Rehabilitation Computing Group
Using computing to assist the communications needs of people with disabilities is an area with vast potential. This group explores uses of computers to enable improved communication for blind and deaf students, although the solutions developed have applicability beyond this domain.
Project: An Accessible, Tremor-filtering, Pointing Device
Purpose: Develop an application that smoothes the jerky motion of a pointing device that is caused by an essential tremor or other tremor-causing conditions.
Researchers: Tom Way
Research Alumni: Tim Mizas (related Wiimote research), Andrew Miller, Anthony Dovelle, John Truitt
Applications: Assistive technology, assistive device
The incidence of tremors, resulting from an essential tremor, familial tremor, Parkinson's disease, or other conditions, is present in a significant portion of the population. In public speaking situations, such as when giving a PowerPoint-based presentation, a tremor can lead to a greatly reduced ability to make use of a laser pointing device.
Our research involves creating a computer application that can filter positional data from a Nintendo Wii remote control, or Wiimote, to smooth out the jerky motion induced by a tremor.
Project: Affordable Speech Recognition for the Classroom
Purpose: Develop a real-time continuous speech recognition application for use by college students to assist with note-taking.
Researchers: Tom Way
Researcher Alumni: Richard Kheir, Louis Bevilacqua
Applications: Assistive technology, security & monitoring
A principal difficulty with speech recognition software, and therefore with its broad acceptance, has been its accuracy rate. Even with an achievable 98% accuracy rate, automatic speech recognition (ASR) for general applications such as real-time transcription are unacceptable. Industry predictions are that accuracy will be significantly boosted within 5-10 years.
For the deaf and hard-of-hearing, the task of listening is difficult, requires an extreme amount of attention, and can be aided by a sign-language interpreter. The use of software ASR is an attractive one, allowing more freedom and independence. Although a 2% inaccuracy rate is dreadful in the business world, it is entirely workable in the context of an automatic speech recognition interpreter. It is likely that higher degrees of inaccuracy, perhaps 10% or more, would not be unworkable, given the assistive (rather than transcriptive) nature of the task.
We are exploring the use of Java tools and off-the-shelf, low-cost ASR systems to solve this problem.
A prototype version has been developed for testing in a classroom lecture setting that will use a desktop or laptop computer, a wireless head-set microphone, and the Microsoft Speech Recognition software bundled with Office. Experiments have been conducted, and additional experiments are planned, to compare speaker-trained ASR with and without use of an automatically captured domain dictionary.
Best of the related info:
Other related info:
Publications & Conferences:
Example training session (4/25/05):
This training was conducted in my office using the wireless headset microphone.
Project: Firefox Imaging Plug-ins
Purpose: Develop a Firefox browser extension that creates tactile-ready images and textual descriptions of images
Researchers: Tom Way
Blind and low-vision computer users are faced with a quandary. The popularity of the Internet has led to an explosion of fancy graphics, beautiful (and ugly) web site layout and design, and easily available digital photographs numbering in the millions, none of which are accessible to this group of users. The lab director's M.S. thesis, "Automatic Generation of Tactile Images," was an early investigation of how images could be made accessible to blind and low-vision computer users through creation of tactile graphics or "tactics." By applying sophisticated image processing techniques and using tactile imaging technology, significant strides were made in developing a framework for creating meaningful "tactic" representations. This work that was started in 1995 has been carried on by Dr. Ken Barner and many of his students at the University of Delaware.
This work is involves using the Firefox plug-in extension API to create a brower extension that will perform appropriate processing of each image on a web page. The result will be the first step in providing broader access, automatically, to the blind and low-vision computer using population.
Secondarily, this work involves creating or extending a Firefox plug-in to generate textual descriptions of images. Initially, this is likely to be rudimentary, with the main goal to add some initial proof-of-concept level of textual description where none is present. The approach can be a combination of scraping and summarizing nearby text and alt text, and performing simple detection of objects within the image, or otherwise analyzing shapes and colors in the image. This is a very difficult problem, so the first step is important but will necessarily be incomplete.