Xianjing Han, Bin Zhu, Shiqi Hu, Franklin Mingzhe Li, Patrick Carrington, Roger Zimmermann, Jingjing Chen. Proceedings of the 64th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers). 2026.

Audio Description (AD) provides essential access to visual media for blind and low vision (BLV) audiences. Yet current AD production tools remain largely inaccessible to BLV video creators, who possess valuable expertise but face barriers due to visually-driven interfaces. We present ADCanvas, a multimodal authoring system that supports non-visual control over audio description (AD) creation. ADCanvas combines conversational interaction with keyboard-based playback control and a plain-text, screen reader–accessible editor to support end-to-end AD authoring and visual question answering (VQA). Combining screen-reader-friendly controls with a multimodal LLM agent, ADCanvas supports live VQA, script generation, and AD modification. Through a user study with 12 BLV video creators, we find that users adopt the conversational agent as an informational aide and drafting assistant, while maintaining agency through verification and editing. For example, participants saw themselves as curators who received information from the model and filtered it down for their audience. Our findings offer design implications for accessible media tools, including precise editing controls, accessibility support for creative ideation, and configurable rules for human-AI collaboration.

Nature plays a crucial role in human health and well-being, but little is known about how blind people experience and relate to it. We conducted a survey of nature relatedness with blind (N=20) and sighted (N=20) participants, along with in-depth interviews with 16 blind participants, to examine how blind people engage with nature and the factors shaping this engagement. Our survey results revealed lower levels of nature relatedness among blind participants compared to sighted peers. Our interview study further highlighted: 1) current practices and challenges of nature engagement, 2) attitudes and values that shape engagement, and 3) expectations for assistive technologies that support safe and meaningful engagement. We also provide design implications to guide future technologies that support nature engagement for blind people. Overall, our findings illustrate how blind people experience nature beyond vision and lay a foundation for technologies that support inclusive nature engagement.

Makeup plays a vital role in self-expression, identity, and confidence -yet remains an underexplored domain for assistive technology, especially for people with vision impairments.While existing tools support isolated tasks such as color identification or product labeling, they rarely address the procedural complexity of makeup routines: coordinating step sequences, managing product placement, and assessing the final look with accessible feedback.To understand the real-world process, we conducted a contextual inquiry with 15 visually impaired makeup users, capturing real-time makeup application behaviors and their step-by-step information needs and assessment approaches.Our findings reveal embodied, tactile-first strategies; persistent challenges in blending, symmetry, and assessment; and a desire for honest, real-time, goal-aligned feedback.We also interviewed five professional makeup artists, who reviewed participant makeup videos and provided expert responses to participant-raised questions and assessment practices.We contribute a taxonomy of feedback needs in non-visual makeup, and outline design implications for future assistive systems -emphasizing hands-free, conversational interaction and context-aware, procedural support for expressive and independent beauty practices.

Mobile games are becoming a vital medium for social interaction, offering a platform that transcends geographical boundaries.An increasing number of visually impaired individuals are engaging in mobile gaming to connect, collaborate, compete, and build friendships.In China, visually impaired communities face significant social challenges in offline settings, making mobile games a crucial avenue for socialization.However, the design of mobile games and their mapping to real-world environments significantly shape their social gaming experiences.This study explores how visually impaired players in China navigate socialization and integrate into gaming communities.Through interviews with 30 visually impaired players, we found that while mobile games fulfill many of their social needs, technological barriers and insufficient accessibility features, and internal community divisions present significant challenges to their participation.This research sheds light on their social experiences and offers insights for designing more inclusive and accessible mobile games.

Video content creation offers vital opportunities for expression and participation, yet remains largely inaccessible to creators with sensory impairments, especially in low-resource settings.We conducted interviews with 20 video creators with visual and hearing impairments in Kenya to examine their tools, challenges, and collaborative practices.Our findings show that accessibility barriers and infrastructural limitations shape video creation as a staged, collaborative process involving trusted human partners and emerging AI tools.Across workflows, creators actively negotiated agency and trust, maintaining creative control while bridging sensory gaps.We discuss the need for flexible, interdependent collaboration models, inclusive human-AI workflows, and diverse storytelling practices.This work broadens accessibility research in HCI by examining how technology and social factors intersect in low-resource contexts, suggesting ways to better support disabled creators globally.

