洞察：利用LLMs增强视障和视觉障碍用户移动设备的可访问性
Insight: Enhancing Mobile Accessibility for Blind and Visually Impaired Users with LLMs
AI总结：
本文提出Insight，一种基于LLM的Android无障碍服务，通过自然语言交互和实时屏幕摘要提升视障用户体验，实验显示其在减少心理努力和任务时间方面优于TalkBack。
摘要：
本文研究了当前移动无障碍服务如TalkBack的局限性，这些服务通过手动手势提供顺序反馈。受大型语言模型（LLMs）的启发，本文提出Insight，一种基于Android的无障碍服务，提供自然语言交互和实时屏幕摘要。论文通过用户实验比较Insight和TalkBack的可用性因素。结果表明，Insight在减少心理努力和任务时间方面优于TalkBack，并因其对话界面而受到青睐，但用户感到需要中断管理。结果表明，基于LLM的界面可以显著提高移动无障碍性，并描述了结合手势和对话模式的混合解决方案在更包容设计中的潜力。
英文摘要：
This research paper addresses the limitations of current mobile accessibility services like TalkBack, which provide manual gesture-based sequential feedback to BVI users. Motivated by the promise of large language models (LLMs), this paper introduces Insight, an Android accessibility service that provides natural language interaction and real-time summarization of the screen. The paper performs a within-subject experimental study with users to compare Insight and TalkBack on usability factors. Results show Insight reduced mental effort and task time, and was preferred because of its dialogue interface, but users felt the need for interruption management. Results show LLM-based interfaces can significantly improve mobile accessibility, and describe the potential of hybrid solutions combining gesture and dialogue modalities towards more inclusive design.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
