Adding American Sign Language (ASL) versions of information content to websites can improve information accessibility for many people who are Deaf or Hard of Hearing (DHH) who may have lower levels of English literacy. Generating animations from a script representation would enable this content to be easily updated, yet software is needed that can set detailed speed and timing parameters for such animations, which prior work has revealed to be critical for their understandability and acceptance among DHH users. Despite recent work on predicting these parameters using AI models trained on recordings of human signers, no prior work had examined whether DHH users actually prefer for these speed and timing properties to be similar to humans, or to be exaggerated, e.g. for additional clarity. We conducted two empirical studies to investigate preferences of ASL signers for speed and timing parameters of ASL animations, including: sign duration, transition time, differential signing rate, pause length, and pausing frequency. Our first study (N=20) identified two preferred values from among five options for each parameter, one of which included a typical human value for this parameter, and a second study (N=20) identified the most preferred value. We found that while ASL signers preferred pause length and frequency to be similar to those of humans, they actually preferred animations to have faster signs, slower transitions, and less dynamic variation in differential signing speed, as compared to the timing of human signers. This study provides specific empirical guidance for creators of future ASL animation technologies, and more broadly, it demonstrates that it is not safe to assume that ASL signers will simply prefer for properties of ASL animations to be as similar as possible to human signers.

Listening to podcasts is a popular way for people to spend their time. However, little focus has been given to how accessible podcast platforms are for Deaf and Hard-of-Hearing (DHH) people. We present a DHH-centered accessible podcast platform prototype developed with user-centered design. Our proposed design was constructed through semi-structured interviews (n=7) and prototype design feedback sessions (n=8) with DHH users. We encourage podcast platform designers to adopt our design recommendations to make podcasts more inclusive for DHH people and recommend how podcast hosts can make their shows more accessible.

In interaction or user-centered design practices, it is common to employ interviews and think-aloud techniques to gather data about user behavior. These techniques enable researchers to learn about how users think and use technologies during the design and user testing process. However, such techniques involve accessing audio feedback, which may require workarounds if the researcher identifies as deaf or hard of hearing (DHH). We report on a project led by a DHH researcher in which workarounds to audio access resulted in methodological changes. We discuss the implications of these adjustments.

Without a commonly accepted writing system for American Sign Language (ASL), Deaf or Hard of Hearing (DHH) ASL signers who wish to express opinions or ask questions online must post a video of their signing, if they prefer not to use written English, a language in which they may feel less proficient. Since the face conveys essential linguistic meaning, the face cannot simply be removed from the video in order to preserve anonymity. Thus, DHH ASL signers cannot easily discuss sensitive, personal, or controversial topics in their primary language, limiting engagement in online debate or inquiries about health or legal issues. We explored several recent attempts to address this problem through development of “face swap” technologies to automatically disguise the face in videos while preserving essential facial expressions and natural human appearance. We presented several prototypes to DHH ASL signers (N=16) and examined their interests in and requirements for such technology. After viewing transformed videos of other signers and of themselves, participants evaluated the understandability, naturalness of appearance, and degree of anonymity protection of these technologies. Our study revealed users’ perception of key trade-offs among these three dimensions, factors that contribute to each, and their views on transformation options enabled by this technology, for use in various contexts. Our findings guide future designers of this technology and inform selection of applications and design features.

Research has explored using Automatic Text Simplification for reading assistance, with prior work identifying benefits and interests from Deaf and Hard-of-Hearing (DHH) adults. While the evaluation of these technologies remains a crucial aspect of research in the area, researchers lack guidance in terms of how to evaluate text complexity with DHH readers. Thus, in this work we conduct methodological research to evaluate metrics identified from prior work (including reading speed, comprehension questions, and subjective judgements of understandability and readability) in terms of their effectiveness for evaluating texts modified to be at various complexity levels with DHH adults at different literacy levels. Subjective metrics and low-linguistic-complexity comprehension questions distinguished certain text complexity levels with participants with lower literacy. Among participants with higher literacy, only subjective judgements of text readability distinguished certain text complexity levels. For all metrics, participants with higher literacy scored higher or provided more positive subjective judgements overall.

Automatic Text Simplification (ATS) software replaces text with simpler alternatives. While some prior research has explored its use as a reading assistance technology, including some empirical findings suggesting benefits for deploying this technology among particular groups of users, relatively little work has investigated the interest and requirements of specific groups of users of this technology. In this study, we investigated the interests of Deaf and Hard-of-Hearing (DHH) individuals in the computing industry in ATS-based reading assistance tools, motivated by prior work establishing that computing professionals often need to read about new technologies in order to stay current in their profession. Through a survey and follow-up interviews, we investigate these DHH individuals’ reading practices, current techniques for overcoming complicated text, and their interest in reading assistance tools for their work. Our results suggest that these users read relatively often, especially in support of their work, and they were interested in tools to assist them with complicated texts. This empirical contribution provides motivation for further research into ATS-based reading assistance tools for these users, prioritizing which reading activities users are most interested in seeing application of this technology, as well as some insights into design considerations for such tools.