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IJCNLP
2005
Springer

Phrase-Based Statistical Machine Translation: A Level of Detail Approach

8 years 10 months ago
Phrase-Based Statistical Machine Translation: A Level of Detail Approach
The merit of phrase-based statistical machine translation is often reduced by the complexity to construct it. In this paper, we address some issues in phrase-based statistical machine translation, namely: the size of the phrase translation table, the use of underlying translation model probability and the length of the phrase unit. We present Level-Of-Detail (LOD) approach, an agglomerative approach for learning phrase-level alignment. Our experiments show that LOD approach significantly improves the performance of the word-based approach. LOD demonstrates a clear advantage that the phrase translation table grows only sub-linearly over the maximum phrase length, while having a performance comparable to those of other phrase-based approaches.
Hendra Setiawan, Haizhou Li, Min Zhang, Beng Chin
Added 27 Jun 2010
Updated 27 Jun 2010
Type Conference
Year 2005
Where IJCNLP
Authors Hendra Setiawan, Haizhou Li, Min Zhang, Beng Chin Ooi
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