Year: 2026
Type: article
Abstract: Web forms are a critical gateway to online services, yet they remain challenging for blind and visually impaired (BVI) users. Despite accessibility standards, screen reader workflows often prove frustrating and error-prone. This paper investigates how conversational agents (CAs) powered by Large Language Models (LLMs) can enable more accessible, voice-based interaction with online forms. Through a human-centered process involving guidelines analysis, stakeholder consultations, prototyping and a study with 18 BVI participants, we explored how LLM-driven CAs can support data entry, navigation, and input verification. Findings show that participants valued the system’s intuitiveness and reliability but highlighted tensions around verbosity, pacing, and control. From these insights, we derive design patterns that translate abstract voice interaction guidelines into concrete strategies for conversational form filling, contributing to more inclusive digital services for BVI users and beyond.
Institution: Politecnico di Milano
Language: English
Subfield: Human Factors and Ergonomics
Field: Social Sciences
Domain: Social Sciences
SDG: Reduced inequalities
Open Access status: hybrid
Estimated APC paid: $3,510
OpenAlex ID: W7208815650