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• VeasyGuide: Personalized Visual Guidance for Low-vision Learners on Instructor Actions in Presentation Videos

  Mohamad Elayyan Sechayk, Himanshu Singh, Jan Smeddinck, Chakkrit Tantithamthavorn · 2025 · ASSETS 2025: 27th International ACM SIGACCESS Conference on Computers and Accessibility

  This paper introduces VeasyGuide, a tool designed to make presentation videos more accessible for low-vision (LV) learners by automatically detecting and highlighting instructor actions such as pointing, marking, and sketching. The authors identify a significant gap in current…

  low vision · video accessibility · e-learning · motion detection · visual guidance

• FocusView: Understanding and Customizing Informational Video Watching Experiences for Viewers with ADHD

  Hanxiu Hazel Zhu, Ruijia Chen, Yuhang Zhao · 2025 · ASSETS 2025: 27th International ACM SIGACCESS Conference on Computers and Accessibility

  This paper presents FocusView, an AI-powered video customization interface designed to help viewers with ADHD reduce distractions and maintain focus when watching informational videos. The research addresses the critical gap that while videos have become a dominant medium for…

  ADHD · video accessibility · video customization · distraction reduction · cognitive accessibility

• DescribePro: Collaborative Audio Description with Human-AI Interaction

  Maryam S Cheema, Sina Elahimanesh, Samuel Martin, Pooyan Fazli, Hasti Seifi · 2025 · ASSETS 2025: 27th International ACM SIGACCESS Conference on Computers and Accessibility

  This paper presents DescribePro, a web-based platform that combines human expertise with AI capabilities to create and refine audio descriptions (AD) for video content. The system addresses the fundamental tension in AD production: human-crafted descriptions are high quality but…

  audio description · video accessibility · human-AI collaboration · authoring tools · blind and low vision

• Making Lecture Videos Accessible for Students who are Blind or have Low Vision through AI-Assisted Navigation and Visual Question Answering

  Katharina Anderer, Karin Müller, Lukas Strobel, Matthias Wölfel, Jan Niehues, Kathrin Gerling · 2025 · Proceedings of the 27th International ACM SIGACCESS Conference on Computers and Accessibility (ASSETS 2025)

  This paper presents the design and evaluation of LectureAssistant, an AI-powered prototype that makes lecture videos more accessible for students who are blind or have low vision. The research follows a three-part human-centred design process. First, need-finding interviews with…

  blind and low vision · lecture accessibility · higher education · large language models · vision-language models

• NoTeeline: Supporting Real-Time, Personalized Notetaking with LLM-Enhanced Micronotes

  Faria Huq, Abdus Samee, David Chuan-En Lin, Alice Xiaodi Tang, Jeffrey P. Bigham · 2025 · Proceedings of the 30th International Conference on Intelligent User Interfaces (IUI '25)

  This paper introduces NoTeeline, an interactive notetaking tool that uses LLMs to expand user-written "micronotes" — brief shorthand jottings like "plastic pol. ->" or "RNNs are unrolled l to r or opp" — into full-fledged notes that maintain the user's personal writing style.…

  large language models · writing assistance · personalization · notetaking · cognitive load

5 results.