An online color naming experiment in Russian using Munsell color samples

Russian color naming was explored in a web-based experiment. The purpose was 3-fold: to examine (1) CIELAB coordinates of centroids for 12 Russian basic color terms (BCTs), including 2 Russian terms for “blue”, sinij “dark blue”, and goluboj “light blue”, and compare these with coordinates for the 11 English BCTs obtained in earlier studies; (2) frequent nonBCTs; and (3) gender differences in color naming. Native Russian speakers participated in the experiment using an unconstrained color-naming method. Each participant named 20 colors, selected from 600 colors densely sampling the Munsell Color Solid. Color names and response times of typing onset were registered. Several deviations between centroids of the Russian and English BCTs were found. The 2 “Russian blues”, as expected, divided the BLUE area along the lightness dimension; their centroids deviated from a centroid of English blue. Further minor departures were found between centroids of Russian and English counterparts of “brown” and “red”. The Russian color inventory confirmed the linguistic refinement of the PURPLE area, with high frequencies of nonBCTs. In addition, Russian speakers revealed elaborated naming strategies and use of a rich inventory of nonBCTs. Elicitation frequencies of the 12 BCTs were comparable for both genders; however, linguistic segmentation of color space, employing a synthetic observer, revealed gender differences in naming colors, with more refined naming of the “warm” colors from females. We conclude that, along with universal perceptual factors, that govern categorical partition of color space, Russian speakers’ color naming reflects language-specific factors, supporting the weak relativity hypothesis

Gender Differences in Russian Colour Naming

In the present study we explored Russian colour naming in a web-based psycholinguistic experiment (http://www.colournaming.com). Colour singletons representing the Munsell Color Solid (N=600 in total) were presented on a computer monitor and named using an unconstrained colour-naming method. Respondents were Russian speakers (N=713). For gender-split equal-size samples (NF=333, NM=333) we estimated and compared (i) location of centroids of 12 Russian basic colour terms (BCTs); (ii) the number of words in colour descriptors; (iii) occurrences of BCTs most frequent non-BCTs. We found a close correspondence between females’ and males’ BCT centroids. Among individual BCTs, the highest inter-gender agreement was for seryj ‘grey’ and goluboj ‘light blue’, while the lowest was for sinij ‘dark blue’ and krasnyj ‘red’. Females revealed a significantly richer repertory of distinct colour descriptors, with great variety of monolexemic non-BCTs and “fancy” colour names; in comparison, males offered relatively more BCTs or their compounds. Along with these measures, we gauged denotata of most frequent CTs, reflected by linguistic segmentation of colour space, by employing a synthetic observer trained by gender-specific responses. This psycholinguistic representation revealed females’ more refined linguistic segmentation, compared to males, with higher linguistic density predominantly along the redgreen axis of colour space

An online colour naming experiment in Russian using Munsell colour samples

Russian colour naming was explored in a web-based psycholinguistic experiment. The purpose was threefold: to examine (i) CIELAB coordinates of centroids for 12 Russian basic colour terms (BCTs), including two Russian terms for ‘blue’, sinij ‘dark blue’ and goluboj ‘light blue’, and compare these with coordinates for the 11 English BCTs obtained in earlier studies; (ii) frequent non-BCTs and (iii) gender differences in colour naming. Native Russian speakers participated in the experiment using an unconstrained colour-naming method. Each participant named 20 colours, selected from 600 colours densely sampling the Munsell Color Solid. Colour names and response times of typing onset were registered. Several deviations between centroids of the Russian and English BCTs were found. The two Russian ‘blues’, as expected, divided the BLUE area along the lightness dimension; their centroids deviated from a centroid of English blue. Further minor departures were found between centroids of Russian and English counterparts of ‘brown’ and ‘red’. The Russian colour inventory confirmed the linguistic refinement of the PURPLE area, with high frequencies of non-BCTs. In addition, Russian speakers revealed elaborated naming strategies and use of a rich inventory of non-BCTs. Elicitation frequencies of the 12 BCTs were comparable for both genders; however, linguistic segmentation of colour space, employing a synthetic observer, revealed gender differences in naming colours, with more refined naming of the “warm” colours from females. We conclude that, along with universal perceptual factors, that govern categorical partition of colour space, Russian speakers’ colour naming reflects language-specific factors, supporting the weak relativity hypothesis

