Hands on demonstration
Nature of colour categories
Modelling the evolution of language for modellers and non-modellers
IJCAI 2005
1
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 2005
2
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 2005
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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 2005
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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 2005
5
Tools
• A digital camera.
• Matlab (a mathematical package).
• SPSS (a statistics package).
Modelling the evolution of language for modellers and non-modellers
IJCAI 2005
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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 2005
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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 Englishspeaking 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 2005
8
The colour stimuli
urban
natural
random
Modelling the evolution of language for modellers and non-modellers
IJCAI 2005
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Extracted categories versus human categories
NATURE vs Sturges and Whitfield (1995) in CIElab
100
90
80
70
l for clusters
60
50
40
30
20
10
0
0
10
20
30
40
50
60
l for Sturges and Whitfield
70
Modelling the evolution of language for modellers and non-modellers
IJCAI 2005
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90
100
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Demonstration
• A quick demonstration of a “light” version
of an experiment.
Modelling the evolution of language for modellers and non-modellers
IJCAI 2005
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Results
l
a
NATURE vs Sturges and Whitfield (1995) in CIElab
b
NATURE vs Sturges and Whitfield (1995) in CIElab
NATURE vs Sturges and Whitfield (1995) in CIElab
100
100
80
90
80
60
80
60
40
70
40
50
40
b for clusters
a for clusters
nature
l for clusters
60
20
0
20
0
30
-20
-20
20
-40
-40
10
0
0
10
20
30
40
50
60
l for Sturges and Whitfield
70
80
90
-60
-60
100
-40
URBAN vs Sturges and Whitfield (1995) in CIElab
-20
0
20
a for Sturges and Whitfield
40
60
-60
-60
80
-40
0
20
40
b for Sturges and Whitfield
60
80
100
80
100
80
100
URBAN vs Sturges and Whitfield (1995) in CIElab
URBAN vs Sturges and Whitfield (1995) in CIElab
100
-20
100
80
90
80
60
80
60
40
70
40
50
40
b for clusters
a for clusters
urban
l for clusters
60
20
0
20
0
30
-20
-20
20
-40
-40
10
0
0
10
20
30
40
50
60
l for Sturges and Whitfield
70
80
90
-60
-60
100
-40
RANDOM vs Sturges and Whitfield (1995) in CIElab
-20
0
20
a for Sturges and Whitfield
40
60
-60
-60
80
-40
60
100
80
90
0
20
40
b for Sturges and Whitfield
RANDOM vs Sturges and Whitfield (1995) in CIElab
RANDOM vs Sturges and Whitfield (1995) in CIElab
100
-20
80
60
80
60
40
70
40
a for clusters
50
b for clusters
20
60
l for clusters
random
0
20
0
40
-20
-20
30
-40
-40
20
-60
10
0
0
10
20
30
40
50
60
l for Sturges and Whitfield
70
80
90
100
-80
-60
-60
-40
-20
0
20
a for Sturges and Whitfield
40
60
80
-80
-60
-40
Modelling the evolution of language for modellers and non-modellers
IJCAI 2005
-20
0
20
40
b for Sturges and Whitfield
60
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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 2005
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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 2005
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More on this
• Yendrikhovskij, S.N. (2001) Computing Color Categories
from Statistics of Natural Images. Journal of Imaging
Science and Technology, 45(5):409-417.
• 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.
Modelling the evolution of language for modellers and non-modellers
IJCAI 2005
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