Reading is a vital skill for social, educational, and professional development, yet various disabilities can impact a person's ability to read and develop literacy skills.HCI and accessibility researchers have explored a wide range of technologies to support reading for people with disabilities.To understand trends in this space, we analyzed 101 publications from Association for Computing Machinery (ACM) venues , coding for target user communities, research methods, technologies, types of support, and contributions.Most research focused on people with dyslexia, followed by people who are Blind or Low Vision, Deaf or Hard of Hearing, or who have intellectual and cognitive disabilities.The majority of studies involved artifact development and short-term lab-based evaluations, with common technologies including visual augmentations, text modifications, and simplification-primarily aimed at improving readability, comprehension, and reading speed.However, participatory approaches and longitudinal evaluations were rarely employed, and the body of work has disproportionately focused on web-based digital reading.Following the initial coding, we conducted community-specific analyses of individual publications to identify patterns and limitations.Based on these analyses, we offer a set of open research questions and community-specific directions to guide future work.

People with disabilities represent linguistically diverse communities.For example, among Deaf and Hard of Hearing (DHH) people, many of whom use sign language as their primary language, there is significant variation in written language literacy, highlighting that some might benefit from reading comprehension support tools.Prior research has demonstrated the benefits of lexical and syntactic approaches to Automatic Text Simplification for DHH readers and explored design considerations.Building on this work, we present a fully automatic, GPT-based text comprehension tool that provides in-situ reading support.The tool, released with this demo paper, is easily customizable and adaptable to support a range of disability communities and literacy levels.We present usage scenarios to spark conversations around broader applicability, personalization needs, and future studies comparing in-situ reading support to chatbot-style GPT interfaces.

Recruiting participants from disability communities for accessibility research presents unique challenges that require careful consideration of ethical practices, intersectional representation, methodological rigor, and community sustainability.As accessibility research continues to grow and evolve, researchers face tensions between meaningfully including participants with disabilities and addressing emerging concerns around recruited participants not adequately representing the diversity of the community, overburdening certain participants, participant verification, and fair compensation practices.This workshop will bring together members of the ASSETS community to examine current recruiting practices and document insights into ethical, rigorous, and inclusive participant recruitment in disability research.Through facilitated discussions, we will explore three main themes: (1) methods and models, (2) eligibility criteria and participant verification, and (3) ethical and sustainability considerations.The workshop aims to share current practices, identify key challenges, and develop preliminary guidelines to support accessibility researchers in more sustainable participant recruitment.

Research has observed benefits from providing lexical and syntactic approaches to Automatic Text Simplification (ATS) to Deaf and Hard-of-hearing (DHH) readers. However, little research has explored DHH readers’ design preferences and interactions with these approaches. This work first explores the design space of ATS systems with DHH readers, identifying potential design configurations for evaluation. Open-ended discussion of participants’ design preferences reveal values informing those preferences, including maintaining reading fluency and efficiency, and control over the tool. Using popular design choices from our formative study, we evaluated a prototype that provides various simplification types to explore DHH readers’ interactions with the system. We observed potential conflicts between participants’ values and design preferences, such as the prototype’s impact on participants’ reading speed and participants’ perceived need to reread simplifications suggested by the tool. However, participants found the tool useful, showing a nuanced preference towards world-level lexical simplifications using pop-ups. Our findings highlight the importance of the tool’s design on users’ reading experiences, and provide implications for the design and evaluation of ATS prototypes with target readers.

Captioning provides access to sounds in audio-visual content for people who are Deaf or Hard-of-hearing (DHH). As user-generated content in online videos grows in prevalence, researchers have explored using automatic speech recognition (ASR) to automate captioning. However, definitions of captions (as compared to subtitles) include non-speech sounds, which ASR typically does not capture as it focuses on speech. Thus, we explore DHH viewers’ and hearing video creators’ perspectives on captioning non-speech sounds in user-generated online videos using text or graphics. Formative interviews with 11 DHH participants informed the design and implementation of a prototype interface for authoring text-based and graphic captions using automatic sound event detection, which was then evaluated with 10 hearing video creators. Our findings include identifying DHH viewers’ interests in having important non-speech sounds included in captions, as well as various criteria for sound selection and the appropriateness of text-based versus graphic captions of non-speech sounds. Our findings also include hearing creators’ requirements for automatic tools to assist them in captioning non-speech sounds.

Research has revealed benefits and interest among Deaf and Hard-of-Hearing (DHH) adults in reading-assistance tools powered by Automatic Text Simplification (ATS), a technology whose development benefits from evaluations by specific user groups. While prior work has provided guidance for evaluating text complexity among DHH adults, researchers lack guidance for evaluating the fluency of automatically simplified texts, which may contain errors from the simplification process. Thus, we conduct methodological research on the effectiveness of metrics (including reading speed; comprehension questions; and subjective judgements of understandability, readability, grammaticality, and system performance) for evaluating texts controlled to be at different levels of fluency, when measured among DHH participants at different literacy levels. Reading speed and grammaticality judgements effectively distinguished fluency levels among participants across literacy levels. Readability and understandability judgements, however, only worked among participants with higher literacy. Our findings provide methodological guidance for designing ATS evaluations with DHH participants.

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.

Automatic Text Simplification (ATS), which replaces text with simpler equivalents, is rapidly improving. While some research has examined ATS reading-assistance tools, little has examined preferences of adults who are deaf or hard-of-hearing (DHH), and none empirically evaluated lexical simplification technology (replacement of individual words) with these users. Prior research has revealed that U.S. DHH adults have lower reading literacy on average than their hearing peers, with unique characteristics to their literacy profile. We investigate whether DHH adults perceive a benefit from lexical simplification applied automatically or when users are provided with greater autonomy, with on-demand control and visibility as to which words are replaced. Formative interviews guided the design of an experimental study, in which DHH participants read English texts in their original form and with lexical simplification applied automatically or on-demand. Participants indicated that they perceived a benefit form lexical simplification, and they preferred a system with on-demand simplification.

Researchers have investigated various methods to help users search for the meaning of an unfamiliar word in American Sign Language (ASL). Some are based on sign-recognition technology, e.g. a user performs a word into a webcam and obtains a list of possible matches in the dictionary. However, developers of such technology report the performance of their systems inconsistently, and prior research has not examined the relationship between the performance of search technology and users' subjective judgements for this task. We conducted two studies using a Wizard-of-Oz prototype of a webcam-based ASL dictionary search system to investigate the relationship between the performance of such a system and user judgements. We found that in addition to the position of the desired word in a list of results, which is what is often reported in literature; the similarity of the other words in the results list also affected users' judgements of the system. We also found that metrics that incorporate the precision of the overall list correlated better with users' judgements than did metrics currently reported in prior ASL dictionary research.