Learning to Generate Compositional Color Descriptions

Understand

The production of color language is essential for grounded language generation.

• Color descriptions have many challenging properties: they can be vague, compositionally complex, and denotationally rich.
• We present an effective approach to generating color descriptions using recurrent neural networks and a Fourier-transformed color representation.
• Our model outperforms previous work on a conditional language modeling task over a large corpus of naturalistic color descriptions.