ACS is pleased to share on its website a new video by the University of Washington AccessComputer Project that explores what CART is and where it can be used. The video is ideal for anyone who is deaf or hard-of-hearing and is considering what types of accommodations might be best for participating in a class, conference, webinar, or business meeting. The video was developed by the Access Computing Project at the University of Washington. The University of Washington has granted ACS permission to use this video for educational, noncommercial purposes.
To view the video on the ACS website, click on the following link and scroll down to the bottom of the page:
You will be taken to the ACS CART landing page, then scroll down to access the video. The video is captioned.
For more information about communication access realtime translation, please email firstname.lastname@example.org.
Additional Information About the Video
Author: Rob Roth, AccessComputing staff
The University of Washington AccessComputing Project produced a 7minute-34 second video, Communication Access Realtime Translation (CART) Services for Deaf and Hard-of-Hearing People, that explores what CART is and where it can be used. The video is ideal for anyone who is deaf or hard of hearing and is considering what types of accommodations would be best for participating in a college-level class or at a conference.
The video was developed after it was discovered that few, if any, resources were available on the Internet to explain what CART and other captioning systems were. Four students from the Summer Academy for Advancing Deaf and Hard of Hearing in Computing, including two ASL signers, speak about why they chose captioning within a STEM educational setting. This video is viewable on the Alternative Communication Services (ACS) website by permission of the University of Washington.
Copyright © 2014 by University of Washington. Permission is granted to copy these materials for educational, noncommercial purposes provided the source is acknowledged. The AccessComputing project is funded by the National Science Foundation (grant #CNS-0540615, CNS-0837508, and CNS-1042260). Any questions, findings, and conclusions or recommendations expressed in this material are those of the author and do not necessarily reflect the views of the federal government. We support the University of Washington’s online privacy statement and its terms and conditions of use.