A Substitution-Translation-Restoration Framework for Handling Unknown Words in Statistical Machine Translation

Unknown words are one of the key factors that greatly affect the translation quality. Traditionally, nearly all the related researches focus on obtaining the translation of the unknown words. However, these approaches have two disadvantages. On the one hand, they usually rely on many additional reso...

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Vydané v:	Journal of computer science and technology Ročník 28; číslo 5; s. 907 - 918
Hlavní autori:	Zhang, Jia-Jun, Zhai, Fei-Fei, Zong, Cheng-Qing
Médium:	Journal Article
Jazyk:	English
Vydavateľské údaje:	Boston Springer US 01.09.2013 Springer Nature B.V National Laboratory of Pattern Recognition, Institute of Automation, Chinese Academy of Sciences, Beijing 100190, China
Predmet:	Artificial Intelligence Bilingualism Computer Science Computer simulation Data mining Data Structures and Information Theory Experiments Handling Information Systems Applications (incl.Internet) Language Machine translation Mathematical analysis Mathematical models Regular Paper Semantics Sentences SMT Software Engineering Studies Theory of Computation Translations Words (language) 框架统计机器翻译网络数据翻译质量翻译过程语义模型语言模型 Statistical machine translation Distributional semantics Bidirectional language model bidirectional language model distributional semantics statistical machine translation
ISSN:	1000-9000, 1860-4749
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