“Edible” colour names: Cross-cultural comparison of Russian and English

We explored differences between Russian and English languages in incidences of colour names related to food and edible substances. Colour names were elicited in a web-based psycholinguistic experiment with native speakers of Russian (N=713; 333 males) and English (N=272, 113 males). Colour samples (N=600) were approximately uniformly distributed in the Munsell Color Solid. An unconstrained colour-naming method was employed. A refined dataset comprised 14,260 responses from Russian and 5,428 responses from English speakers. For each language dataset, we report the inventory of “edible” colour names, their frequency, and derivational productivity. We conclude that, along with the natural environment, the inventory of “edible” terms is language-specific and manifests culture-specific culinary worldview

Gender Differences in Russian Colour Naming

In the present study we explored Russian colour naming in a web-based psycholinguistic experiment (http://www.colournaming.com). Colour singletons representing the Munsell Color Solid (N=600 in total) were presented on a computer monitor and named using an unconstrained colour-naming method. Respondents were Russian speakers (N=713). For gender-split equal-size samples (NF=333, NM=333) we estimated and compared (i) location of centroids of 12 Russian basic colour terms (BCTs); (ii) the number of words in colour descriptors; (iii) occurrences of BCTs most frequent non-BCTs. We found a close correspondence between females’ and males’ BCT centroids. Among individual BCTs, the highest inter-gender agreement was for seryj ‘grey’ and goluboj ‘light blue’, while the lowest was for sinij ‘dark blue’ and krasnyj ‘red’. Females revealed a significantly richer repertory of distinct colour descriptors, with great variety of monolexemic non-BCTs and “fancy” colour names; in comparison, males offered relatively more BCTs or their compounds. Along with these measures, we gauged denotata of most frequent CTs, reflected by linguistic segmentation of colour space, by employing a synthetic observer trained by gender-specific responses. This psycholinguistic representation revealed females’ more refined linguistic segmentation, compared to males, with higher linguistic density predominantly along the redgreen axis of colour space

Objects as culture-specific referents of color terms in Russian

The present study is an extension of our analysis of Russian basic color terms (BCTs) elicited in a web-based psycholinguistic experiment. Color samples (N = 600) were approximately uniformly distributed in the Munsell color solid. An unconstrained color-naming method was employed. Native Russian speakers (N = 713; 333 males) participated in the study. Among 1422 elicited unique color words, 698 terms (49%) were derived from object names. Here we explore object-derived non-BCTs, focusing on broad classes of names referred to objects, categories within these, and the inventory of color terms, as well as their frequency, patterns of derivation, and derivational productivity. Six classes of object referents were identified: flora, fauna, inanimate nature, food and beverages, man-made objects, body and bodily products. In detail, 20 most frequent object-derived terms are reported. These are accompanied by analysis of gender differences and representation of the terms' denotata on the Munsell Mercator projection. In addition, Russian object-derived color terms are related to those in English; discussed are differences between the 2 languages in the color term classes, inventories and incidences. We conclude that Russian object-derived color terms follow the generic metonymy pattern, that is, signifying color of objects in the speakers' natural environment. The inventory is also language-specific, reflecting social practices, preferences and views entrenched in the traditional Russian culture. Furthermore, recent extensive development of the inventory signals 2 novel phenomena: marked globalization influence, surfacing as abundant transliteration of English referent loanwords, and noticeable sociolectal diversification that manifests itself by novel evocative color terms, particularly in marketing and advertisement

Gender differences in colour naming

Gender differences in colour naming were explored using a web-based experiment in English. Each participant named twenty colours selected from 600 Munsell samples, presented one at a time against a neutral background. Colour names and typing onset response times were registered. For the eleven basic colour terms, elicitation frequency was comparable for both genders. Females demonstrated more elaborated colour vocabulary, with more descriptors in general and more non-basic monolexemic terms; they also named colours faster than males. The two genders differ in the repertoire of frequent colour terms: a Bayesian synthetic observer revealed that women segment colour space linguistically more densely in the “warm” area whereas men do so in the “cool” area. Current “nurture” and “nature” explanations of why females excel in colour naming behaviour are considered

