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ACL
2003

Feedback Cleaning of Machine Translation Rules Using Automatic Evaluation

8 years 10 months ago
Feedback Cleaning of Machine Translation Rules Using Automatic Evaluation
When rules of transfer-based machine translation (MT) are automatically acquired from bilingual corpora, incorrect/redundant rules are generated due to acquisition errors or translation variety in the corpora. As a new countermeasure to this problem, we propose a feedback cleaning method using automatic evaluation of MT quality, which removes incorrect/redundant rules as a way to increase the evaluation score. BLEU is utilized for the automatic evaluation. The hillclimbing algorithm, which involves features of this task, is applied to searching for the optimal combination of rules. Our experiments show that the MT quality improves by 10% in test sentences according to a subjective evaluation. This is considerable improvement over previous methods.
Kenji Imamura, Eiichiro Sumita, Yuji Matsumoto
Added 31 Oct 2010
Updated 31 Oct 2010
Type Conference
Year 2003
Where ACL
Authors Kenji Imamura, Eiichiro Sumita, Yuji Matsumoto
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