Chinese Poetry Generation with Planning based Neural Network

Understand

Chinese poetry generation is a very challenging task in natural language processing.

• In this paper, we propose a novel two-stage poetry generating method which first plans the sub-topics of the poem according to the user's writing intent, and then generates each line of the poem sequentially, using a modified recurrent neural network encoder-decoder framework.
• The proposed planning-based method can ensure that the generated poem is coherent and semantically consistent with the user's intent.
• A comprehensive evaluation with human judgments demonstrates that our proposed approach outperforms the state-of-the-art poetry generating methods and the poem quality is somehow comparable to human poets.