This is the data page for The Many Languages, Many Colors Project.
This project is divided up as follows:
- The "raw" directory contains the raw color naming data
- the "processing_scripts" directory contains the code we that takes the raw data and calculates information about color naming.
- the "model" directory contains the various models and calculations about color naming
- this directory and the "vis" directory contains the code of The Many Languages, Many Colors Project page and all the visualizations of the color naming data
Official Website is located at https://uwdata.github.io/color-naming-in-different-languages
This repository contains color data, processing, and visualization code from the project that resulted in our EuroVis paper, including:
- Color-name judgements that are collected from our 12 minute color perception survey on LabIntheWild
- Color naming probabilistic models for hue colors and full colors
- Interactive visualizations
- Color Translator Finds similar colors in the same language or across languages.
- The probabilities of terms for each hue color bin across 14 languages
- Interactive version of the above
- Maximum Probability Maps for English and Korean color names
- Comparison of translations
- The probabilities of viridis colors for some nameable terms
Note: The old paper versions of the data and visualizations are in the "2019_paper_version" subfolder, and the visualizations are available here:
- 2019 Paper Interactive visualizations
- Color Translator Finds similar colors in the same language or across languages.
- The probabilities of terms for each hue color bin across 14 languages
- Interactive version of the above
- Maximum Probability Maps for English and Korean color names
- Comparison of translations
- The probabilities of viridis colors for some nameable terms
If you use the data in published research, please cite this paper: Color Names Across Languages: Salient Colors and Term Translation in Multilingual Color Naming Models. Younghoon Kim, Kyle Thayer, Gabriella Silva Gorsky, and Jeffery Heer (2019). EuroVis.