Accessible Bar Charts Through Textual Description Templates - Oliveira, Cynthya Leticia Teles de; Silva, Alan Trindade de Almeida; Morais, Jefferson Magalhães de; Mota, Marcelle Pereira (Journal of the Brazilian Computer Society, 2023)
Data charts are very prevalent in everyday life in different contexts, from economics to politics. However, people with blindness and low vision do not have easy access to this information since they use screen reader software. This software does not extract the information available graphically, but only the chart legend and the text. Among the solutions proposed in the literature, there are crowdsourcing techniques when a person is responsible for interpreting the chart, which can cause bias in the chart’s interpretation. To solve this problem, we proposed textual description templates for simple and grouped bar charts to inform the chart data in a standardized way to users, excluding the interpretation bias. The methodology of this work was divided into three stages: a definition of templates for textual description and testing with 30 participants; the application of textual description templates in an assistive technology tool and testing with 45 participants; the validation of the results found through interviews and tests with 3 specialists. We have iteratively refined templates generated at each stage with users tests, and we carried out quantitative and qualitative analyses. An assistive technology tool, ChartVision, was developed to consume the templates. Finally, we interviewed a specialist about how he would explain chart materials to blind students at university, and we carried out a validation of the final templates with two other professionals from the health and education areas who deal with people with blind people in their daily lives. The main contributions are three textual description bar charts templates: simple bar for applications with sequential reading or reading on-demand, grouped bar for applications with sequential reading, and grouped bar for applications on-demand. The secondary contribution is ChartVision. Other findings include considerations about the synthetic voice used in the tests, expected characteristics for a better understanding of the chart, and interaction ways to access the information.