Middleton Jonathan, Hakulinen Jaakko, Tiitinen Katariina, Hella Juho, Keskinen Tuuli, Huuskonen Pertti, Culver Jeffrey, Linna Juhani, Turunen Markku, Ziat Mounia, Raisamo Roope
Department of Fine and Performing Arts, Eastern Washington University, Cheney, WA, United States.
Tampere Unit for Computer-Human Interaction (TAUCHI), Tampere University, Tampere, Finland.
Front Big Data. 2023 Aug 10;6:1206081. doi: 10.3389/fdata.2023.1206081. eCollection 2023.
The process of transforming data into sounds for auditory display provides unique user experiences and new perspectives for analyzing and interpreting data. A research study for data transformation to sounds based on musical elements, called data-to-music sonification, reveals how musical characteristics can serve analytical purposes with enhanced user engagement. An existing user engagement scale has been applied to measure engagement levels in three conditions within melodic, rhythmic, and chordal contexts. This article reports findings from a user engagement study with musical traits and states the benefits and challenges of using musical characteristics in sonifications. The results can guide the design of future sonifications of multivariable data.
将数据转换为声音以进行听觉显示的过程为分析和解释数据提供了独特的用户体验和新视角。一项基于音乐元素的数据转换为声音的研究，即所谓的数据到音乐的声化，揭示了音乐特征如何以增强用户参与度的方式服务于分析目的。现有的用户参与度量表已被用于测量旋律、节奏和和弦背景下三种条件下的参与度水平。本文报告了一项关于音乐特征的用户参与度研究的结果，并阐述了在声化中使用音乐特征的益处和挑战。这些结果可为未来多变量数据声化的设计提供指导。