Colour Communication Within Different Languages

For computational methods aiming to reproduce colour names that are meaningful to speakers of different languages, the mapping between perceptual and linguistic aspects of colour is a problem of central information processing. This thesis advances the field of computational colour communication within different languages in five main directions. First, we show that web-based experimental methodologies offer considerable advantages in obtaining a large number of colour naming responses in British and American English, Greek, Russian, Thai and Turkish. We continue with the application of machine learning methods to discover criteria in linguistic, behavioural and geometric features of colour names that distinguish classes of colours. We show that primary colour terms do not form a coherent class, whilst achromatic and basic classes do. We then propose and evaluate a computational model trained by human responses in the online experiment to automate the assignment of colour names in different languages across the full three-dimensional colour gamut. Fourth, we determine for the first time the location of colour names within a physiologically-based cone excitation space through an unconstrained colour naming experiment using a calibrated monitor under controlled viewing conditions. We show a good correspondence between online and offline datasets; and confirm the validity of both experimental methodologies for estimating colour naming functions in laboratory and real-world monitor settings. Finally, we present a novel information theoretic measure, called dispensability, for colour categories that predicts a gradual scale of basicness across languages from both web- and laboratory- based unconstrained colour naming datasets. As a result, this thesis contributes experimental and computational methodologies towards the development of multilingual colour communication schemes

Augmenting basic colour terms in english

In an unconstrained colour naming experiment conducted over the web, 330 participants named 600 colour samples in English. The 30 most frequent monolexemic colour terms were analyzed with regards to frequency, consensus among genders, response times, consistency of use, denotative volume in the Munsell and OSA colour spaces and inter-experimental agreement. Each of these measures served for ranking colour term salience; rankings were then combined to give a composite index of basicness. The results support the extension of English inventory from the 11 basic colour terms of Berlin and Kay to 13 terms by the addition of lilac and turquoise

Intergenerational differences in Russian color naming in the globalized era: linguistic analysis

The present study is an apparent-time analysis of color terms in Russian native speakers (N = 1927), whose age varied between 16 and 98 years. Stratified sampling was employed with the following age groups: 16–19, 20–29, and so on, with the oldest group of 70 years and over. Color names were elicited in a web-based psycholinguistic experiment (http://colournaming.com). Participants labeled color samples (N = 606) using an unconstrained color-naming method. Color vocabulary of each age group was estimated using multiple linguistic measures: diversity index; frequency of occurrences of 12 Russian basic color terms (BCTs) and of most frequent non-BCTs; color-naming pattern. Our findings show intergenerational differences in Russian color-term vocabulary, color-naming patterns, and object referents. The CT diversity (measured by the Margalef index) progressively increments with speakers’ juniority; the lexical refinement is manifested by the increasing variety of BCT modifiers and growing use of non-BCTs, both traditional and novel. Furthermore, the most frequent Russian non-BCTs sirenevyj “lilac”, salatovyj “lettuce‐colored”, and birûzovyj “turquoise” appear to be the emerging BCTs. The greatest diversity and richness of CT inventory is observed in Russian speakers aged 20–59 years, i.e., those who constitute the active workforce and are enthusiastic consumers. In comparison, speakers of 60 and over manifest less diverse color inventory and greater prevalence of (modified) BCTs. The two youngest groups (16–29 years) are linguistic innovators: their color vocabulary includes abundant recent loanwords, predominantly from English and, not infrequently, CTs as nouns rather than adjectives. Moreover, Generation Z (16–19 years) tend to offer highly specific or idiosyncratic color descriptors that serve expressive rather than informative function. The apprehended dynamics of color naming in apparent time reflects intergenerational differences as such, but even more so dramatic changes of sociocultural reality in the post-Soviet era, whereby Russian speakers, in particular under 60 years, were/are greatly impacted by globalization of trade: new market product arrivals resulted in adoption of novel and elaboration of traditional CTs for efficient communication about perceived colo