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Erschienen in:
2006 | OriginalPaper | Buchkapitel
Some Improvements in Phrase-Based Statistical Machine Translation
verfasst von : Zhendong Yang, Wei Pang, Jinhua Du, Wei Wei, Bo Xu
Erschienen in: Chinese Spoken Language Processing
Verlag: Springer Berlin Heidelberg
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In statistical machine translation, many of the top-performing systems are phrase-based systems. This paper describes a phrase-based translation system and some improvements. We use more information to compute translation probability. The scaling factors of the log-linear models are estimated by the minimum error rate training that uses an evaluation criteria to balance BLEU and NIST scores. We extract phrase-template from initial phrases to deal with data sparseness and distortion problem through decoding. By re-ranking the n-best list of translations generated firstly, the system gets the final output. Some experiments concerned show that all these refinements are beneficial to get better results.