Learning to Generate Understandable Animations of American Sign Language – Matt Huenerfauth (Rochester Institute of Technology)

November 7, 2014 all-day

Standardized testing has revealed that many deaf adults in the U.S. have lower levels of English literacy; therefore, providing American Sign Language (ASL) on websites can make information and services more accessible. Unfortunately, video recordings of human signers are difficult to update when information changes, and there is no way to support just-in-time generation of web content from a query. Software is needed that can automatically synthesize understandable animations of a virtual human performing ASL, based on an easy-to-update script as input. The challenge is for this software to select the details of such animations so that they are linguistically accurate, understandable, and acceptable to users. This software can also serve as the final surface realization component in future ASL generation or translation technologies. This talk will discuss Huenerfauth’s research at the intersection of the fields of computer accessibility, human computer interaction, and computational linguistics. His methodology includes: experimental evaluation studies with native ASL signers, motion-capture data collection from signers to collect a corpus of ASL, linguistic annotation of this corpus, statistical modeling techniques, and animation synthesis. In this way, his laboratory has found models that underlie the accurate and natural movements of virtual human characters performing ASL. His recent focus has been on how signers use 3D points in space and how this affects the hand-movements required for ASL verb signs, and in upcoming work, he is investigating technologies for supporting students who are learning ASL.

Matt Huenerfauth is an associate professor at The Rochester Institute of Technology (RIT) in the Golisano College of Computer and Information Sciences; his research focuses on the design of computer technology to benefit people who are deaf or have low levels of written-language literacy. He is an editor-in-chief of the ACM Transactions on Accessible Computing, the major journal in the field of computer accessibility for people with disabilities. Since 2007, Huenerfauth has secured over $2.1 million in external research funding to support his work, including a National Science Foundation CAREER Award in 2008. He has authored 40 peer-reviewed scientific journal articles, book chapters, and conference papers, and he has twice received the Best Paper Award at the ACM SIGACCESS Conference on Computers and Accessibility, the major computer science conference on assistive technology for people with disabilities. He served as the general chair for this conference in 2012 and is a member of the steering committee for the conference series. He received his PhD from the University of Pennsylvania in 2006.

Center for Language and Speech Processing