From curating the layout of a resume to selecting filters for social media, creating and configuring visual content allows individuals to express identity, communicate intent, and engage socially, yet blind individuals often face significant barriers to such expressive practices.Prior accessibility research primarily addresses functional content configuration, leaving little understanding of blind individuals' expressive visual creation needs.To better understand and support these needs, we conducted a two-stage study: first, we interviewed 10 blind participants to understand their motivations, current practices, and barriers in visual expression, and to ideate on potential visual editing support; second, based on interview insights, we developed an interactive prototype (VizXpress) that provides real-time feedback on visual aesthetics using a vision-language model and supports automated and manual visual editing controls.We used VizXpress as a design probe to further explore accessible design opportunities for visual expression.Our findings highlight many blind users' strong interest in creating visually expressive content, nuanced informational requirements for subjective aesthetics (e.g., color, mood, lighting), and ongoing accessibility challenges with visual creative tools.Grounded in these insights, we propose design implications including richer aesthetic feedback, controlled intelligent editing, and accessible manual editing mechanisms.

Fingerspelling is a critical part of American Sign Language (ASL) recognition and has become an accessible optional text entry method for Deaf and Hard of Hearing (DHH) individuals. In this paper, we introduce SpellRing, a single smart ring worn on the thumb that recognizes words continuously fingerspelled in ASL. SpellRing uses active acoustic sensing (via a microphone and speaker) and an inertial measurement unit (IMU) to track handshape and movement, which are processed through a deep learning algorithm using Connectionist Temporal Classification (CTC) loss. We evaluated the system with 20 ASL signers (13 fluent and 7 learners), using the MacKenzie-Soukoref Phrase Set of 1,164 words and 100 phrases. Offline evaluation yielded top-1 and top-5 word recognition accuracies of 82.45% (9.67%) and 92.42% (5.70%), respectively. In real-time, the system achieved a word error rate (WER) of 0.099 (0.039) on the phrases. Based on these results, we discuss key lessons and design implications for future minimally obtrusive ASL recognition wearables.

Parkinson's Disease (PD) significantly impacts driving abilities, often leading to early driving cessation or accidents due to reduced CHI '25, Yokohama, Japan

Videos offer rich audiovisual information that can support people in performing activities of daily living (ADLs), but they remain largely inaccessible to blind or low-vision (BLV) individuals.In cooking, BLV people often rely on non-visual cues-such as touch, taste, and smell-to navigate their environment, making it difficult to follow UIST '25, September 28-October 01, 2025, Busan, Republic of Korea Ning et al.the predominantly audiovisual instructions found in video recipes.To address this problem, we introduce Aroma, an AI system that provides timely responses to the user based on real-time, contextaware assistance by integrating non-visual cues perceived by the user, a wearable camera feed, and video recipe content.Aroma uses a mixed-initiative approach: it responds to user requests while also proactively monitoring the video stream to offer timely alerts and guidance.This collaborative design leverages the complementary strengths of the user and AI system to align the physical environment with the video recipe, helping the user interpret their current state and make sense of the steps.We evaluated Aroma through a study with eight BLV participants and offered insights for designing interactive AI systems to support BLV individuals in performing ADLs.

Emotional voice communication plays a crucial role in effective daily interactions. Deaf and Hard of Hearing (DHH) individuals, who often have limited use of voice, rely on facial expressions to supplement sign language and convey emotions. However, in American Sign Language (ASL), facial expressions serve not only emotional purposes but also function as linguistic markers that can alter the meaning of signs. This dual role can often confuse non-signers when interpreting a signer's emotional state. In this paper, we present studies that: (1) confirm the challenges non-signers face when interpreting emotions from facial expressions in ASL communication, and (2) demonstrate how integrating emotional voice into translation systems can enhance hearing individuals' understanding of a signer's emotional intent. An online survey with 45 hearing participants (non-ASL signers) revealed frequent misinterpretations of signers' emotions when emotional and linguistic facial expressions were used simultaneously. The findings show that incorporating emotional voice into translation systems significantly improves emotion recognition by 32%. Additionally, follow-up survey with 48 DHH participants highlights design considerations for implementing emotional voice features, emphasizing the importance of emotional voice integration to bridge communication gaps between DHH and hearing communities.

