People's associations between colors and concepts influence their ability to interpret the meanings of colors in information visualizations. Previous work has suggested such effects are limited to concepts that have strong, specific associations with colors. However, although a concept may not be strongly associated with any colors, its mapping can be disambiguated in the context of other concepts in an encoding system. We articulate this view in semantic discriminability theory, a general framework for understanding conditions determining when people can infer meaning from perceptual features. Semantic discriminability is the degree to which observers can infer a unique mapping between visual features and concepts. Semantic discriminability theory posits that the capacity for semantic discriminability for a set of concepts is constrained by the difference between the feature-concept association distributions across the concepts in the set. We define formal properties of this theory and test its implications in two experiments. The results show that the capacity to produce semantically discriminable colors for sets of concepts was indeed constrained by the statistical distance between color-concept association distributions (Experiment 1). Moreover, people could interpret meanings of colors in bar graphs insofar as the colors were semantically discriminable, even for concepts previously considered "non-colorable" (Experiment 2). The results suggest that colors are more robust for visual communication than previously thought.

翻译：人们对于颜色与概念之间的关联会影响其从信息可视化中解读颜色含义的能力。以往研究表明，这种效应仅限于与颜色存在强烈且特定关联的概念。然而，即使某个概念与任何颜色均无强烈关联，其在编码系统中与其他概念共同出现的语境也能使其映射关系得以消解歧义。本文通过语义可辨别性理论系统阐述这一观点，该理论为理解"人们何时能通过知觉特征推断含义"的条件提供了通用框架。语义可辨别性指观察者推断视觉特征与概念间唯一映射关系的程度。该理论提出，一组概念的语义可辨别能力受该集合中特征-概念关联分布差异的制约。我们定义了该理论的形式化属性，并通过两项实验检验其推论。结果表明，为概念集合生成语义可辨别颜色的能力确实受颜色-概念关联分布之间的统计距离制约（实验1）。此外，当颜色具有语义可辨别性时，即便是先前被认为"不可着色"的概念，人们也能解读条形图中颜色的含义（实验2）。这一发现表明，颜色在视觉沟通中的鲁棒性远超先前认知。