Robitaille (2010) wrote ‘if all technology companies have accessibility in their mind then people with disabilities won’t be left behind.’ Current technology has come a long way from where it stood decades ago; however, researchers and manufacturers often do not include people with disabilities in the design process and tend to accommodate them after the fact. In this paper we share feedback from four assistive technology users who rely on one or more assistive technology devices in their everyday lives. We believe end users should be part of the design process and that by bringing together experts and users, we can bridge the research/practice gap.

Humans rely on multiple sensory modalities when examining and reasoning over images. In this paper, we describe a new multimodal dataset that consists of gaze measurements and spoken descriptions collected in parallel during an image inspection task. The task was performed by multiple participants on 100 general-domain images showing everyday objects and activities. We demonstrate the usefulness of the dataset by applying an existing visual-linguistic data fusion framework in order to label important image regions with appropriate linguistic labels.