用声音方向呈现数据，让视障者更准确识别具体数值
Accessible Fine-grained Data Representation via Spatial Audio
- 将数据值映射为声源方位角，实现精细数据感知
- 在判断数据正负和精确值上优于传统音高表示法
- 适合需要精确读数的视障数据分析场景
基于音高的数据听觉化虽能传达数据趋势和大致比较，但难以表现个体数据点的符号与精确值。受听觉感知研究启发，本文提出一种基于空间音频的方法，将数据值映射为水平面内声源的方向，以实现对细粒度数据的可访问表达。我们在26名参与者（含10名视障者）上开展用户研究，测试四种数据感知任务。结果表明，该方法在识别数据符号和精确值等细粒度任务中显著优于音高表示法，而在趋势识别上表现相当，但在数值比较任务中准确性较低。
原文摘要 · Abstract (English)
Pitch-based sonification of quantitative data increases the accessibility of data visualizations that are otherwise inaccessible for blind and low-vision (BLV) individuals. We argue that, although pitch representations can reveal the coarse-grained information of data, such as data trend and value comparison, they cannot effectively convey the fine-grained details like the sign and exact value of individual data points. Informed by existing sound perception research, we propose a spatial audio-based approach by representing data values as the sound direction in the azimuth plane to achieve accessible fine-grained data representation. We conducted a user study with 26 participants (including 10 BLV participants) on four data perception tasks. The results show our approach significantly outperforms pitch representation on fine-grained data perception tasks like recognizing data signs and exact values, and performs similarly on data trend identification, despite its inferior accuracy on data value comparison.
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