Modelling the evolution of language for modellers and non-modellers IJCAI Hands on demonstration Nature of colour categories

Modelling the evolution of language for modellers and non-modellers IJCAI What do we know? There is evidence that colour categories are universal. –All cultures have colour categories that are similar to RED, GREEN, BLUE, YELLOW, and so on. Three possible explanations –Genetically determined. –Culturally (and linguistically) determined. –Ecologically determined. In this demonstration we will take a closer look at the last explanation.

Modelling the evolution of language for modellers and non-modellers IJCAI Why do we want to know? Language is about communicating concepts, we want to now how concepts are acquired. As a case study we take colour categories. “…this may at first appear to be a comparatively trivial example of some minor aspect of language, but the implications for other aspects of language evolution are truly staggering.” (Deacon, 1997)

Modelling the evolution of language for modellers and non-modellers IJCAI Hypothesis and assumptions Research question –Does our ecology contain enough structure to specify colour categories the way they are? Hypothesis –Human ecologies contain enough structure to specify human colour categories. Assumptions –No semantics, culture or language is involved. –Colour categories have a prototypical nature. –Colour categories are extracted from chromatic stimuli in an unsupervised manner. –We choose a representation for our colours that is psychophysically plausible.

Modelling the evolution of language for modellers and non-modellers IJCAI What do we expect? If the claim is true: –Categories extracted from the real-world data should resemble human colour categories. –Categories extracted from the random data should not resemble human colour categories. –Categories extracted from real-world data should not resemble the ones from random data.

Modelling the evolution of language for modellers and non-modellers IJCAI Tools A digital camera. Matlab (a mathematical package). SPSS (a statistics package).

Modelling the evolution of language for modellers and non-modellers IJCAI Methodology Gather image collection from natural and urban environments. Draw 25,000 random pixels from each collection. Construct random set as control.

Modelling the evolution of language for modellers and non-modellers IJCAI Methodology Extract categories from the data –This we do by unsupervised clustering (k-means clustering) as this does not violate our assumptions. Compare the categories to human colour categories –Sturges & Whitfield (1995) have recorded the 11 basic colour categories of American English- speaking informants. –Quantitative and objective comparing happens through matching couples and calculating the correlation between clusters and human colour categories. We use Kendall’s Tau correlation for ranked and matched observations.

Modelling the evolution of language for modellers and non-modellers IJCAI The colour stimuli natural urban random

Modelling the evolution of language for modellers and non-modellers IJCAI Extracted categories versus human categories

Modelling the evolution of language for modellers and non-modellers IJCAI Demonstration A quick demonstration of a “light” version of an experiment.

Modelling the evolution of language for modellers and non-modellers IJCAI Results lab nature urban random

Modelling the evolution of language for modellers and non-modellers IJCAI Correlation Correlations between lightness, colour axes, chroma and hue. Correlation between random distribution and human categories is not lower than for a real-world distribution For two different colour appearance models (CIE L*a*b* and CIE L*u*v*).

Modelling the evolution of language for modellers and non-modellers IJCAI Conclusion We could not refute the null hypothesis. –Clustering random colours produces categories that correlate equally well. Human ecologies have only a marginal influence on colour categories. What then does have an influence? –Psychophysical properties of colour perception. –The nature of categories (maximally distinct). –And possible culture and language (but no proof in this experiment).

Modelling the evolution of language for modellers and non-modellers IJCAI More on this Yendrikhovskij, S.N. (2001) Computing Color Categories from Statistics of Natural Images. Journal of Imaging Science and Technology, 45(5): Belpaeme, T. & Bleys, J. (2004) Does structure in the environment influence our conceptualization? Proceedings of the Conference on the Evolution of Language 2004, Leipzig, Germany. Steels, L. & Belpaeme, T. (2005) Coordinating perceptually grounded categories through language: A case study for colour. Behavioral and Brain Sciences, 28(4). In press.