Cooking is an essential activity that enhances quality of life by enabling individuals to prepare their own meals. However, cooking often requires multitasking between cooking tasks and following instructions, which can be challenging to cooks with vision impairments if recipes or other instructions are inaccessible. To explore the practices and challenges of recipe access while cooking, we conducted semi-structured interviews with 20 people with vision impairments who have cooking experience and four cooking instructors at a vision rehabilitation center. We also asked participants to edit and give feedback on existing recipes. We revealed unique practices and challenges to accessing recipe information at different cooking stages, such as the heavy burden of hand-washing to interact with recipe readers. We also presented the preferred information representation and structure of recipes. We then highlighted design features of technological supports that could facilitate the development of more accessible kitchen technologies for recipe access. Our work contributes nuanced insights and design guidelines to enhance recipe accessibility for people with vision impairments.

Sidewalk robots are increasingly common across the globe. Yet, their operation on public paths poses challenges for people with mobility disabilities (PwMD) who face barriers to accessibility, such as insufficient curb cuts. We interviewed 15 PwMD to understand how they perceive sidewalk robots. Findings indicated that PwMD feel they have to compete for space on the sidewalk when robots are introduced. We next interviewed eight robotics practitioners to learn about their attitudes towards accessibility. Practitioners described how issues often stem from robotic companies addressing accessibility only after problems arise. Both interview groups underscored the importance of integrating accessibility from the outset. Building on this finding, we held four co-design workshops with PwMD and practitioners in pairs. These convenings brought to bear accessibility needs around robots operating in public spaces and in the public interest. Our study aims to set the stage for a more inclusive future around public service robots.

Individuals with vision impairments employ a variety of strategies for object identification, such as pans or soy sauce, in the culinary process. In addition, they often rely on contextual details about objects, such as location, orientation, and current status, to autonomously execute cooking activities. To understand how people with vision impairments collect and use the contextual information of objects while cooking, we conducted a contextual inquiry study with 12 participants in their own kitchens. This research aims to analyze object interaction dynamics in culinary practices to enhance assistive vision technologies for visually impaired cooks. We outline eight different types of contextual information and the strategies that blind cooks currently use to access the information while preparing meals. Further, we discuss preferences for communicating contextual information about kitchen objects as well as considerations for the deployment of AI-powered assistive technologies.

Sensemaking in unfamiliar domains can be challenging, demanding considerable user effort to compare different options with respect to various criteria. Prior research and our formative study found that people would benefit from reading an overview of an information space upfront, including the criteria others previously found useful. However, existing sensemaking tools struggle with the “cold-start” problem — it not only requires significant input from previous users to generate and share these overviews, but such overviews may also turn out to be biased and incomplete. In this work, we introduce a novel system, Selenite, which leverages Large Language Models (LLMs) as reasoning machines and knowledge retrievers to automatically produce a comprehensive overview of options and criteria to jumpstart users’ sensemaking processes. Subsequently, Selenite also adapts as people use it, helping users find, read, and navigate unfamiliar information in a systematic yet personalized manner. Through three studies, we found that Selenite produced accurate and high-quality overviews reliably, significantly accelerated users’ information processing, and effectively improved their overall comprehension and sensemaking experience.

Recent research proposed gaze-assisted gestures to enhance interaction within virtual reality (VR), providing opportunities for people with motor impairments to experience VR. Compared to people with other motor impairments, those with Spinal Muscular Atrophy (SMA) exhibit enhanced distal limb mobility, providing them with more design space. However, it remains unknown what gaze-assisted upper-body gestures people with SMA would want and be able to perform. We conducted an elicitation study in which 12 VR-experienced people with SMA designed upper-body gestures for 26 VR commands, and collected 312 user-defined gestures. Participants predominantly favored creating gestures with their hands. The type of tasks and participants’ abilities influence their choice of body parts for gesture design. Participants tended to enhance their body involvement and preferred gestures that required minimal physical effort, and were aesthetically pleasing. Our research will contribute to creating better gesture-based input methods for people with motor impairments to interact with VR.

