Authors:
Aspen Belle
1
;
Vanessa Goh
1
;
Akshay Kumar
1
;
Richard Pranjatno
1
;
Pui Man Yip
1
;
Umayangani Wickramaratne
2
and
Humphrey O. Obie
1
Affiliations:
1
Faculty of Information Technology, Monash University, Melbourne, Australia
;
2
Academy Xi, Melbourne, Australia
Keyword(s):
Visualization, Accessible Visualizations, Alternative Text, Caption Generation, SVG, Data Extraction, Accessibility.
Abstract:
Data visualizations are used everywhere on the web to convey data and insight. However, interpreting these visualizations is reliant on sight, which poses a problem for the visually impaired who rely on screen readers. Alternative text descriptions are often missing from visualizations or not of a helpful quality, which the screen readers rely on to interpret them for the user. In this short paper, we propose Alt-Texify, a pipeline to generate alternative text descriptions for SVG-based bar, line and scatter charts. Our pipeline classifies the chart type and extracts the data and labels from the SVG code and inserts the relevant information into a description template. Our approach extracts the data and labels deterministically, allowing for factually accurate descriptions 99.74% of the time.