Paper: Chinese Poetry Generation with Recurrent Neural Networks

ACL ID D14-1074
Title Chinese Poetry Generation with Recurrent Neural Networks
Venue Conference on Empirical Methods in Natural Language Processing
Session Main Conference
Year 2014
Authors

We propose a model for Chinese poem generation based on recurrent neural net- works which we argue is ideally suited to capturing poetic content and form. Our generator jointly performs content selec- tion (?what to say?) and surface realization (?how to say?) by learning representations of individual characters, and their com- binations into one or more lines as well as how these mutually reinforce and con- strain each other. Poem lines are gener- ated incrementally by taking into account the entire history of what has been gen- erated so far rather than the limited hori- zon imposed by the previous line or lexical n-grams. Experimental results show that our model outperforms competitive Chi- nese poetry generation systems using both automatic and manual evaluation methods.