Extending the Hierarchical Phrase Based Model with Maximum Entropy Based BTG

Zhongjun He, Yao Meng, Hao Yu


Abstract
In the hierarchical phrase based (HPB) translation model, in addition to hierarchical phrase pairs extracted from bi-text, glue rules are used to perform serial combination of phrases. However, this basic method for combining phrases is not sufficient for phrase reordering. In this paper, we extend the HPB model with maximum entropy based bracketing transduction grammar (BTG), which provides content-dependent combination of neighboring phrases in two ways: serial or inverse. Experimental results show that the extended HPB system achieves absolute improvements of 0.9∼1.8 BLEU points over the baseline for large-scale translation tasks.
Anthology ID:
2010.amta-papers.25
Volume:
Proceedings of the 9th Conference of the Association for Machine Translation in the Americas: Research Papers
Month:
October 31-November 4
Year:
2010
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Denver, Colorado, USA
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AMTA
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Publisher:
Association for Machine Translation in the Americas
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URL:
https://aclanthology.org/2010.amta-papers.25
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PDF:
https://aclanthology.org/2010.amta-papers.25.pdf