or without post-query filtering capabilities. We discuss our upcoming study to investigate users’ experience with a working prototype based on actual sign-recognition technology that is being designed. Finally, we discuss extensions of this work to the context of users searching datasets of videos of other human movements, e.g. dance moves, or when searching for words in other languages.

Saad Hassan

Assistant Professor

My research interests include human-computer interaction (HCI), accessibility, and computational social science.