Concept: Basic Color Terms: Their Universality and Evolution
- Proceedings of the National Academy of Sciences of the United States of America
- Published almost 3 years ago
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.
Despite numerous prior studies, important questions about the Japanese color lexicon persist, particularly about the number of Japanese basic color terms and their deployment across color space. Here, 57 native Japanese speakers provided monolexemic terms for 320 chromatic and 10 achromatic Munsell color samples. Through k-means cluster analysis we revealed 16 statistically distinct Japanese chromatic categories. These included eight chromatic basic color terms (aka/red, ki/yellow, midori/green, ao/blue, pink, orange, cha/brown, and murasaki/purple) plus eight additional terms: mizu (“water”)/light blue, hada (“skin tone”)/peach, kon (“indigo”)/dark blue, matcha (“green tea”)/yellow-green, enji/maroon, oudo (“sand or mud”)/mustard, yamabuki (“globeflower”)/gold, and cream. Of these additional terms, mizu was used by 98% of informants, and emerged as a strong candidate for a 12th Japanese basic color term. Japanese and American English color-naming systems were broadly similar, except for color categories in one language (mizu, kon, teal, lavender, magenta, lime) that had no equivalent in the other. Our analysis revealed two statistically distinct Japanese motifs (or color-naming systems), which differed mainly in the extension of mizu across our color palette. Comparison of the present data with an earlier study by Uchikawa & Boynton (1987) suggests that some changes in the Japanese color lexicon have occurred over the last 30 years.
Categorization with basic color terms is an intuitive and universal aspect of color perception. Yet research on visual working memory capacity has largely assumed that only continuous estimates within color space are relevant to memory. As a result, the influence of color categories on working memory remains unknown. We propose a dual content model of color representation in which color matches to objects that are either present (perception) or absent (memory) integrate category representations along with estimates of specific values on a continuous scale (“particulars”). We develop and test the model through 4 experiments. In a first experiment pair, participants reproduce a color target, both with and without a delay, using a recently influential estimation paradigm. In a second experiment pair, we use standard methods in color perception to identify boundary and focal colors in the stimulus set. The main results are that responses drawn from working memory are significantly biased away from category boundaries and toward category centers. Importantly, the same pattern of results is present without a memory delay. The proposed dual content model parsimoniously explains these results, and it should replace prevailing single content models in studies of visual working memory. More broadly, the model and the results demonstrate how the main consequence of visual working memory maintenance is the amplification of category related biases and stimulus-specific variability that originate in perception. (PsycINFO Database Record
It has often been observed that color is a highly preferred attribute for use in distinguishing descriptions, that is, referring expressions produced with the purpose of identifying an object within a visual scene. However, most of these observations were based on visual displays containing only colors that were maximally different in hue and for which the language of experimentation possessed basic color terms. The experiments described in this paper investigate whether speakers' preference for color is reduced if the color of the target referent is similar to that of the distractors. Because colors that look similar are often also harder to distinguish linguistically, we also examine the impact of the codability of color values. As a third factor, we investigate the salience of available alternative attributes and its impact on the use of color. The results of our experiments show that, while speakers are indeed less likely to use color when the colors in a display are similar, this effect is mostly due to the difficulty in naming similar colors. Color use for color with a basic color term is affected only when the colors of target and distractors are very similar (yet still distinguishable). The salience of our alternative attribute size, manipulated by varying the difference in size between target and distractors, had no impact on the use of color.
- IEEE transactions on visualization and computer graphics
- Published almost 5 years ago
When data categories have strong color associations, it is useful to use these semantically meaningful concept-color associations in data visualizations. In this paper, we explore how linguistic information about the terms defining the data can be used to generate semantically meaningful colors. To do this effectively, we need first to establish that a term has a strong semantic color association, then discover which color or colors express it. Using co-occurrence measures of color name frequencies from Google n-grams, we define a measure for colorability that describes how strongly associated a given term is to any of a set of basic color terms. We then show how this colorability score can be used with additional semantic analysis to rank and retrieve a representative color from Google Images. Alternatively, we use symbolic relationships defined by WordNet to select identity colors for categories such as countries or brands. To create visually distinct color palettes, we use k-means clustering to create visually distinct sets, iteratively reassigning terms with multiple basic color associations as needed. This can be additionally constrained to use colors only in a predefined palette.
This article describes color naming by 51 American English-speaking informants. A free-naming task produced 122 monolexemic color terms, with which informants named the 330 Munsell samples from the World Color Survey. Cluster analysis consolidated those terms into a glossary of 20 named color categories: the 11 Basic Color Term (BCT) categories of Berlin and Kay (1969, p. 2) plus nine nonbasic chromatic categories. The glossed data revealed two color-naming motifs: the green-blue motif of the World Color Survey and a novel green-teal-blue motif, which featured peach, teal, lavender, and maroon as high-consensus terms. Women used more terms than men, and more women expressed the novel motif. Under a constrained-naming protocol, informants supplied BCTs for the color samples previously given nonbasic terms. Most of the glossed nonbasic terms from the free-naming task named low-consensus colors located at the BCT boundaries revealed by the constrained-naming task. This study provides evidence for continuing evolution of the color lexicon of American English, and provides insight into the processes governing this evolution.
Categorical perception provides a potential link between color perception and the linguistic categories that correspond to the basic color terms. We examined whether the sensory information of the second-stage chromatic mechanisms is further processed so that sensitivity for color differences yields categorical perception. In this case, sensitivity for color differences should be higher across than within category boundaries. We measured discrimination thresholds (JNDs) and color categories around an isoluminant hue circle in Derrington-Krauskopf-Lennie (DKL) color space at three levels of lightness. At isoluminant lightness, the global pattern of JNDs coarsely followed an ellipse. Deviations from the ellipse coincided with the orange-pink and the blue-green category borders, but these minima were also aligned with the second-stage cone-opponent mechanisms. No evidence for categorical perception of color was found for any other category borders. At lower lightness, categories changed substantially, but JNDs did not change accordingly. Our results point to a loose relationship between color categorization and discrimination. However, the coincidence of some boundaries with JND minima is not a general property of color categorical boundaries. Hence, our basic ability to discriminate colors cannot fully explain why we use the particular set of categories to communicate about colors. Moreover, these findings seriously challenge the idea that color naming forms the basis for the categorical perception of colors. With respect to previous studies that concentrated on the green-blue boundary, our results highlight the importance of controlling perceptual distances and examining the full set of categories when investigating category effects on color perception.