Basic Color Terms in Estonian Sign Language

In this chapter, I determine Iron Ossetic1's basic color terms and the place of the Iron Ossetic2 system in the evolutionary sequence of the development of basic color terms. I examine the semantics and use of basic and non-basic color terms, morphological and lexical color modifiers, the main patterns used to describe color in modern Ossetic as well as connotations of color terms. I conclude by comparing the peculiarities of the Ossetic color system with the systems of some other Iranian languages. This study is based on the methodology proposed by A. Majid, F. Jordan, and M. Dunn (2011). The Ossetic material is taken from the field data collected in North Ossetia, Russia, and data from the Ossetic corpora3.

A colour-term elicitation task was used to estimate basic colour terms (BCTs) in three Spanish dialects. In Castilian (spoken in Spain) and Mexican, eleven BCTs were identified, compared to twelve in Uruguayan, including celeste “sky blue”. The six primary BCTs and three derived BCTs appeared identical in all three dialects; however, terms for “brown” and “purple” revealed dialectal variation. An Extremes naming task was used to estimate the equivalence relation between BCT counterparts in the three dialects. A Boundary delimitation task was employed to demarcate boundaries of the basic colour categories in a*b*-plane of CIELAB. The task enabled mapping the denotata of the Uruguayan-specific BCT celeste. Results are discussed in the framework of the debate of universal versus language-specific factors.

Basic perceptual abilities are universal, and most people can distinguish between millions of distinct shades. However, languages differ in the set of basic color terms (BCTs) they have. Despite numerous prior studies, the exact number of BCTs in Mandarin (Sino‐Tibetan) and Spanish (Indo‐European) is still debated. In Mandarin, this number varies from 6 to 11, whereas in Spanish there are about 11 or 12 BCTs. Additionally, differences between these two languages can be expected with regard to the differing usage of BCTs in reference to color, as well as the naming strategies used for specifying references. To clarify this, we recruited a group of Mainland Mandarin speakers and a group of Castilian Spanish speakers and assessed them in two related tasks: the list task, in which participants were asked to write down as many color names as they could recall; and the color‐naming task, in which they were asked to name color chips from the Munsell color chart that were presented randomly. Our results suggest that Mandarin has nine BCTs, while Spanish has 12 BCTs. Furthermore, we found that Mandarin speakers use more modified terms and compounds to achieve precise color reference, whereas Spanish speakers rely more on monomorphemic non‐basic terms. Finally, we observed that Mandarin speakers use some colors (gray, blue, and purple) less consistently; although, the color space is partitioned similarly by these two languages. Our results reinforce the view that there are universal constraints on color naming that are compatible with subtle cross‐cultural differences in how colors are used.

According to Berlin and Kay, there is a set of 11 universal basic color terms: White, Black, Red, Green, Yellow, Blue, Brown, Purple, Pink, Orange, and Gray. To approve this, a world survey (WCS) was begun to gather data on color categorization through the world, although, despite many languages, Persian language has not been studied so far. We report a study of color naming in Iran. A study was carried out in six major cities including: Tehran, Isfahan, Mashhad, Yazd, Rasht, and Shiraz to investigate the color naming for Persian language and also the effect of local culture. The main purpose of this study was to describe the basic color terms of Persian language and to verify Berlin and Kay's theory. In total, 200 subjects were studied from all the six cities. Our results showed that there were the same basic color terms (as Berlin and Kay's theory) in Persian language overall including:“ (White) ”,“ (Black) ”, “ (Red) ”, “ (Green) ”, “ (Yellow) ”, “ (Blue) ”, “ (Brown) ”, “ (Purple) ”, “ (Pink) ”, “ (Orange), ” and “ (Gray) ”. However, this was not valid for all the cities when they were investigated individually. There were 10 basic terms in Mashhad and Shiraz while the other cities had 11 basic terms. Also, the set of the used terms would differ by the city. © 2014 Wiley Periodicals, Inc. Col Res Appl, 40, 352–360, 2015

In Basic color terms, Brent Berlin and Paul Kay propose that ‘there exist universally for humans eleven basic perceptual color categories, which serve as the psychophysical referents of the eleven or fewer basic color terms in any language’ (1991[1969]: 104). Later research has not invalidated this claim, although their evolutionary ‘encoding sequence’ has subsequently been modified (Fig. 25). The ‘perceptual’ and ‘psychophysical’ component of their theory has been investigated in relation to ethnographic and other materials, and synthesized by Kay and Chad McDaniel (1978: esp. 617 n. 4, 620 n. 5; see further Cole and Scribner 1974: 43–50; Tornay 1978; von Wattenwyl 1979).

