Character Sequence Models for Colorful Words
Kazuya Kawakami, Chris Dyer, Bryan Routledge, Noah A. Smith · 2016
We present a neural network architecture to predict a point in space from the sequence of characters in the color's name. Using large scale color--name pairs obtained from an online 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 names created by humans. Our datasets and demo system are available online at this http URL.