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• WLA4ND: a Wearable Dataset of Learning Activities for Young Adults with Neurodiversity to Provide Support in Education

  Hui Zheng, Pattiya Mahapasuthanon, Yujing Chen, Huzefa Rangwala, Anya S Evmenova, Vivian Genaro Motti · 2021 · Proceedings of the 23rd International ACM SIGACCESS Conference on Computers and Accessibility (ASSETS '21)

  This paper introduces WLA4ND (Wearable Learning Activities for Neurodiversity), the first wearable sensor dataset of learning activities collected from young adults with neurodiversity. While existing wearable sensor datasets focus on fitness, daily living, and locomotion…

  neurodiversity · wearable technology · machine learning · activity recognition · inclusive education

• Sharing Practices for Datasets Related to Accessibility and Aging

  Rie Kamikubo, Utkarsh Dwivedi, Hernisa Kacorri · 2021 · The 23rd International ACM SIGACCESS Conference on Computers and Accessibility (ASSETS 2021)

  This paper presents a systematic review of 137 accessibility datasets collected from people with disabilities and older adults over a 35-year period (1984-2020). The authors undertook an extensive two-year search process using a multilayer strategy: open searches on search…

  datasets · machine learning · data sharing · privacy · ethics

• Fluent: An AI Augmented Writing Tool for People who Stutter

  Bhavya Ghai, Klaus Mueller · 2021 · The 23rd International ACM SIGACCESS Conference on Computers and Accessibility (ASSETS 2021)

  This paper presents Fluent, a novel AI-powered writing tool designed to help people who stutter (PWS) prepare scripts and written content that they can deliver more fluently. Over 70 million people worldwide stutter, and a common coping strategy is word substitution — replacing…

  stuttering · speech disorders · machine learning · active learning · natural language processing

• Disability-first Dataset Creation: Lessons from Constructing a Dataset for Teachable Object Recognition with Blind and Low Vision Data Collectors

  Lida Theodorou, Daniela Massiceti, Luisa Zintgraf, Simone Stumpf, Cecily Morrison, Edward Cutrell, Matthew Tobias Harris, Katja Hofmann · 2021 · Proceedings of the 23rd International ACM SIGACCESS Conference on Computers and Accessibility (ASSETS '21)

  This paper presents a disability-first approach to constructing a machine learning dataset for teachable object recognition, developed through the ORBIT (Objects that Recognize Blind Individuals in Their environment) project. The authors argue that while AI for accessibility is…

  disability-first design · dataset creation · teachable object recognition · blind and low vision · machine learning

• Activity Recognition in Older Adults with Training Data from Younger Adults: Preliminary Results on in Vivo Smartwatch Sensor Data

  Sabahat Fatima · 2021 · Proceedings of the 23rd International ACM SIGACCESS Conference on Computers and Accessibility (ASSETS '21)

  This extended abstract investigates a critical age-related bias in wearable activity recognition: models trained on data from younger adults perform significantly worse when applied to older adults. The study is motivated by the growing potential of smartwatch-based…

  older adults · activity recognition · machine learning · wearable technology · smartwatch

• The FATE Landscape of Sign Language AI Datasets: An Interdisciplinary Perspective

  Danielle Bragg, Oscar Koller, Mary Bellard, Larwan Berke, Patrick Boudreault, Annelies Braffort, Naomi Caselli, Matt Huenerfauth, Hernisa Kacorri, Tessa Verhoef, Christian Vogler, Meredith Ringel Morris · 2021 · ACM Transactions on Accessible Computing

  This interdisciplinary paper examines the ethical landscape of AI datasets used for sign language recognition, generation, and translation technologies. Drawing on expertise from deaf community members, sign language linguists, and AI researchers, the authors apply the FATE…

  sign language · AI datasets · deaf community · FATE framework · machine learning

• How Could Equality and Data Protection Law Shape AI Fairness for People with Disabilities?

  Reuben Binns, Reuben Kirkham · 2021 · ACM Transactions on Accessible Computing

  This interdisciplinary paper examines how UK equality law and EU data protection law (GDPR) intersect with AI fairness for people with disabilities (PWD). The authors argue that AI fairness for PWD requires a fundamentally different approach than for other protected…

  AI fairness · disability discrimination · data protection · GDPR · equality law

• Screen Parsing: Towards Reverse Engineering of UI Models from Screenshots

  Jason Wu, Xiaoyi Zhang, Jeff Nichols, Jeffrey P. Bigham · 2021 · The 34th Annual ACM Symposium on User Interface Software and Technology (UIST)

  This paper introduces screen parsing, the task of predicting UI elements and their hierarchical relationships from a screenshot alone. While prior work could detect individual UI elements on a screen (element detection), those approaches produced flat lists of elements with no…

  screen readers · mobile accessibility · computer vision · UI semantics · machine learning

• Screen Recognition: Creating Accessibility Metadata for Mobile Applications from Pixels

  Xiaoyi Zhang, Lilian de Greef, Amanda Swearngin, Samuel White, Kyle Murray, Lisa Yu, Qi Shan, Jeffrey Nichols, Jason Wu, Chris Fleizach, Aaron Everitt, Jeffrey P. Bigham · 2021 · CHI Conference on Human Factors in Computing Systems

  This paper from Apple introduces Screen Recognition, a system that automatically generates accessibility metadata for mobile apps by analyzing their visual pixels, enabling screen readers to work with apps that lack proper developer-provided accessibility information. The…

  mobile accessibility · screen readers · machine learning · object detection · VoiceOver

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