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Augmenting a colour lexicon
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AI
DOI：10.1057/s41599-022-01045-3.png)
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摘要
En 中文
Languages differ markedly in the number of colour terms in their lexicons. The Himba, for example, a remote culture in Namibia, were reported in 2005 to have only a 5-colour term language. We re-examined their colour naming using a novel computer-based method drawing colours from across the gamut rather than only from the saturated shell of colour space that is the norm in cross-cultural colour research. Measuring confidence in communication, the Himba now have seven terms, or more properly categories, that are independent of other colour terms. Thus, we report the first augmentation of major terms, namely green and brown, to a colour lexicon in any language. A critical examination of supervised and unsupervised machine-learning approaches across the two datasets collected at different periods shows that perceptual mechanisms can, at most, only to some extent explain colour category formation and that cultural factors, such as linguistic similarity are the critical driving force for augmenting colour terms and effective colour communication.
Keyword:
LOCATING BASIC COLORS
URBAN-ENVIRONMENT
RANDOM FORESTS
UNIQUE HUES
CATEGORIES
LANGUAGE
EVOLUTION
CLASSIFICATION
APPEARANCE
PERCEPTION
期刊
IF:
3.6
论文数:
6.6K
被引数:
8.9K
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