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Character Sequence Models for Colorful Words
2016
Proceedings of the 2016 Conference on Empirical Methods in Natural Language Processing
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 http: //colorlab.us.
doi:10.18653/v1/d16-1202
dblp:conf/emnlp/KawakamiDRS16
fatcat:7miapytb7rehpbpqsejphrella