Sidewalk robots are becoming increasingly common worldwide, yet their operation on public walkways presents challenges for pedestrians. This is especially true for people with motor disabilities (PWMD) who already manage obstacles such as inadequate ramps and public incivility. The addition of sidewalk robots could further intensify these difficulties, which poses an urgent need to examine how the design of sidewalk robots may influence the daily navigation experiences of PWMD. This poster illustrates findings from semi-structured interviews with ten PWMD, providing insights into their perspectives on the presence of sidewalk robots. The study uncovers potential conflicts in shared sidewalk use and the adaptive actions PWMD described needing to undertake in response. Interviewees raised concerns about whether the robots could accommodate the needs of PWMD, as compared to people walking on foot, and the repercussions of any shortcomings in this regard. Our research also examines tensions stemming from different robotic design choices, indicating the necessity for more accessible public robot designs. We further delve into PWMD’s interaction needs and modalities for routine operation and in the event of robot malfunction. As cities increasingly allow for the deployment of robots in public spaces, this work seeks to inform equitable design and deployment guidelines for sidewalk robots and calls for further research into the implications of the rise of public robots for the diverse populations that make up any given municipality.

Acquiring accessibility information about unfamiliar places in advance is essential for wheelchair users to make better decisions about physical visits. Today’s assessment approaches such as phone calls, photos/videos, or 360° virtual tours often fall short of providing the specific accessibility details needed for individual differences. For example, they may not reveal crucial information like whether the legroom underneath a table is spacious enough or if the spatial configuration of an appliance is convenient for wheelchair users. In response, we present Embodied Exploration, a Virtual Reality (VR) technique to deliver the experience of a physical visit while keeping the convenience of remote assessment. Embodied Exploration allows wheelchair users to explore high-fidelity digital replicas of physical environments with themselves embodied by avatars, leveraging the increasingly affordable VR headsets. With a preliminary exploratory study, we investigated the needs and iteratively refined our techniques. Through a real-world user study with six wheelchair users, we found Embodied Exploration is able to facilitate remote and accurate accessibility assessment. We also discuss design implications for embodiment, safety, and practicality.

Upper extremity (UE) health issues are a common concern among wheelchair users and have a large impact on their independence, social participation, and quality of life. However, despite the well-documented prevalence and negative impacts, these issues remain unresolved. Existing solutions (e.g. surgical repair, conservative treatments) often fail to promote sustained UE health improvement in wheelchair users’ day-to-day lives. Recent HCI research has shown the effectiveness of health tracking technologies in supporting patients’ self-care for different health conditions (e.g. chronic diseases, mental health). In this work, we explore how health tracking technologies could support wheelchair users’ UE health self-care. We conducted semi-structured interviews with 12 wheelchair users and 5 therapists to understand their practices and challenges in UE health management, as well as the potential benefits of integrating health tracking technologies into self-care routines. We discuss design implications for UE health tracking technologies and outline opportunities for future investigation.

Visual arts play an important role in cultural life and provide access to social heritage and self-enrichment, but most visual arts are inaccessible to blind people. Researchers have explored different ways to enhance blind people’s access to visual arts (e.g., audio descriptions, tactile graphics). However, how blind people adopt these methods remains unknown. We conducted semi-structured interviews with 15 blind visual arts patrons to understand how they engage with visual artwork and the factors that influence their adoption of visual arts access methods. We further examined interview insights in a follow-up survey (N=220). We present: 1) current practices and challenges of accessing visual artwork in-person and online (e.g., Zoom tour), 2) motivation and cognition of perceiving visual arts (e.g., imagination), and 3) implications for designing visual arts access methods. Overall, our findings provide a roadmap for technology-based support for blind people’s visual arts experiences.

