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Comparing Distributions of Color Words: Pitfalls and Metric Choices
St. Andrews University, UK.ORCID iD: 0000-0001-6322-7542
Stockholm University.
KTH, School of Computer Science and Communication (CSC), Computer Vision and Active Perception, CVAP.
2014 (English)In: PLoS ONE, ISSN 1932-6203, Vol. 9, no 2Article in journal (Refereed) Published
Abstract [en]

Computational methods have started playing a significant role in semantic analysis. One particularly accessible area for developing good computational methods for linguistic semantics is in color naming, where perceptual dissimilarity measures provide a geometric setting for the analyses. This setting has been studied first by Berlin & Kay in 1969, and then later on by a large data collection effort: the World Color Survey (WCS). From the WCS, a dataset on color naming by 2 616 speakers of 110 different languages is made available for further research. In the analysis of color naming from WCS, however, the choice of analysis method is an important factor of the analysis. We demonstrate concrete problems with the choice of metrics made in recent analyses of WCS data, and offer approaches for dealing with the problems we can identify. Picking a metric for the space of color naming distributions that ignores perceptual distances between colors assumes a decorrelated system, where strong spatial correlations in fact exist. We can demonstrate that the corresponding issues are significantly improved when using Earth Mover's Distance, or Quadratic Χ-square Distance, and we can approximate these solutions with a kernel-based analysis method.

Place, publisher, year, edition, pages
Public Library of Science , 2014. Vol. 9, no 2
National Category
General Language Studies and Linguistics
URN: urn:nbn:se:kth:diva-150373DOI: 10.1371/journal.pone.0089184ISI: 000332385900033ScopusID: 2-s2.0-84896098405OAI: diva2:742565
EU, FP7, Seventh Framework ProgrammeKnut and Alice Wallenberg Foundation

QC 20140908

Available from: 2014-09-02 Created: 2014-09-02 Last updated: 2014-12-16Bibliographically approved

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