CollabAlly: Accessible Collaboration Awareness in Document Editing

CHI Conference on Human Factors in Computing Systems · 2022 · 26 citations

• Computer Science
• Computer Science
• World Wide Web

Collaborative document editing tools are widely used in professional and academic workplaces. While these tools provide basic accessibility support, it is challenging for blind users to gain collaboration awareness that sighted people can easily obtain using visual cues (e.g., who is editing where and what). Through a series of co-design sessions with a blind coauthor, we identified the current practices and challenges in collaborative editing, and iteratively designed CollabAlly, a system that makes collaboration awareness in document editing accessible to blind users. CollabAlly extracts collaborator, comment, and text-change information and their context from a document and presents them in a dialog box to provide easy access and navigation. CollabAlly uses earcons to communicate background events unobtrusively, voice fonts to differentiate collaborators, and spatial audio to convey the location of document activity. In a study with 11 blind participants, we demonstrate that CollabAlly provides improved access to collaboration awareness by centralizing scattered information, sonifying visual information, and simplifying complex operations.

TutorialLens: Authoring Interactive Augmented Reality Tutorials Through Narration and Demonstration

Symposium on Spatial User Interaction · 2021 · 20 citations

• Computer Science
• Computer Science
• Human–computer interaction

Exploring unfamiliar devices and interfaces through trial and error can be challenging and frustrating. Existing video tutorials require frequent context switching between the device showing the tutorial and the device being used. While augmented reality (AR) has been adopted to create user manuals, many are inflexible for diverse tasks, and usually require programming and AR development experience. We present TutorialLens, a system for authoring interactive AR tutorials through narration and demonstration. To use TutorialLens, authors demonstrate tasks step-by-step while verbally explaining what they are doing. TutorialLens automatically detects and records 3D finger positions and guides authors to capture important changes of the device. Using the created tutorials, TutorialLens then provides AR visual guidance and feedback for novice device users to complete the demonstrated tasks. TutorialLens is automated, friendly to users without AR development experience, and applicable to a variety of devices and tasks.