April 7, 2021
Journal Article

Blending Machine Learning and Interaction Design in Audio Explorer

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.

Published: April 7, 2021

Citation

Scruggs C., C. Henkel, C. Stolper, K.A. Cook, and J. Crouser. 2021. Blending Machine Learning and Interaction Design in Audio Explorer. IEEE Computer Graphics and Applications 41, no. 2:89 - 95. PNNL-SA-141120. doi:10.1109/MCG.2019.2950185