Speaking with LLMs: Co-Designing Voice Interaction Patterns with Blind and Visually Impaired Users
Year: 2026
Type: article
Abstract: The widespread availability of chat-based interfaces for LLMs, such as ChatGPT, has brought AI into everyday professional and personal contexts. Ensuring the inclusivity of this prompt-based interaction paradigm is therefore essential. This paper responds to this need by presenting a human-centered design study involving 119 blind and visually impaired (BVI) individuals. Through questionnaires, interviews, and focus groups, we identified key challenges and derived design patterns for voice interactions with LLMs. These patterns specifically address tasks that remain difficult for BVI users, such as accessing and controlling lengthy model-generated responses, refining prompts iteratively, and retrieving content from past chats. We implemented the identified patterns in a web platform and validated them through additional focus groups. With these contributions, we aim to provide a foundation for the inclusive design of voice interactions with chat-based LLM systems.
Source: Figshare
Language: English
Subfield: Human Factors and Ergonomics
Field: Social Sciences
Domain: Social Sciences
SDG: Reduced inequalities
Open Access status: green
OpenAlex ID: W7165937303