EyeDescribe: Combining Eye Gaze and Speech to Automatically Create Accessible Touch Screen Artwork
Kyle Reinholt, Darren Guinness, Shaun K. Kane
ISS '19: ACM International Conference on Interactive Surfaces and Spaces
Session: Pen and Novel Interactions
Abstract
Many images on the Web, including photographs and artistic images, feature spatial relationships between objects that are inaccessible to someone who is blind or visually impaired even when a text description is provided. While some tools exist to manually create accessible image descriptions, this work is time consuming and requires specialized tools. We introduce an approach that automatically creates spatially registered image labels based on how a sighted person naturally interacts with the image. Our system collects behavioral data from sighted viewers of an image, specifically eye gaze data and spoken descriptions, and uses them to generate a spatially indexed accessible image that can then be explored using an audio-based touch screen application. We describe our approach to assigning text labels to locations in an image based on eye gaze. We then report on two formative studies with blind users testing EyeDescribe. Our approach resulted in correct labels for all objects in our image set. Participants were able to better recall the location of objects when given both object labels and spatial locations. This approach provides a new method for creating accessible images with minimum required effort.
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Recorded at the 2019 ACM International Conference on Interactive Surfaces and Spaces, Daejeon, South Korea, November 10 - 13 2019
