Character Sequence Models for ColorfulWords

Kazuya Kawakami, Chris Dyer, Bryan R. Routledge, Noah A. Smith

We present a neural network architecture to predict a point in color space from the sequence of characters in the color's name. Using large scale color--name pairs obtained from an online color design forum, we evaluate our model on a "color Turing test" and find that, given a name, the colors predicted by our model are preferred by annotators to color names created by humans. Our datasets and demo system are available online at colorlab.us.

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