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Blending Machine Learning and Interaction Design in Audio Explorer
IEEE Computer Graphics and Applications ( IF 1.7 ) Pub Date : 2019-01-01 , DOI: 10.1109/mcg.2019.2950185
Colin Scruggs 1 , Cameron Henkel 2 , Charles Stolper 3 , Kris Cook 4 , R. Jordan Crouser 5
Affiliation  

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.

中文翻译:

在音频资源管理器中混合机器学习和交互设计

机器学习模型的结果通常难以解释,尤其是对领域专家而言。Audio Explorer 是 2018 VAST Challenge 的获奖作品,是一种交互式数据探索工具,可有效传达机器学习结果,使用协调的地理空间、时间和听觉可视化来促进信息发现。
更新日期:2019-01-01
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