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• The State of Accessibility in Blackboard: Survey and User Reviews Case Study

  Wajdi Aljedaani, Mohammed Alkahtani, Stephanie Ludi, Mohamed Wiem Mkaouer, Marcelo M. Eler, Marouane Kessentini, Ali Ouni · 2023 · Proceedings of the 20th International Web for All Conference (W4A)

  This paper investigates the accessibility of the Blackboard mobile app, one of the most widely used Learning Management Systems (LMS) in higher education, through a two-pronged methodology. First, the authors conducted a large-scale survey with 1,308 hearing students and 65 deaf…

  mobile accessibility · learning management systems · deaf and hard of hearing · education accessibility · user reviews

• On the independent and sustainable mobility of people with visual impairments

  Gabriele Galimberti · 2023 · Proceedings of the 20th International Web for All Conference (W4A '23)

  This doctoral consortium extended abstract outlines a research project investigating the factors that enable or hinder independent mobility for people with blindness or visual impairments (BVI), with a particular focus on the link between mobility autonomy and environmental…

  visual impairment · blind and low vision · independent living · public transportation · navigation

• "I stepped into a puddle": Non-Visual Texting in Nomadic Contexts

  Pegah Karimi, Erin Brady, Aqueasha Martin-Hammond, Davide Bolchini · 2023 · Proceedings of the 20th International Web for All Conference (W4A '23)

  This study investigates the under-explored practice of texting by people who are blind and visually impaired (BVI) while navigating outdoors — what the authors term "nomadic contexts." While previous research has examined accessible text entry methods (screen readers, speech…

  blind and low vision · text entry · mobile accessibility · navigation · assistive technology

• Understanding Personalized Accessibility through Teachable AI: Designing and Evaluating Find My Things for People who are Blind or Low Vision

  Cecily Morrison, Martin Grayson, Rita Faia Marques, Daniela Massiceti, Camilla Longden, Linda Wen, Edward Cutrell · 2023 · Proceedings of the 25th International ACM SIGACCESS Conference on Computers and Accessibility (ASSETS '23)

  This paper from Microsoft Research presents Find My Things, one of the first fully realized end-to-end teachable AI applications for accessibility. The app allows people who are blind or low vision to teach their phone to recognize personal objects — keys, earbuds, lip balm,…

  teachable AI · object recognition · blind and low vision · personalization · few-shot learning

• AdaptiveSound: An Interactive Feedback-Loop System to Improve Sound Recognition for Deaf and Hard of Hearing Users

  Hang Do, Quan Dang, Jeremy Zhengqi Huang, Dhruv Jain · 2023 · ASSETS '23: Proceedings of the 25th International ACM SIGACCESS Conference on Computers and Accessibility

  This paper introduces AdaptiveSound, the first feedback-loop sound recognition system designed for deaf and hard of hearing (DHH) users. Sound recognition tools help DHH people become aware of environmental sounds ranging from safety-critical alerts like fire alarms and sirens…

  deaf and hard of hearing · sound recognition · human-in-the-loop · machine learning · incremental learning

• "I just thought it was me": How Smartphones Fail Users with Mild-to-Moderate Dexterity Differences

  Molly Bowman, Jerry Robinson, Erin Buehler, Shaun Kane · 2023 · Proceedings of the 25th International ACM SIGACCESS Conference on Computers and Accessibility (ASSETS 2023)

  This paper examines the smartphone experiences of people with mild-to-moderate dexterity (MMD) challenges — a population largely overlooked by accessibility research that tends to focus on more severe motor disabilities requiring specialized assistive technology like switches.…

  motor disability · dexterity · mobile accessibility · smartphones · touch screen

• Never-ending Learning of User Interfaces

  Jason Wu, Rebecca Krosnick, Eldon Schoop, Amanda Swearngin, Jeffrey P. Bigham, Jeffrey Nichols · 2023 · Proceedings of the 36th Annual ACM Symposium on User Interface Software and Technology (UIST)

  This paper introduces the Never-ending UI Learner, an automated system that continuously crawls real mobile applications to learn semantic properties of user interfaces. The system addresses a fundamental limitation of current approaches to UI understanding: most machine…

  machine learning · mobile accessibility · UI semantics · automated crawling · tappability

• WebUI: A Dataset for Enhancing Visual UI Understanding with Web Semantics

  Jason Wu, Siyan Wang, Siman Shen, Yi-Hao Peng, Jeffrey Nichols, Jeffrey P. Bigham · 2023 · Proceedings of the 2023 CHI Conference on Human Factors in Computing Systems

  This paper introduces WebUI, a large-scale dataset of approximately 400,000 web pages automatically crawled and paired with visual, semantic, and stylistic metadata extracted from the browser engine. The dataset addresses a critical bottleneck in UI understanding research:…

  machine learning · computer vision · UI modeling · web semantics · transfer learning

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