Literature Reviews

Reviewed research papers, articles, and publications relevant to digital accessibility.

• Can a Blind Person Understand Your World?

  Chieko Asakawa (2014) — Proceedings of the 11th Web for All Conference (W4A)

  This keynote paper by Chieko Asakawa of IBM Research presents a vision for the next frontier of accessibility for blind people: moving from digital information access to real-world understanding through cognitive computing. Asakawa charts the exponen…

  • blindness
  • cognitive assistance
  • image recognition
  • computer vision
  • machine learning
  • crowdsourcing
  • assistive technology
  • navigation
  • augmented reality

• Exploring Accessibility of Mobile Applications Through User Feedback: Insights from App Reviews in a Systematic Literature Review

  Alberto Dumont Alves Oliveira, Marcelo Medeiros Eler (2024) — Proceedings of the XXIII Brazilian Symposium on Human Factors in Computing Systems (IHC 2024)

  This systematic literature review examines how user reviews from app stores have been used to study the accessibility of mobile applications. The authors searched five major academic databases (ACM, IEEE, ScienceDirect, Scopus, and Web of Science) an…

  • mobile accessibility
  • app reviews
  • user feedback
  • systematic literature review
  • user reviews
  • Android
  • machine learning
  • accessibility barriers

• Dialog Generation for Voice Browsing

  Zan Sun, Amanda Stent, I. V. Ramakrishnan (2006) — Proceedings of the 2006 International Cross-Disciplinary Workshop on Web Accessibility (W4A): Building the Mobile Web: Rediscovering Accessibility?

  This paper presents HearSay, a voice browser system developed at Stony Brook University that provides speech-driven web access for people with visual disabilities. Unlike conventional screen readers that force users to arrow through a linearized, sin…

  • voice browsing
  • screen readers
  • visual impairment
  • web page segmentation
  • content summarization
  • machine learning
  • VoiceXML
  • dialog systems
  • assistive technology

• Prediction of Web Page Accessibility Based on Structural and Textual Features

  Sina Bahram, Debadeep Sen, Robert St. Amant (2011) — Proceedings of the International Cross-Disciplinary Conference on Web Accessibility (W4A)

  This paper from NC State University explores whether machine learning classifiers can predict the accessibility of web pages based on structural and textual features of their DOM — features that are independent of explicit accessibility markup like a…

  • machine learning
  • accessibility evaluation
  • automated testing
  • visual impairment
  • web accessibility
  • accessibility metrics
  • artificial intelligence

• An Adaptive Videos Enrichment System Based on Decision Trees for People with Sensory Disabilities

  José Francisco Saray Villamizar, Benoît Encelle, Yannick Prié, Pierre-Antoine Champin (2011) — Proceedings of the International Cross-Disciplinary Conference on Web Accessibility (W4A)

  This paper from the ACAV (Collaborative Annotation for Video Accessibility) project at the University of Lyon proposes an adaptive system that personalises how video accessibility descriptions are presented to users with sensory disabilities. The cor…

  • video accessibility
  • multimedia accessibility
  • machine learning
  • personalization
  • adaptive systems
  • audio description
  • sensory disabilities
  • decision trees
  • blind and low vision
  • deaf and hard of hearing

• Efficient and Effective Information Finding on Small Screen Devices

  Pauli P. Y. Lai (2013) — Proceedings of the 10th International Cross-Disciplinary Conference on Web Accessibility (W4A)

  This paper proposes a reverse engineering approach for automatically adapting desktop-oriented webpages for efficient information seeking on small-screen mobile devices. The core contribution is a "semantic-DOM tree" model that analyzes the relations…

  • mobile accessibility
  • content adaptation
  • responsive design
  • web accessibility
  • information architecture
  • semantic HTML
  • machine learning

• Intelligent Assistive Communication and the Web as a Social Medium

  Karl Wiegand (2014) — Proceedings of the 11th Web for All Conference (W4A)

  This short paper presents doctoral research on applying natural language processing (NLP) and machine learning to improve augmentative and alternative communication (AAC) systems, with a particular focus on enabling web-based social interaction for p…

  • augmentative and alternative communication
  • AAC
  • natural language processing
  • machine learning
  • social media accessibility
  • brain-computer interface
  • speech impairment
  • icon-based communication

• Automatically Generating and Improving Voice Command Interface from Operation Sequences on Smartphones

  Lihang Pan, Chun Yu, JiaHui Li, Tian Huang, Xiaojun Bi, Yuanchun Shi (2022) — Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems

  This paper presents AutoVCI, a system that automatically generates voice command interfaces (VCIs) for smartphone tasks from recorded touch operation sequences, enabling hands-free and eyes-free interaction without requiring programming expertise, co…

  • voice command interface
  • mobile accessibility
  • speech recognition
  • natural language understanding
  • programming by demonstration
  • smartphone automation
  • machine learning
  • GUI accessibility

• Look Ma, No ARIA: Generic Accessible Interfaces for Web Widgets

  Valentyn Melnyk, Vikas Ashok, Yury Puzis, Yevgen Borodin, Andrii Soviak, I. V. Ramakrishnan (2015) — Proceedings of the 12th International Web for All Conference (W4A)

  This paper proposes an alternative approach to web widget accessibility that bypasses ARIA entirely. Rather than relying on web developers to correctly implement ARIA markup — which is often missing, incorrect, or inconsistent — the system automatica…

  • widget accessibility
  • screen readers
  • WAI-ARIA
  • machine learning
  • web chat
  • blind users
  • dynamic content
  • widget recognition

• Detecting Readers with Dyslexia Using Machine Learning with Eye Tracking Measures

  Luz Rello, Miguel Ballesteros (2015) — Proceedings of the 12th International Web for All Conference (W4A)

  This paper presents the first machine learning model to automatically detect readers with dyslexia using eye tracking data. The authors trained a Support Vector Machine (SVM) binary classifier on a dataset of 1,135 readings from 97 Spanish-speaking p…

  • dyslexia
  • eye tracking
  • machine learning
  • detection
  • support vector machine
  • reading accessibility
  • learning disabilities