Left-to-right tree-to-string decoding with prediction

Authors:
Yang Feng;Yang Liu;Qun Liu;Trevor Cohn
Affiliations:
The University of Sheffield, Sheffield, UK;Tsinghua University, Beijing, China;Chinese Academy of Sciences, Beijing, China;The University of Sheffield, Sheffield, UK
Venue:
EMNLP-CoNLL '12 Proceedings of the 2012 Joint Conference on Empirical Methods in Natural Language Processing and Computational Natural Language Learning
Year:
2012

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Abstract

Decoding algorithms for syntax based machine translation suffer from high computational complexity, a consequence of intersecting a language model with a context free grammar. Left-to-right decoding, which generates the target string in order, can improve decoding efficiency by simplifying the language model evaluation. This paper presents a novel left to right decoding algorithm for tree-to-string translation, using a bottom-up parsing strategy and dynamic future cost estimation for each partial translation. Our method outperforms previously published tree-to-string decoders, including a competing left-to-right method.