Specific Aims There are many modern approaches to accessibility in data visualizations, from simple but inadequate alternative data tables to excellent work with tactile graphics, haptics, and sonification. Each has its benefits and limitations, but common underlying weaknesses to the advanced methods are lack of precision and need for reader training. By contrast, most of the 7.7 million Americans with visual disabilities are at least moderately skilled in using a screen reader. However, this typically limits users to serial data point access, the equivalent of a data table, which does not provide an equivalent experience to the advantages of data visualizations. It decreases independence and professional opportunities, increases stress, decreases quality of life, and puts vulnerable people at risk when crucial public health information is disseminated in graphical-only form, such as in the current COVID-19 pandemic. The long range goal of this Phase I project is to create technologies that permit authors and developers of web sites to effortlessly publish charts, diagrams, and infographics that are fully usable by all people, in particular people who are blind, low-vision, or have cognitive disabilities. In this Phase I SBIR project, we will assess the feasibility of creating interactive contextual automatic descriptions that enable the reader to construct an accurate working mental model of the data with minimal effort and time, to perform tasks and make decisions. Fizz Studio has created a software package, Fizz Charts, that generates accessible keyboard-browsable charts for use on any website. We seek to enhance this with Fizz Reader, a novel interactive interface that uses natural language generation (NLG) to enable the user to query the chart for quick answers about each data point, its relationship to other data points and to the chart statistics, and to high-level or detailed trends and patterns in the data. The effect is of one person explaining the chart to another over the phone, and providing relevant and rapid answers to help the listener understand as much of the data as they wish for a core set of 7 common chart types: bar; line; pie; histogram; scatterplot; heatmap; and flowchart. Aim 1: Develop effective interactive NLG model and engine module To concisely communicate relevant details to the user, we will design a comprehensive set of tasks for all supported chart types, and a set of NLG templates for each chart component (e.g. data point, axis, title). We will use these NLG templates to develop a software module which composes colloquial utterances from an internal statistical data model we build from the data extracted from the chart. Each set of options will represent the affordances optimal for the chart type (e.g. comparisons for bar charts, changes over time for line charts). This module will have a client-server API architecture, to make it adaptable to multiple user interface modalities, including the screen reader inter...