SNAG: Spoken Narratives and Gaze Dataset

Preethi Vaidyanathan, Emily T. Prud'hommeaux, Jeff B. Pelz, Cecilia O. Alm

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.