Older adults have been hit disproportionally hard by the COVID-19 pandemic. One critical way for older adults to minimize the negative impact of COVID-19 and future pandemics is to stay informed about its latest information, which has been increasingly presented through online interactive visualizations (e.g., live dashboards and websites). Thus, it is imperative to understand how older adults interact with and comprehend online COVID-19 interactive visualizations and what challenges they might encounter to make such visualizations more accessible to older adults. We adopted a user-centered approach by inviting older adults to interact with COVID-19 interactive visualizations while at the same time verbalizing their thought processes using a think-aloud protocol. By analyzing their think-aloud verbalizations, we identified four types of thought processes representing how older adults comprehended the visualizations and uncovered the challenges they encountered with these thought processes. Furthermore, we also identified the challenges they encountered with seven common types of interaction techniques adopted by the visualizations. Based on the findings, we present design guidelines for making interactive visualizations more accessible to older adults.

Many people with upper-body motor impairments encounter challenges while performing Activities of Daily Living (ADLs) and Instrumental Activities of Daily Living (IADLs), such as toileting, grooming, and managing finances, which have impacts on their Quality of Life (QOL). Although existing assistive technologies enable people with upper-body motor impairments to use different input modalities to interact with computing devices independently (e.g., using voice to interact with a computer), many people still require Personal Care Assistants (PCAs) to perform ADLs. Multimodal input has the potential to enable users to perform ADLs without human assistance. We conducted 12 semi-structured interviews with people who have upper-body motor impairments to capture their existing practices and challenges of performing ADLs, identify opportunities to expand the input possibilities for assistive devices, and understand user preferences for multimodal interaction during everyday tasks. Finally, we discuss implications for the design and use of multimodal input solutions to support user independence and collaborative experiences when performing daily living tasks.

Makeup and cosmetics offer the potential for self-expression and the reshaping of social roles for visually impaired people. However, there exist barriers to conducting a beauty regime because of the reliance on visual information and color variances in makeup. We present a content analysis of 145 YouTube videos to demonstrate visually impaired individuals’ unique practices before, during, and after doing makeup. Based on the makeup practices, we then conducted semi-structured interviews with 12 visually impaired people to discuss their perceptions of and challenges with the makeup process in more depth. Overall, through our findings and discussion, we present novel perceptions of makeup from visually impaired individuals (e.g., broader representations of blindness and beauty). The existing challenges provide opportunities for future research to address learning barriers, insufficient feedback, and physical and environmental barriers, making the experience of doing makeup more accessible to people with visual impairments.

Deaf and Hard-of-Hearing (DHH) audiences have long complained about caption qualities for many online videos created by individual content creators on video-sharing platforms (e.g., YouTube). However, there lack explorations of practices, challenges, and perceptions of online video captions from the perspectives of both individual content creators and DHH audiences. In this work, we first explore DHH audiences' feedback on and reactions to YouTube video captions through interviews with 13 DHH individuals, and uncover DHH audiences' experiences, challenges, and perceptions on watching videos created by individual content creators (e.g., manually added caption tags could create additional confidence and trust in caption qualities for DHH audiences). We then discover individual content creators' practices, challenges, and perceptions on captioning their videos (e.g., back-captioning problems) by conducting a YouTube video analysis with 189 captioning-related YouTube videos, followed by a survey with 62 individual content creators. Overall, our findings provide an in-depth understanding of captions generated by individual content creators and bridge the knowledge gap mutually between content creators and DHH audiences on captions.

The reliance on vision for tasks related to cooking and eating healthy can present barriers to cooking for oneself and achieving proper nutrition. There has been little research exploring cooking practices and challenges faced by people with visual impairments. We present a content analysis of 122 YouTube videos to highlight the cooking practices of visually impaired people, and we describe detailed practices for 12 different cooking activities (e.g., cutting and chopping, measuring, testing food for doneness). Based on the cooking practices, we also conducted semi-structured interviews with 12 visually impaired people who have cooking experience and show existing challenges, concerns, and risks in cooking (e.g., tracking the status of tasks in progress, verifying whether things are peeled or cleaned thoroughly). We further discuss opportunities to support the current practices and improve the independence of people with visual impairments in cooking (e.g., zero-touch interactions for cooking). Overall, our findings provide guidance for future research exploring various assistive technologies to help people cook without relying on vision.

