Generating Chinese Classical Poems with Statistical Machine Translation Models

32Citations
Citations of this article
38Readers
Mendeley users who have this article in their library.

Abstract

This paper describes a statistical approach to generation of Chinese classical poetry and proposes a novel method to automatically evaluate poems. The system accepts a set of keywords representing the writing intents from a writer and generates sentences one by one to form a completed poem. A statistical machine translation (SMT) system is applied to generate new sentences, given the sentences generated previously. For each line of sentence a specific model specially trained for that line is used, as opposed to using a single model for all sentences. To enhance the coherence of sentences on every line, a coherence model using mutual information is applied to select candidates with better consistency with previous sentences. In addition, we demonstrate the effectiveness of the BLEU metric for evaluation with a novel method of generating diverse references.

Cite

CITATION STYLE

APA

He, J., Zhou, M., & Jiang, L. (2012). Generating Chinese Classical Poems with Statistical Machine Translation Models. In Proceedings of the 26th AAAI Conference on Artificial Intelligence, AAAI 2012 (pp. 1650–1656). AAAI Press. https://doi.org/10.1609/aaai.v26i1.8344

Register to see more suggestions

Mendeley helps you to discover research relevant for your work.

Already have an account?

Save time finding and organizing research with Mendeley

Sign up for free