Blending Machine Learning and Interaction Design in Audio Explorer
Published in IEEE Computer Graphics and Applications, 2019
Abstract: The results of machine learning models can often be difficult to interpret, especially for domain experts. Audio Explorer, the winning entry of the 2018 VAST Challenge, is an interactive data exploration tool that effectively communicates machine learning results using coordinated geospatial, temporal, and auditory visualizations to promote information discovery.
Recommended citation: Scruggs, Colin and Henkel, Cameron and Stolper, Charles and Cook, Kris and Crouser, R Jordan. Blending Machine Learning and Interaction Design in Audio Explorer. IEEE Computer Graphics and Applications 41(2) :89–95 , 2019.