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首页> 外文会议>9th International conference on language resources and evaluation >Linguistic Evaluation of Support Verb Constructions by OpenLogos and Google Translate
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Linguistic Evaluation of Support Verb Constructions by OpenLogos and Google Translate

机译：通过OpenLogos和Google Translate对支持动词结构进行语言评估

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摘要

This paper presents a systematic human evaluation of translations of English support verb constructions produced by a rule-based machine translation (RBMT) system (OpenLogos) and a statistical machine translation (SMT) system (Google Translate) for five languages: French, German, Italian, Portuguese and Spanish. We classify support verb constructions by means of their syntactic structure and semantic behavior and present a qualitative analysis of their translation errors. The study aims to verify how machine translation (MT) systems translate fine-grained linguistic phenomena, and how well-equipped they are to produce high-quality translation. Another goal of the linguistically motivated quality analysis of SVC raw output is to reinforce the need for better system hybridization, which leverages the strengths of RBMT to the benefit of SMT, especially in improving the translation of multiword units. Taking multiword units into account, we propose an effective method to achieve MT hybridization based on the integration of semantico-syntactic knowledge into SMT.
机译：本文介绍了针对五种语言的基于规则的机器翻译（RBMT）系统（OpenLogos）和统计机器翻译（SMT）系统（Google Translate）生成的英语支持动词结构的翻译的系统化人工评估。意大利语，葡萄牙语和西班牙语。我们根据支持动词的句法结构和语义行为对其进行分类，并对它们的翻译错误进行定性分析。这项研究旨在验证机器翻译（MT）系统如何翻译细粒度的语言现象，以及它们如何提供高质量的翻译。语言学上对SVC原始输出进行质量分析的另一个目标是，加强对更好的系统混合的需求，这需要利用RBMT的优势来实现SMT的优势，特别是在改善多字单元的翻译方面。考虑到多词单元，我们提出了一种有效的方法，以将语义-句法知识集成到SMT中来实现MT混合。

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