ABSTRACT

Evidence from the contemporary translation services market and many centuries of translation practice demonstrate that translation into a non-native language (L2 translation) can be performed effectively, despite the once-strong resistance to it on the grounds of it being perceived as unprofessional and inherently deficient. L2 translation is in fact unavoidable in the case of so-called languages of low diffusion, the command of which happens to be rather limited among native speakers of major languages. However, although the academic dispute about the validity of L2 translation seems decidedly milder now, there is still a lacuna within L2 translator training that needs to be addressed. This paper indicates that what usually betrays an L2 translation is its phraseological profile, often recognised as unnatural by native speakers of the target language. The aim of this paper is to propose a corpus-based data mining technique that may help L2 legal translator trainees become more observant with regards to phraseological patterning of foreign legal discourse, and more self-confident in taking well-informed translation decisions.

摘要

从当代翻译服务市场和许多世纪的翻译实践中获得的证据表明，可以有效地进行非本国语言的翻译（L2翻译），尽管人们曾一度强烈反对它，因为它被认为是非专业的，并且是固有的。不足。实际上，在所谓的低扩散语言中，L2翻译是不可避免的，在主要母语的母语人士中，其命令恰好受到限制。但是，尽管有关L2翻译有效性的学术争论现在看来已经温和了一些，但是L2翻译培训中仍然存在一些空白需要解决。本文指出，通常会背叛L2翻译的是其词组概况，通常被目标语言的母语者认为是不自然的。本文的目的是提出一种基于语料库的数据挖掘技术，该技术可以帮助L2的法律翻译学员对外国法律话语的措辞模式更加了解，并在做出明智的翻译决策时更加自信。