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Matching Abnormality in Hybrid Machine Translation

机译:混合机器翻译中的匹配异常

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摘要

Recent MT paradigms, such as example-based MT, pattern-based MT, and hybrid MT contribute to overcoming the shortcoming of rule-based MT by improving the quality of translations. However, a problem with erroneous selection of examples or patterns also exists in these types of MTs. In this paper, we discover a matching abnormality, which we term an Over-Specification Problem that occurs when an input sentence corresponding to the pattern of general sense is actually matched to the patterns of exceptional sense, and thus is incorrectly translated. We formally define the problem and propose a solution based on the similarity of dependency trees and lexical association ratio to detect whether the input tree is dragged into the exceptional range of example trees or not. Finally, promising experimental results are provided. We take a hybrid MT as a testing MT and Chinese-to-Korean as a sample language pair.
机译:最近的MT范例,例如基于示例的MT,基于模式的MT和混合MT,有助于通过改善翻译质量来克服基于规则的MT的缺点。然而,在这些类型的MT中也存在错误选择示例或模式的问题。在本文中,我们发现了一个匹配异常,我们将其称为超规范问题,该异常是在与一般意义的模式相对应的输入句子实际上与特殊意义的模式相匹配并因此被错误翻译时发生的。我们正式定义问题并基于依赖树的相似性和词汇关联率提出解决方案,以检测输入树是否被拖入示例树的特殊范围内。最后,提供了有希望的实验结果。我们将混合式MT作为测试MT,将中文至韩语作为示例语言对。

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