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FINTAL
2006

Improving Phrase-Based Statistical Translation Through Combination of Word Alignments

11 years 5 months ago
Improving Phrase-Based Statistical Translation Through Combination of Word Alignments
This paper investigates the combination of word-alignments computed with the competitive linking algorithm and well-established IBM models. New training methods for phrase-based statistical translation are proposed, which have been evaluated on a popular traveling domain task, with English as target language, and Chinese, Japanese, Arabic and Italian as source languages. Experiments were performed with a highly competitive phrase-based translation system, which ranked at the top in the 2005 IWSLT evaluation campaign. By applying the proposed techniques, even under very different data-sparseness conditions, consistent improvements in BLEU and NIST scores were obtained on all considered language pairs.
Boxing Chen, Marcello Federico
Added 22 Aug 2010
Updated 22 Aug 2010
Type Conference
Year 2006
Where FINTAL
Authors Boxing Chen, Marcello Federico
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