The role of perception, language, and preference in the developmental acquisition of basic color terms

The goal of the paper is to analyze Yakut color terms from an etymological perspective. In all, fifty-one color terms have been collected from different Yakut dictionaries and electronic sources. The terms show a heterogeneous picture: the basic color terms are of Common Turkic origin (e.g. küöx ‘blue’, qara ‘black’, kïhïl ‘red’) representing the archaic features, some basic color terms are absent in other Modern Turkic languages due to internal developments involving special Turkic or specifically Yakut suffixes (e.g. saharxay ‘yellow’, kïtarxay ‘red’). The largest group of Yakut color terms includes Mongolic loanwords, most of which are connected to the colors of animals (especially horses), which prove the Mongolic influence on the Yakut lifestyle. Another part of the paper considers the special suffixes in Yakut forming adjectives designating shades of colors, which have a mixed, i.e. Turkic and Mongolic origin. The paper tries to shed light on the way color terms may play in determining the place of the Yakut language among the Turkic languages.

The ancient Egyptian language possesses 4 basic color terms; painting uses 7 and later 9 polychrome colors. These sets correspond to Stages Ilia, V, and VII (incomplete) of the Berlin and Kay encoding sequence for language, and support the theory of 11 “basic perceptual color categories.” The categories are probably available only through progressive differentiation. The use of color in pictorial representation fits an “active” rather than a “response” model for this expansion. The separation of color use and color terminology has significant cognitive implications.

Previous research into metaphors containing colour terms has focused on the primary basic colour terms, yet examples can also be found with the secondary basic and non-basic colour terms. A case study of the colour terms purple and lavender is presented here. Situated within the Mapping Metaphor project, this analysis utilizes the unique data source, the Historical Thesaurus. In addition to thesaurus data, dictionaries were consulted to establish the etymologies of metaphorical phrases. Finally, corpus evidence was used to establish current usage of such phrases.

The main purpose of this paper is to relate recent findings regarding the evolution of basic color term systems to current research in linguistic variation and language change. More specifically it is to provide in the area of lexical semantics a demonstration of the hypothesis that all linguistic change has its roots in synchronic heterogeneity of the speech community (cf. Weinreich, Labov & Herzog (1968: 188) for a general statement of this position, also many empirical demonstrations already reported, such as those by Labov (1972) and Wang (1969) in phonology and by Bickerton (1973) in syntax). Before taking up this topic, I summarize some recent revisions in the basic color term theory itself. (Ethnographic semantics, color terms, language variation, evolutionary universals in linguistic change.)

Russian reduplicated constructions with colour terms have never previously been an object of a comprehensive corpus study. Nevertheless, they present considerable interest for a researcher because comparative ability of colour terms to be reduplicated reflects their semantic and pragmatic differences, whereas semantics and pragmatics of reduplication construction are revealed in the properties of colour terms that can fill its slots. Thus, the goal of the paper is to study semantic and pragmatic properties of Russian colour terms and Russian syntactic reduplication construction by analyzing their co-occurrence. We apply corpus methods to the data from the Russian National Corpus, RuTenTen Corpus on Sketch Engine and RuSkell corpus. We analyze absolute corpus frequencies and collocation patterns of Russian non-reduplicated colour terms, as well as their relative frequencies and collocation patterns in the construction of syntactic reduplication with a hyphen ( belyj-belyj ‘white-white, very white, spotlessly white’). Drawing on this data, we establish that absolute frequencies of non-reduplicated colour terms in Russian reflect both Anna Wierzbicka’s “universals of visual semantics”, as well as certain language and culture-specific tendencies, as evidenced by the prominence of goluboj ‘light blue’ and ryzhij ‘carroty-red’ in Russian. We also argue that the Russian reduplication construction with a hyphen ( belyj-belyj ‘white-white) is semantically and prosodically different from the construction of repetition with a comma ( belyj , belyj ‘white, white’). The former has the meaning of high degree, and thus attracts only gradable colour terms, such as belyj ‘white’, chernyj ‘black’, sinij ‘medium to dark blue’, and other basic colour terms. There are additional factors that influence colour term reduplication. Collocation patterns suggest that colour terms that co-occur with the names of culturally and cognitively salient objects, such as denotations of human appearance (face, hands, skin, eyes, hair) or landscape features (sea, sky, fire, grass) are more likely to be reduplicated. Moreover, aesthetic or emotional evaluation of such objects (‘blue-blue eyes’, ‘green-green grass’) is also a factor that is conducive to their occurrence in the construction of reduplication. Our findings establish the importance of corpus methods in the study of colour terms and reduplication, demonstrate that the use and interpretation of lexical and syntactic items hinges both on semantic and pragmatic factors, and add to the understanding of semantics and pragmatics of Russian colour terms and reduplication construction.

