Efficient compression in color naming and its evolution

Significance Semantic typology documents and explains how languages vary in their structuring of meaning. Information theory provides a formal model of communication that includes a precise definition of efficient compression. We show that color-naming systems across languages achieve near-optimal compression and that this principle explains much of the variation across languages. These findings suggest a possible process for color category evolution that synthesizes continuous and discrete aspects of previous accounts. The generality of this principle suggests that it may also apply to other semantic domains. We derive a principled information-theoretic account of cross-language semantic variation. Specifically, we argue that languages efficiently compress ideas into words by optimizing the information bottleneck (IB) trade-off between the complexity and accuracy of the lexicon. We test this proposal in the domain of color naming and show that (i) color-naming systems across languages achieve near-optimal compression; (ii) small changes in a single trade-off parameter account to a large extent for observed cross-language variation; (iii) efficient IB color-naming systems exhibit soft rather than hard category boundaries and often leave large regions of color space inconsistently named, both of which phenomena are found empirically; and (iv) these IB systems evolve through a sequence of structural phase transitions, in a single process that captures key ideas associated with different accounts of color category evolution. These results suggest that a drive for information-theoretic efficiency may shape color-naming systems across languages. This principle is not specific to color, and so it may also apply to cross-language variation in other semantic domains.

• Publication year

  2018

• Venue

  Proceedings of the National Academy of Sciences of the United States of America

• Publication date

  2018-07-18

• Fields of study

  Medicine, Linguistics, Computer Science

• Identifiers
  DOI 10.1073/pnas.1800521115PMID 30021851PMCID PMC6077716
• External record

  Open on Semantic Scholar

• Source metadata

  Semantic Scholar, PubMed

• No claims are published for this paper.

• No concepts are published for this paper.

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