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首页> 外文期刊>International Journal of Computational Science and Engineering >Syntactic parsing of clause constituents for statistical machine translation
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Syntactic parsing of clause constituents for statistical machine translation

机译:统计机器翻译子句组分的句法解析

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摘要

The clause is considered as the basic unit of grammar in linguistics, which is a structure between a chunk and a sentence. Clause constituents, therefore, are one important kind of linguistically valid syntactic phrases. This paper adopts the CRFs model to recognise English clause constituents with their syntactic functions, and testifies their effect on machine translation by applying this syntactic information to an English-Chinese PBSMT system, evaluated on a corpus of business domain. Clause constituents are mainly classified into six kinds: subject, predicate, complement, adjunct, residues of predicate, and residues of complement. Results show that our rich-feature CRFs model achieves an F-measure of 93.31%, a precision of 93.26%, and a recall of 93.04%. This syntactic knowledge in the source language is further combined with the NiuTrans phrasal SMT system, which slightly improves the English-Chinese translation accuracy.
机译:该条款被认为是语言学中语言的基本单位,这是一个块和句子之间的结构。 因此,组成部分是一种重要的语言上有效的句法短语。 本文采用CRFS模型以其句法函数识别英语子句成分,并通过将此句法信息应用于英语 - 中文PBSMT系统,对其对机器翻译的影响,在商业域的语音上进行评估。 条款成分主要分为六种:受试者,谓词,补体,辅助,谓词残留物,以及补体的残留物。 结果表明,我们的丰富特征CRFS模型实现了93.31%的F-Measure,精度为93.26%,召回为93.04%。 源语言中的这种句法知识与Niutrans短语SMT系统相结合,这略微提高了英汉的翻译准确性。

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