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COLING
2010

Learning Phrase Boundaries for Hierarchical Phrase-based Translation

10 years 1 months ago
Learning Phrase Boundaries for Hierarchical Phrase-based Translation
Hierarchical phrase-based models provide a powerful mechanism to capture non-local phrase reorderings for statistical machine translation (SMT). However, many phrase reorderings are arbitrary because the models are weak on determining phrase boundaries for patternmatching. This paper presents a novel approach to learn phrase boundaries directly from word-aligned corpus without using any syntactical information. We use phrase boundaries, which indicate the beginning/ending of phrase reordering, as soft constraints for decoding. Experimental results and analysis show that the approach yields significant improvements over the baseline on large-scale Chineseto-English translation.
Zhongjun He, Yao Meng, Hao Yu
Added 13 May 2011
Updated 13 May 2011
Type Journal
Year 2010
Where COLING
Authors Zhongjun He, Yao Meng, Hao Yu
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