Reviews

Search results

• Fairness of AI for People with Disabilities: Problem Analysis and Interdisciplinary Collaboration

  Jason J. G. White · 2020 · SIGACCESS Accessibility and Computing

  This paper provides a philosophical analysis of the fairness challenges that machine learning-based AI poses for people with disabilities, arguing that these challenges demand unprecedented interdisciplinary collaboration across applied ethics, human rights law, disability…

  AI fairness · algorithmic bias · disability · social justice · ethics

• Screening Risk of Dyslexia Through a Web-Game Using Language-Independent Content and Machine Learning

  Maria Rauschenberger, Ricardo Baeza-Yates, Luz Rello · 2020 · Proceedings of the 17th International Web for All Conference (W4A)

  This paper presents MusVis, a web-based game designed to screen for dyslexia risk using language-independent content and machine learning, enabling potential early detection even in pre-readers who have not yet developed literacy skills. Dyslexia affects 5-15% of the world…

  dyslexia · machine learning · screening · serious games · gamification

• Autism Detection Based on Eye Movement Sequences on the Web: A Scanpath Trend Analysis Approach

  Sukru Eraslan, Yeliz Yesilada, Victoria Yaneva, Simon Harper · 2020 · Proceedings of the 17th International Web for All Conference (W4A)

  This paper investigates whether sequential eye-movement data — the order in which people look at elements on web pages — can be used to detect autism, improving upon the authors' previous non-sequential approach that achieved 75% accuracy but was unstable across different web…

  autism · eye tracking · machine learning · web accessibility · scanpath analysis

• Supporting the Design of Data Visualisation for the Visually Impaired through Reinforcement Learning

  Dalal Aljasem · 2020 · Proceedings of the 17th International Web for All Conference (W4A)

  This doctoral consortium paper presents a research programme aimed at making data visualizations more accessible to people with partial vision loss, specifically those with peripheral vision damage (tunnel vision from conditions like glaucoma) or central vision loss (from…

  data visualization · visual impairment · reinforcement learning · visual search · machine learning

• Exploring Collection of Sign Language Datasets: Privacy, Participation, and Model Performance

  Danielle Bragg, Oscar Koller, Naomi Caselli, William Thies · 2020 · Proceedings of the 22nd International ACM SIGACCESS Conference on Computers and Accessibility (ASSETS 2020)

  This paper tackles a fundamental tension in building machine learning systems for marginalized communities: the need for large training datasets versus the privacy risks of collecting data from small, identifiable populations. The authors focus on sign language video collection,…

  sign language · privacy · machine learning · data collection · Deaf culture

• A Mobile Cloud Collaboration Fall Detection System Based on Ensemble Learning

  Tong Wu, Yang Gu, Yiqiang Chen, Jiwei Wang, Siyu Zhang · 2020 · Proceedings of the 22nd International ACM SIGACCESS Conference on Computers and Accessibility (ASSETS)

  This paper addresses fall detection for older adults, which the WHO identifies as the second leading cause of accidental injury death worldwide. Roughly 28-35% of people over 65 experience falls each year, with the rate increasing to 32-42% for those over 70. The authors propose…

  fall detection · machine learning · wearable technology · aging · health monitoring

• SoundWatch: Exploring Smartwatch-based Deep Learning Approaches to Support Sound Awareness for Deaf and Hard of Hearing Users

  Dhruv Jain, Hung Ngo, Pratyush Patel, Steven Goodman, Leah Findlater, Jon Froehlich · 2020 · Proceedings of the 22nd International ACM SIGACCESS Conference on Computers and Accessibility (ASSETS '20)

  This paper presents SoundWatch, a smartwatch-based sound awareness system that uses deep learning to classify environmental sounds in real time and provide visual and haptic notifications to deaf and hard of hearing (DHH) users. The research addresses the finding from prior…

  deaf accessibility · hard of hearing · sound awareness · deep learning · wearable technology

• Computer Vision-based Methodology to Support AAC

  Rúbia Eliza de Oliveira Schultz Ascari, Roberto Pereira, Luciano Silva · 2020 · ACM Transactions on Accessible Computing

  This paper presents a methodology for supporting augmentative and alternative communication (AAC) through personalized gestural interaction using computer vision and machine learning. The authors developed the PGCA (Personal Gesture Communication Assistant) system, which enables…

  AAC · augmentative and alternative communication · computer vision · machine learning · gesture recognition

• Automated Class Discovery and One-Shot Interactions for Acoustic Activity Recognition

  Jason Wu, Chris Harrison, Jeffrey P. Bigham, Gierad Laput · 2020 · Proceedings of the 2020 CHI Conference on Human Factors in Computing Systems (CHI '20)

  This paper presents Listen Learner, an end-to-end system for acoustic activity recognition that automatically discovers and learns to classify environmental sounds with minimal user effort. Traditional approaches to sound recognition face a tradeoff: custom models trained in a…

  acoustic activity recognition · smart home · machine learning · Internet of Things · context awareness

9 results.