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        <title>Statistical Syntax-Directed Translation with Extended Domain of Locality</title>
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    <abstract>In syntax-directed translation, the source-language input is first parsed into a parse-tree, which is then recursively converted into a string in the target-language. We model this conversion by an extended tree-to-string transducer that has multi-level trees on the source-side, which gives our system more expressive power and flexibility. We also define a direct probability model and use a linear-time dynamic programming algorithm to search for the best derivation. The model is then extended to the general log-linear frame-work in order to incorporate other features like n-gram language models. We devise a simple-yet-effective algorithm to generate non-duplicate k-best translations for n-gram rescoring. Preliminary experiments on English-to-Chinese translation show a significant improvement in terms of translation quality compared to a state-of-the- art phrase-based system.</abstract>
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%0 Conference Proceedings
%T Statistical Syntax-Directed Translation with Extended Domain of Locality
%A Huang, Liang
%A Knight, Kevin
%A Joshi, Aravind
%S Proceedings of the 7th Conference of the Association for Machine Translation in the Americas: Technical Papers
%D 2006
%8 aug 8 12
%I Association for Machine Translation in the Americas
%C Cambridge, Massachusetts, USA
%F huang-etal-2006-statistical
%X In syntax-directed translation, the source-language input is first parsed into a parse-tree, which is then recursively converted into a string in the target-language. We model this conversion by an extended tree-to-string transducer that has multi-level trees on the source-side, which gives our system more expressive power and flexibility. We also define a direct probability model and use a linear-time dynamic programming algorithm to search for the best derivation. The model is then extended to the general log-linear frame-work in order to incorporate other features like n-gram language models. We devise a simple-yet-effective algorithm to generate non-duplicate k-best translations for n-gram rescoring. Preliminary experiments on English-to-Chinese translation show a significant improvement in terms of translation quality compared to a state-of-the- art phrase-based system.
%U https://aclanthology.org/2006.amta-papers.8
%P 66-73

Markdown (Informal)

[Statistical Syntax-Directed Translation with Extended Domain of Locality](https://aclanthology.org/2006.amta-papers.8) (Huang et al., AMTA 2006)

• Statistical Syntax-Directed Translation with Extended Domain of Locality (Huang et al., AMTA 2006)

ACL

• Liang Huang, Kevin Knight, and Aravind Joshi. 2006. Statistical Syntax-Directed Translation with Extended Domain of Locality. In Proceedings of the 7th Conference of the Association for Machine Translation in the Americas: Technical Papers, pages 66–73, Cambridge, Massachusetts, USA. Association for Machine Translation in the Americas.