We report a field study of the colour terms of the Bantu language Ndebele. The main purposes of the study were to describe the Ndebele colour term inventory, and to determine which colour terms were basic in order to test Berlin & Kay's theory of colour universals. A sample of school children and a sample of adults from Matabeleland performed a list task ('tell me as many colour terms as you know') in order to identify Ndebele colour terms and to establish the relative salience of the terms. The adults also took part in a low resolution colour mapping task which provided a preliminary estimate of the range of referents of each term. Our results show that Ndebele has four definite basic terms: terms for white, black, red and green with blue (grue). In addition, the children had a basic term for yellow, and as this term was taught formally in school, it may eventually become basic for the majority of the population. Both sets of basic terms are consistent with Berlin & Kay's theory.

The aim of this paper is to present colour terms used by scientists in the field of astrophysics. We take into consideration both basic and non-basic colour terms – as understood by Berlin and Kay (1969). The research material, compiled in a corpus with AntConc, consists of abstracts published in selected astrophysical journals. The corpus size is 2,319,787 words. The most frequent basic colour term found in the abstracts is black (612 occurrences), followed by white (167), red (160), blue (111) and green (98). It appears that the frequent word combinations in which these and other colour words are used happen to be specialized terms whose formation involved metaphorical or metonymic processes, e.g. red giant, white dwarf, red planet, red noise and blue straggler.

The object of this study is an analysis of the lexical means employed in the naming of colors, focusing especially on the form, function, and meaning of these color terms in the German language. Fashion magazines were used as source material for the research. The choice of magazines was determined by the high frequency of color terms. The basic color terms proved to be the most frequently exploited lexical means to describe one color, although it had been hypothetically assumed that there would be a quantitative preponderance of word formation structures, syntactic groups, and transferred designations. The decisive factor in the high frequency of basic color terms is their ability to function in a variety of ways. Not only as they describe a particular color of a garment, they are also increasingly used to express prediction and color trends, which is achieved by nominalization. But the goal has not always been a denotative correctness – rather the conveying of positive connotation.

Colour is derived from three physical properties: incident light, object reflectance and sensor sensitivities. Incident light varies under natural conditions; hence, recovering scene illuminant is an important issue in computational colour. One way to deal with this problem under calibrated conditions is by following three steps, 1) building a narrow-band sensor basis to accomplish the diagonal model, 2) building a feasible set of illuminants, and 3) defining criteria to select the best illuminant. In this work we focus on colour constancy for natural images by introducing perceptual criteria in the first and third stages.To deal with the illuminant selection step, we hypothesize that basic colour categories can be used as anchor categories to recover the best illuminant. These colour names are related to how the human visual system has evolved to encode relevant natural colour statistics. Therefore the recovered image provides the best representation of the scene labelled with the basic colour terms. We demonstrate with several experiments how this selection criterion achieves current state-of-art results in computational colour constancy. In addition to this result, we psychophysically prove that usual angular error used in colour constancy does not correlate with human preferences, and we propose a new perceptual colour constancy evaluation.The implementation of this selection criterion strongly relies on the use of a diagonal model for illuminant change. Then, the second contribution focuses on building an appropriate narrow-band sensor basis to represent natural images. We propose to use the spectral sharpening technique to compute a unique narrow-band basis optimized to represent a large set of natural reflectances under natural illuminants and given in the basis of human cones. The proposed sensors allow predicting unique hues and the World colour Survey data independently of the illuminant by using a compact singularity function. Additionally, we studied different families of sharp sensors to minimize different perceptual measures. This study brought us to extend the spherical sampling procedure from 3D to 6D.Several research lines remain still open, such as, measuring the effects of using the computed sharp sensors on the category hypothesis; or inserting spatial contextual information to improve category hypothesis. Finally, to explore how individual sensors can be adjusted to the colours in a scene.