Search

Many Deaf and Hard-of-Hearing (DHH) individuals rely on sign language interpreting to communicate with hearing peers. If on-site interpreting is not available, DHH individuals may use remote interpreting over a smartphone video-call. However, this solution requires the DHH individual to give up either 1) the use of one signing hand by holding the smartphone or 2) their ability to multitask and move around by propping the smartphone up in a fixed location. We explore this problem within the context of the workplace, and present a prototype hands-free device using augmented reality glasses with a hat-mounted fisheye camera and mic/speaker. To explore the validity of our design, we conducted 1) a video interpretability experiment, and 2) a user study with 18 participants (9 DHH, 9 hearing) in a workplace environment. Our results suggest that a hands-free device can support accurate interpretation while enhancing personal interactions. [ABSTRACT FROM AUTHOR]

To enable more websites to provide content in the form of sign language, we investigate software to partially automate the synthesis of animations of American Sign Language (ASL), based on a human-authored message specification. We automatically select: where prosodic pauses should be inserted (based on the syntax or other features), the time-duration of these pauses, and the variations of the speed at which individual words are performed (e.g. slower at the end of phrases). Based on an analysis of a corpus of multi-sentence ASL recordings with motion-capture data, we trained machine-learning models, which were evaluated in a cross-validation study. The best model out-performed a prior state-of-the-art ASL timing model. In a study with native ASL signers evaluating animations generated from either our new model or from a simple baseline (uniform speed and no pauses), participants indicated a preference for speed and pausing in ASL animations from our model. [ABSTRACT FROM AUTHOR]

In usability studies, designers and researchers frequently use subjective questions to evaluate participants' impression of the usability of some product. The System Usability Scale (SUS) is a popular standardized questionnaire consisting of ten English statements about the usability of a product, to which participants indicate their agreement on a five-point scale. Many deaf adults in the U.S. have lower levels of English reading literacy, but there are currently no standardized questionnaires similar to SUS for Deaf and Hard-of-Hearing (DHH) users who are fluent in American Sign Language (ASL). To facilitate the inclusion of such users in studies, we created an ASL translation of SUS following accepted methods of survey translation: using a bilingual team including native ASL signers who are members of the Deaf community, along with back-translation evaluation to determine whether the meaning of the original was preserved. To validate whether key psychometric properties were preserved during translation, we deployed the ASL instrument in a study with 30 DHH participants. By comparing the results to users' responses to another measurement instrument, along with scores from 10 additional DHH participants responding to the original English SUS, we verified the criterion validity and internal reliability of the new "ASL-SUS." We are disseminating the translated instrument to promote the inclusion of DHH users in HCI research studies or in usability testing of consumer products. [ABSTRACT FROM AUTHOR]

Recent advances in Automatic Speech Recognition (ASR) have made this technology a potential solution for transcribing audio input in real-time for people who are Deaf or Hard of Hearing (DHH). However, ASR is imperfect; users must cope with errors in the output. While some prior research has studied ASR-generated transcriptions to provide captions for DHH people, there has not been a systematic study of how to best present captions that may include errors from ASR software nor how to make use of the ASR system's word-level confidence. We conducted two studies, with 21 and 107 DHH participants, to compare various methods of visually presenting the ASR output with certainty values. Participants answered subjective preference questions and provided feedback on how ASR captioning could be used with confidence display markup. Users preferred captioning styles with which they were already most familiar (that did not display confidence information), and they were concerned about the accuracy of ASR systems. While they expressed interest in systems that display word confidence during captions, they were concerned that text appearance changes may be distracting. The findings of this study should be useful for researchers and companies developing automated captioning systems for DHH users. [ABSTRACT FROM AUTHOR]