Accessible Bar Charts for Visually Impaired Users

S. Elzer, E. Schwartz, S. Carberry, D. Chester, S. Demir, and P. Wu (USA)


assistive technology, artificial intelligence, information graphics, natural language processing


This paper presents a novel approach to enabling visually impaired users to gain access to bar charts on theWeb. Our approach differs from previous work by providing the user with the message and knowledge that one would gain from viewing the graphic rather than providing alternative access to the appearance of the graphic. The user interface to the system is implemented as a browser extension. The output of the system is a textual summary, the core content of which is the hypothesized intended message of the graphic designer, as inferred by our Bayesian network. The summary is conveyed to the user by screen reading software. User evaluations have shown the system to be both useful and effective.

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