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Syntax-Directed Machine Translation of Natural Language: Effect of Garden Path Phenomenon on Sentence Structure

机译:语法指导的自然语言机器翻译:花园路径现象对句子结构的影响

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The potential of current machine translation (MT) of natural languages is discussed by comparing the output of embedded structure sentence, ambiguous sentence and garden path sentence. The syntax-oriented MT is a kind of literal translation which may be regarded as an idealized competence of today's practical MT. The above comparison shows that the main reason for the incompleteness of current practical MT systems is the insufficient ability to treat structural ambiguousness of sentences. With the help of Recursive Transition Network (RTN), N-S Flowchart techniques for structured programming and Context-Free Grammar (CFG), the translation examples present that, without understanding the total meaning of the source sentence, it is quite difficult to manipulate the garden path phenomenon in sentence structure. Garden path effect on sentence structure usually originates from syntactic differences, so that the syntax-free computational translation of these sentences is a very difficult problem. However, encouraging evidence is provided that the principal technologies of today's hybrid-knowledge-based MT have sufficient potential for producing barely acceptable translation. Garden path sentence possesses the features of processing breakdown and backtracking, which bring lingering effect on automatic processing. Only on the basis of hybrid knowledge databases of MT system can the suffering from garden path effect on sentence structure be alleviated and can robustness of MT system be enhanced.
机译:通过比较嵌入式结构语句,歧义语句和花园路径语句的输出,讨论了当前自然语言的机器翻译(MT)的潜力。面向语法的MT是一种字面翻译,可以看作是当今实用MT的理想能力。上面的比较表明,当前实际的MT系统不完整的主要原因是处理句子结构歧义的能力不足。借助递归转换网络(RTN),用于结构化编程的NS Flowchart技术和无上下文语法(CFG),翻译示例显示,在不了解源语句的全部含义的情况下,很难操纵花园句子结构中的路径现象。花园路径对句子结构的影响通常源于句法差异,因此这些句子的无语法计算翻译是一个非常困难的问题。但是,提供了令人鼓舞的证据,表明当今基于混合知识的MT的主要技术具有产生几乎无法接受的翻译的足够潜力。园径句具有加工故障和回溯的特点,对自动加工带来挥之不去的影响。只有在MT系统的混合知识数据库的基础上,才能缓解花园路径对句子结构的影响,并增强MT系统的鲁棒性。

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