Although intelligent interactive systems have been the focus of many research efforts, very few have addressed systems for individuals with disabilities. This article presents our methodology for an intelligent interactive system that provides individuals with sight impairments with access to the content of information graphics (such as bar charts and line graphs) in popular media. The article describes the methodology underlying the system's intelligent behavior, its interface for interacting with users, examples processed by the implemented system, and evaluation studies both of the methodology and the effectiveness of the overall system. This research advances universal access to electronic documents.

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Information graphics (bar charts, line graphs, grouped bar charts, etc) often appear in popular media such as newspapers and magazines. In most cases, the information graphic is intended to convey a high‐level message. This message plays a role in facilitating the discourse purpose of the document but is seldom repeated in the document's text, headlines, or captions. We present a methodology and an implemented system for recognizing the intended message of a grouped bar chart. The recognition system relies on the following components: (1) a linguistic classifier that processes text in the graphic and predicts the most linguistically salient entity from those that are mentioned in text, (2) a cognitive model that estimates the relative perceptual effort required for an individual to recognize some high‐level message in a graph, and (3) a Bayesian network that captures the probabilistic relationship between the high‐level intended message of a graphic and its communicative signals. This research contributes to three applications: accessibility of information graphics for sight‐impaired individuals, retrieval of information graphics from a digital library, and summarization of multimodal documents.

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