Despite the potential benefits of assistive technologies (ATs) for people with various disabilities, only around 7% of Chinese with disabilities have had an opportunity to use ATs. Even for those who have used ATs, the abandonment rate was high. Although China has the world's largest population with disabilities, prior research exploring how ATs are used and perceived, and why ATs are abandoned have been conducted primarily in North America and Europe. In this paper, we present an interview study conducted in China with 26 people with various disabilities to understand their practices, challenges, perceptions, and misperceptions of using ATs. From the study, we learned about factors that influence AT adoption practices (e.g., misuse of accessible infrastructure, issues with replicating existing commercial ATs), challenges using ATs in social interactions (e.g., Chinese stigma), and misperceptions about ATs (e.g., ATs should overcome inaccessible social infrastructures). Informed by the findings, we derive a set of design considerations to bridge the existing gaps in AT design (e.g., manual vs. electronic ATs) and to improve ATs' social acceptability in China.

Teeth gestures become an alternative input modality for different situations and accessibility purposes. In this paper, we present TeethTap, a novel eyes-free and hands-free input technique, which can recognize up to 13 discrete teeth tapping gestures. TeethTap adopts a wearable 3D printed earpiece with an IMU sensor and a contact microphone behind both ears, which works in tandem to detect jaw movement and sound data, respectively. TeethTap uses a support vector machine to classify gestures from noise by fusing acoustic and motion data, and implements K-Nearest-Neighbor (KNN) with a Dynamic Time Warping (DTW) distance measurement using motion data for gesture classification. A user study with 11 participants demonstrated that TeethTap could recognize 13 gestures with a real-time classification accuracy of 90.9% in a laboratory environment. We further uncovered the accuracy differences on different teeth gestures when having sensors on single vs. both sides. Moreover, we explored the activation gesture under real-world environments, including eating, speaking, walking and jumping. Based on our findings, we further discussed potential applications and practical challenges of integrating TeethTap into future devices.

ThumbTrak is a novel wearable input device that recognizes 12 micro-finger poses in real-time. Poses are characterized by the thumb touching each of the 12 phalanges on the hand. It uses a thumb-ring, built with a flexible printed circuit board, which hosts nine proximity sensors. Each sensor measures the distance from the thumb to various parts of the palm or other fingers. ThumbTrak uses a support-vector-machine (SVM) model to classify finger poses based on distance measurements in real-time. A user study with ten participants showed that ThumbTrak could recognize 12 micro finger poses with an average accuracy of 93.6%. We also discuss potential opportunities and challenges in applying ThumbTrak in real-world applications.

Eye-based interactions for people with motor impairments have often used clunky or specialized equipment (e.g., eye-trackers with non-mobile computers) and primarily focused on gaze and blinks. However, two eyelids can open and close for different duration in different orders to form various eyelid gestures. We take a first step to design, detect, and evaluate a set of eyelid gestures for people with motor impairments on mobile devices. We present an algorithm to detect nine eyelid gestures on smartphones in real-time and evaluate it with twelve able-bodied people and four people with severe motor impairments in two studies. The results of the study with people with motor-impairments show that the algorithm can detect the gestures with .76 and .69 overall accuracy in user-dependent and user-independent evaluations. Moreover, we design and evaluate a gesture mapping scheme allowing for navigating mobile applications only using eyelid gestures. Finally, we present recommendations for designing and using eyelid gestures for people with motor impairments.

In this paper, we present BrailleSketch, a gesture-based text input method on touchscreen smartphones for people with visual impairments. To input a letter with BrailleSketch, a user simply sketches a gesture that passes through all dots in the corresponding Braille code for that letter. BrailleSketch allows users to place their fingers anywhere on the screen to begin a gesture and draw the Braille code in many ways. To encourage users to type faster, BrailleSketch does not provide immediate letter-level audio feedback but instead provides word-level audio feedback. It uses an auto-correction algorithm to correct typing errors. Our evaluation of the method with ten participants with visual impairments who each completed five typing sessions shows that BrailleSketch supports a text entry speed of 14.53 word per min (wpm) with 10.6% error. Moreover, our data suggest that the speed had not begun to plateau yet by the last typing session and can continue to improve. Our evaluation also demonstrates the positive effect of the reduced audio feedback and the auto-correction algorithm.