DocumentCode
3142303
Title
The research of passive voice in Chinese-English patent machine translation
Author
Liu, Zhiying ; Jin, Yaohong
Author_Institution
Inst. of Chinese Inf. Process., Beijing Normal Univ., Beijing, China
fYear
2011
fDate
27-29 Nov. 2011
Firstpage
300
Lastpage
303
Abstract
This paper conducts comprehensive researches on the translation of passive voice from Chinese to English based on the characteristics that passive voice is often found in patent documents, indicates the necessary to transform the voice in the perspective of semantics and HNC theory, analyzes the language phenomenon of passive voice in Chinese-English Translation, points out that there are three kinds of situations in processing the voice: not passive voice, passive voice with marks, passive voice without marks, puts forward the plan to solve the transformation of passive voice aimed at the difficulties, suggests that the result expression of active sentence without marks needs to transform into the passive voice from active voice in three types: VP+NP, NP1+VP+NP2, NP+VP, discusses the order of semantic chunks in the transformed sentence, gives the transformation rules and algorithm. By using the processing strategies most of the Chinese-English translation problem about the passive voice can be perfectly solvable on an online patent MT system in SIPO.
Keywords
language translation; natural language processing; Chinese-English patent machine translation; HNC theory; hierarchical network of concepts; not passive voice processing; passive voice translation; passive-voice-with-marks processing; passive-voice-without-marks processing; semantic chunk; semantics perspective; Patents; HNC Theory; Machine Translation(MT); passive voice; patent document; sentence category;
fLanguage
English
Publisher
ieee
Conference_Titel
Natural Language Processing andKnowledge Engineering (NLP-KE), 2011 7th International Conference on
Conference_Location
Tokushima
Print_ISBN
978-1-61284-729-0
Type
conf
DOI
10.1109/NLPKE.2011.6138213
Filename
6138213
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