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題名 Effects of Combining Bilingual and Collocational Information on Translation of English and Chinese Verb-Noun Pairs
作者 劉昭麟
Chuang,Yi-Hsuan
Liu,Chao-Lin
Chang,Jing-Shin
貢獻者 資科系
關鍵詞 Information retrieval; Learning to rank; Query-level loss function; RankCosine
日期 2012-09
上傳時間 11-九月-2014 10:43:51 (UTC+8)
摘要 We studied a special case of the translation of English verbs in verb-object pairs. Researchers have studied the effects of the linguistic information of the verbs being translated, and many have reported how considering the objects of the verbs will facilitate the quality of translation. In this study, we took an extreme approach - assuming the availability of the Chinese translation of the English object. In a related exploration, we examined how the availability of the Chinese translation of the English verb influences the translation quality of the English nouns in verb phrases with analogous procedures. We explored the issue with 35 thousand VN pairs that we extracted from the training data obtained from the 2011 NTCIR PatentMT workshop and with 4.8 thousand VN pairs that we extracted from a bilingual version of Scientific American magazine. The results indicated that, when the English verbs and objects were known, the additional information about the Chinese translations of the English verbs (or nouns) could improve the translation quality of the English nouns (or verbs) but not significantly. Further experiments were conducted to compare the quality of translation achieved by our programs and by human subjects. Given the same set of information for translation decisions, human subjects did not outperform our programs, reconfirming that good translations depend heavily on contextual information of wider ranges.
關聯 Computational Linguistics and Chinese Language Processing,17(3),1-28
資料類型 article
dc.contributor 資科系en_US
dc.creator (作者) 劉昭麟zh_TW
dc.creator (作者) Chuang,Yi-Hsuanen_US
dc.creator (作者) Liu,Chao-Linen_US
dc.creator (作者) Chang,Jing-Shinen_US
dc.date (日期) 2012-09en_US
dc.date.accessioned 11-九月-2014 10:43:51 (UTC+8)-
dc.date.available 11-九月-2014 10:43:51 (UTC+8)-
dc.date.issued (上傳時間) 11-九月-2014 10:43:51 (UTC+8)-
dc.identifier.uri (URI) http://nccur.lib.nccu.edu.tw/handle/140.119/69778-
dc.description.abstract (摘要) We studied a special case of the translation of English verbs in verb-object pairs. Researchers have studied the effects of the linguistic information of the verbs being translated, and many have reported how considering the objects of the verbs will facilitate the quality of translation. In this study, we took an extreme approach - assuming the availability of the Chinese translation of the English object. In a related exploration, we examined how the availability of the Chinese translation of the English verb influences the translation quality of the English nouns in verb phrases with analogous procedures. We explored the issue with 35 thousand VN pairs that we extracted from the training data obtained from the 2011 NTCIR PatentMT workshop and with 4.8 thousand VN pairs that we extracted from a bilingual version of Scientific American magazine. The results indicated that, when the English verbs and objects were known, the additional information about the Chinese translations of the English verbs (or nouns) could improve the translation quality of the English nouns (or verbs) but not significantly. Further experiments were conducted to compare the quality of translation achieved by our programs and by human subjects. Given the same set of information for translation decisions, human subjects did not outperform our programs, reconfirming that good translations depend heavily on contextual information of wider ranges.en_US
dc.format.extent 320565 bytes-
dc.format.mimetype application/pdf-
dc.language.iso en_US-
dc.relation (關聯) Computational Linguistics and Chinese Language Processing,17(3),1-28en_US
dc.subject (關鍵詞) Information retrieval; Learning to rank; Query-level loss function; RankCosineen_US
dc.title (題名) Effects of Combining Bilingual and Collocational Information on Translation of English and Chinese Verb-Noun Pairsen_US
dc.type (資料類型) articleen