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TACCESS Tables of Contents: 010203040506

ACM Transactions on Accessible Computing 5

Editors:Andrew Sears; Vicki L. Hanson; Matt Huenerfauth; Kathleen F. McCoy
Standard No:ISSN 1936-7228
Links:Journal Home Page | ACM Digital Library | Table of Contents
  1. TACCESS 2013-09 Volume 5 Issue 1
  2. TACCESS 2013-10 Volume 5 Issue 2
  3. TACCESS 2014-01 Volume 5 Issue 3
  4. TACCESS 2014-03 Volume 5 Issue 4

TACCESS 2013-09 Volume 5 Issue 1

Effects of Target Expansion on Selection Performance in Older Computer Users BIBAFull-Text 1
  Faustina Hwang; Nic Hollinworth; Nitin Williams
Point and click interactions using a mouse are an integral part of computer use for current desktop systems. Compared with younger users though, older adults experience greater difficulties performing cursor positioning tasks, and this can present limitations to using a computer easily and effectively. Target expansion is a technique for improving pointing performance where the target grows dynamically as the cursor approaches. This has the advantage that targets conserve screen real estate in their unexpanded state, yet can still provide the benefits of a larger area to click on. This article presents two studies of target expansion with older and younger participants, involving multidirectional point-select tasks with a computer mouse. Study 1 compares static versus expanding targets, and Study 2 compares static targets with three alternative techniques for expansion. Results show that expansion can improve times by up to 14%, and reduce error rates by up to 50%. Additionally, expanding targets are beneficial even when the expansion happens late in the movement, that is, after the cursor has reached the expanded target area or even after it has reached the original target area. The participants' subjective feedback on the target expansion are generally favorable, and this lends further support for the technique.
Performing Locomotion Tasks in Immersive Computer Games with an Adapted Eye-Tracking Interface BIBAFull-Text 2
  Stephen Vickers; Howell Istance; Aulikki Hyrskykari
Young people with severe physical disabilities may benefit greatly from participating in immersive computer games. In-game tasks can be fun, engaging, educational, and socially interactive. But for those who are unable to use traditional methods of computer input such as a mouse and keyboard, there is a barrier to interaction that they must first overcome. Eye-gaze interaction is one method of input that can potentially achieve the levels of interaction required for these games. How we use eye-gaze or the gaze interaction technique depends upon the task being performed, the individual performing it, and the equipment available. To fully realize the impact of participation in these environments, techniques need to be adapted to the person's abilities. We describe an approach to designing and adapting a gaze interaction technique to support locomotion, a task central to immersive game playing. This is evaluated by a group of young people with cerebral palsy and muscular dystrophy. The results show that by adapting the interaction technique, participants are able to significantly improve their in-game character control.

TACCESS 2013-10 Volume 5 Issue 2

Editorial BIBFull-Text 3
  Andrew Sears; Vicki Hanson
Effect of Displaying Human Videos During an Evaluation Study of American Sign Language Animation BIBAFull-Text 4
  Hernisa Kacorri; Pengfei Lu; Matt Huenerfauth
Many researchers internationally are studying how to synthesize computer animations of sign language; such animations have accessibility benefits for people who are deaf and have lower literacy in written languages. The field has not yet formed a consensus as to how to best conduct evaluations of the quality of sign language animations, and this article explores an important methodological issue for researchers conducting experimental studies with participants who are deaf. Traditionally, when evaluating an animation, some lower and upper baselines are shown for comparison during the study. For the upper baseline, some researchers use carefully produced animations, and others use videos of human signers. Specifically, this article investigates, in studies where signers view animations of sign language and are asked subjective and comprehension questions, whether participants differ in their subjective and comprehension responses when actual videos of human signers are shown during the study. Through three sets of experiments, we characterize how the Likert-scale subjective judgments of participants about sign language animations are negatively affected when they are also shown videos of human signers for comparison -- especially when displayed side-by-side. We also identify a small positive effect on the comprehension of sign language animations when studies also contain videos of human signers. Our results enable direct comparison of previously published evaluations of sign language animations that used different types of upper baselines -- video or animation. Our results also provide methodological guidance for researchers who are designing evaluation studies of sign language animation or designing experimental stimuli or questions for participants who are deaf.
Distinguishing Users By Pointing Performance in Laboratory and Real-World Tasks BIBAFull-Text 5
  Amy Hurst; Scott E. Hudson; Jennifer Mankoff; Shari Trewin
Accurate pointing is an obstacle to computer access for individuals who experience motor impairments. One of the main barriers to assisting individuals with pointing problems is a lack of frequent and low-cost assessment of pointing ability. We are working to build technology to automatically assess pointing problems during every day (or real-world) computer use. To this end, we have gathered and studied real-world pointing use from individuals with motor impairments and older adults. We have used this data to develop novel techniques to analyze pointing performance. In this article, we present learned statistical models that distinguish between pointing actions from diverse populations using real-world pointing samples. We describe how our models could be used to support individuals with different abilities sharing a computer, or one individual who experiences temporary pointing problems. Our investigation contributes to a better understanding of real-world pointing. We hope that these techniques will be used to develop systems that can automatically adapt to users' current needs in real-world computing environments.

