Paper: Improving Decoding Generalization for Tree-to-String Translation

ACL ID P11-2073
Title Improving Decoding Generalization for Tree-to-String Translation
Venue Annual Meeting of the Association of Computational Linguistics
Session Main Conference
Year 2011
Authors

To address the parse error issue for tree-to- string translation, this paper proposes a similarity-based decoding generation (SDG) solution by reconstructing similar source parse trees for decoding at the decoding time instead of taking multiple source parse trees as input for decoding. Experiments on Chinese-English translation demonstrated that our approach can achieve a significant improvement over the standard method, and has little impact on decoding speed in practice. Our approach is very easy to im- plement, and can be applied to other para- digms such as tree-to-tree models.