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颜色命名在不同语言中反映了颜色的使用。

Color naming across languages reflects color use.

机构信息

Department of Brain and Cognitive Sciences, Massachusetts Institute of Technology, Cambridge, MA 02139;

Department of Brain and Cognitive Sciences, Massachusetts Institute of Technology, Cambridge, MA 02139.

出版信息

Proc Natl Acad Sci U S A. 2017 Oct 3;114(40):10785-10790. doi: 10.1073/pnas.1619666114. Epub 2017 Sep 18.

Abstract

What determines how languages categorize colors? We analyzed results of the World Color Survey (WCS) of 110 languages to show that despite gross differences across languages, communication of chromatic chips is always better for warm colors (yellows/reds) than cool colors (blues/greens). We present an analysis of color statistics in a large databank of natural images curated by human observers for salient objects and show that objects tend to have warm rather than cool colors. These results suggest that the cross-linguistic similarity in color-naming efficiency reflects colors of universal usefulness and provide an account of a principle (color use) that governs how color categories come about. We show that potential methodological issues with the WCS do not corrupt information-theoretic analyses, by collecting original data using two extreme versions of the color-naming task, in three groups: the Tsimane', a remote Amazonian hunter-gatherer isolate; Bolivian-Spanish speakers; and English speakers. These data also enabled us to test another prediction of the color-usefulness hypothesis: that differences in color categorization between languages are caused by differences in overall usefulness of color to a culture. In support, we found that color naming among Tsimane' had relatively low communicative efficiency, and the Tsimane' were less likely to use color terms when describing familiar objects. Color-naming among Tsimane' was boosted when naming artificially colored objects compared with natural objects, suggesting that industrialization promotes color usefulness.

摘要

是什么决定了语言如何对颜色进行分类?我们分析了 110 种语言的世界颜色调查(WCS)的结果,表明尽管语言之间存在明显差异,但暖色系(黄色/红色)的颜色表达总是比冷色系(蓝色/绿色)更为准确。我们分析了由人类观察者为显著物体整理的大型自然图像数据库中的颜色统计数据,结果表明物体往往具有暖色调而不是冷色调。这些结果表明,跨语言颜色命名效率的相似性反映了颜色的普遍实用性,并为颜色分类的原则(颜色使用)提供了一个解释。我们通过在三个组中使用颜色命名任务的两个极端版本收集原始数据,表明 WCS 的潜在方法问题不会破坏信息论分析:一个是偏远的亚马逊狩猎采集者孤立群体 Tsimane';另一个是玻利维亚西班牙语使用者;还有一个是英语使用者。这些数据还使我们能够测试颜色实用性假设的另一个预测:语言之间的颜色分类差异是由颜色对文化整体实用性的差异引起的。支持该假设,我们发现 Tsimane'的颜色命名相对较低的交流效率,并且当描述熟悉的物体时,Tsimane'使用颜色术语的可能性较小。与描述自然物体相比,命名人工着色的物体时,Tsimane'的颜色命名效率提高了,这表明工业化促进了颜色的实用性。

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