TACCESS 2014-01 Volume 5 Issue 3

Greetings from the New Editors-in-Chief BIBFull-Text 6
  Matt Huenerfauth; Kathy McCoy
Accessibility Evaluation of Classroom Captions BIBAFull-Text 7
  Raja S. Kushalnagar; Walter S. Lasecki; Jeffrey P. Bigham
Real-time captioning enables deaf and hard of hearing (DHH) people to follow classroom lectures and other aural speech by converting it into visual text with less than a five second delay. Keeping the delay short allows end-users to follow and participate in conversations. This article focuses on the fundamental problem that makes real-time captioning difficult: sequential keyboard typing is much slower than speaking. We first surveyed the audio characteristics of 240 one-hour-long captioned lectures on YouTube, such as speed and duration of speaking bursts. We then analyzed how these characteristics impact caption generation and readability, considering specifically our human-powered collaborative captioning approach. We note that most of these characteristics are also present in more general domains. For our caption comparison evaluation, we transcribed a classroom lecture in real-time using all three captioning approaches. We recruited 48 participants (24 DHH) to watch these classroom transcripts in an eye-tracking laboratory. We presented these captions in a randomized, balanced order. We show that both hearing and DHH participants preferred and followed collaborative captions better than those generated by automatic speech recognition (ASR) or professionals due to the more consistent flow of the resulting captions. These results show the potential to reliably capture speech even during sudden bursts of speed, as well as for generating "enhanced" captions, unlike other human-powered captioning approaches.
Technology for Supporting Care Staff in Residential Homes BIBAFull-Text 8
  Gemma Webster; Vicki L. Hanson
Care staff, those who attend to the day-to-day needs of people in residential facilities, represent an important segment of the health-care provision of those entrusted to their care. The potential use of technology by care staff has not been a focus of researcher attention. The work reported here provides initial steps in addressing that gap, considering both the design requirements for this population and presentation of early work on a software system for use by care staff. We describe the development of a software tool for use by care staff, called Portrait, and report two studies related to factors affecting technology use by this population. The results of this research are promising, with Portrait being very positively received by care managers and care staff. Use of this software in a care home for over a month indicated continued use, with care staff returning to the system throughout the test period. The contributions of this research are the identification of factors important in working with a care staff population, the introduction and evaluation of a novel software tool for care staff in residential homes, and the highlighting of potential benefits of technology in assisting care staff.

TACCESS 2014-03 Volume 5 Issue 4

Identifying Sign Language Videos in Video Sharing Sites BIBAFull-Text 9
  Frank M. Shipman; Ricardo Gutierrez-Osuna; Caio D. D. Monteiro
Video sharing sites enable members of the sign language community to record and share their knowledge, opinions, and worries on a wide range of topics. As a result, these sites have formative digital libraries of sign language content hidden within their large overall collections. This article explores the problem of locating these sign language (SL) videos and presents techniques for identifying SL videos in such collections. To determine the effectiveness of existing text-based search for locating these SL videos, a series of queries were issued to YouTube to locate SL videos on the top 10 news stories of 2011 according to Yahoo!. Overall precision for the first page of results (up to 20 results) was 42%. An approach for automatically detecting SL video is then presented. Five video features considered likely to be of value were developed using standard background modeling and face detection. The article compares the results of an SVM classifier when given all permutations of these five features. The results show that a measure of the symmetry of motion relative to the face position provided the best performance of any single feature. When tested against a challenging test collection that included many likely false positives, an SVM provided with all five features achieved 82% precision and 90% recall. In contrast, the text-based search (queries with the topic terms and "ASL" or "sign language") returned a significant portion of non-SL content -- nearly half of all videos found. By our estimates, the application of video-based filtering techniques such as the one proposed here would increase precision from 42% for text-based queries up to 75%.
Automatic Task Assistance for People with Cognitive Disabilities in Brushing Teeth -- A User Study with the TEBRA System BIBAFull-Text 10
  Christian Peters; Thomas Hermann; Sven Wachsmuth; Jesse Hoey
People with cognitive disabilities such as dementia and intellectual disabilities tend to have problems in coordinating steps in the execution of Activities of Daily Living (ADLs) due to limited capabilities in cognitive functioning. To successfully perform ADLs, these people are reliant on the assistance of human caregivers. This leads to a decrease of independence for care recipients and imposes a high burden on caregivers. Assistive Technology for Cognition (ATC) aims to compensate for decreased cognitive functions. ATC systems provide automatic assistance in task execution by delivering appropriate prompts which enable the user to perform ADLs without any assistance of a human caregiver. This leads to an increase of the user's independence and to a relief of caregiver's burden. In this article, we describe the design, development and evaluation of a novel ATC system. The TEBRA (TEeth BRushing Assistance) system supports people with moderate cognitive disabilities in the execution of brushing teeth. A main requirement for the acceptance of ATC systems is context awareness: explicit feedback from the user is not necessary to provide appropriate assistance. Furthermore, an ATC system needs to handle spatial and temporal variance in the execution of behaviors such as different movement characteristics and different velocities. The TEBRA system handles spatial variance in a behavior recognition component based on a Bayesian network classifier. A dynamic timing model deals with temporal variance by adapting to different velocities of users during a trial. We evaluate a fully functioning prototype of the TEBRA system in a study with people with cognitive disabilities. The main aim of the study is to analyze the technical performance of the system and the user's behavior in the interaction with the system with regard to the main hypothesis: is the TEBRA system able to increase the user's independence in the execution of brushing teeth?