Title

多策略机器翻译系统IHSMTS中实例模式泛化匹配算法

Translated Titles

Generalizing Match of Translation Examples in IHSMTS

Authors

张孝飞(Xiao-Fei Zhang);陈肇雄(Zhao-Xiong Chen);黄河燕(He-Yan Huang);胡春玲(Chun-Ling Hu)

Key Words

人工智能 ; 机器翻译 ; 基于实例的机器翻译 ; 泛化匹配 ; 翻译覆盖率 ; artificial intelligence ; machine translation ; example-based machine translation ; generalizing match ; translation coverage

PublicationName

中文信息學報

Volume or Term/Year and Month of Publication

19卷4期(2005 / 07 / 01)

Page #

1 - 9

Content Language

簡體中文

Chinese Abstract

基于精确匹配的EBMT,由于翻译覆盖率过低,导致其难以大规模实际应用本文提出一种实例模式泛化匹配算法,试图改善EBMT的翻译覆盖率:以输入的待翻译句子为目标导向,对候选翻译实例有针对性地进行实时泛化,使得算法既能满足实时文档翻译对速度的要求,又能充分利用系统使用过程中用户新添加和修改的翻译知识,从而总体上提高了系统的翻译覆盖率和翻译质量。实验结果表明,在语料规模为16万句对的情况下,系统翻译覆盖率达到了75%左右,充分说明了本文算法的有效性。

English Abstract

Example-based machine translation is currently difficult in large-scale implications because of its low translation coverage. In this paper, an algorithm of generalizing match of translation examples is proposed to improve the translation coverage of EBMT: the candidate translation examples are generalized in real time controlled and guided by the input sentence which to be translated. The algorithm not only can satisfy the speed of real time documents translation hut also can use the new language knowledge which added and revised by users in the translation processing. So a higher translation coverage and translation quality is obtained as a whole. The positive experiment results of 75% translation coverage basis on 160,000 pairs of translation examples confirm the algorithm's effect.

Topic Category 基礎與應用科學 > 資訊科學