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improving phrase-based smt model with flattened bilingual parse tree
Zhang Dakun; Sun Le; Li Wenbo
2010
Conference Name6th International Conference on Natural Language Processing and Knowledge Engineering, NLP-KE 2010
SourceProceedings of the 6th International Conference on Natural Language Processing and Knowledge Engineering, NLP-KE 2010
Pages-
Conference DateAugust 21,
Conference PlaceBeijing, China
Publish PlaceUnited States
ISBN9781420000000
Department(1) Institute of Software, Chinese Academy of Sciences, Beijing, China
English AbstractPhrase orders influence much on translation quality. However, general phrase based methods take only the source side information for phrase orderings. We instead propose a bilingual parse structure, Flattened Bilingual Parse Tree (FBPT), for better describing the inner structure of bilingual sentences and then for better translations. The main idea is to extract phrase pairs with orientation features under the help of FBPT structure. Such features can help maintain better sentence generations during translation. Furthermore, the FBPT structure can be learned automatically from parallel corpus with lower costs without the need of complex linguistic parsing. Evaluations on MT08 translation task indicate that 7% relative improvement on BLEU can be achieved compared to distortion based method (like Pharaoh). ©2010 IEEE.
KeywordComputational Linguistics Feature Extraction Information Theory Knowledge Engineering Natural Language Processing Systems Speech Transmission Syntactics
Content Type会议论文
URIhttp://ir.iscas.ac.cn/handle/311060/8798
Collection基础软件国家工程研究中心
Recommended Citation
GB/T 7714
Zhang Dakun,Sun Le,Li Wenbo. improving phrase-based smt model with flattened bilingual parse tree[C]. United States,2010:-.
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