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Corpus Data across Languages and Disciplines


Edited By Piotr Pezik

Over the recent years corpus tools and methodologies have gained widespread recognition in various areas of theoretical and applied linguistics. Data lodged in corpora is explored and exploited across languages and disciplines as distinct as historical linguistics, language didactics, discourse analysis, machine translation and search engine development to name but a few. This volume contains a selection of papers presented at the 8 th edition of the Practical Applications in Language and Computers conference and it is aimed at helping a wide community of researchers, language professionals and practitioners keep up to date with new corpus theories and methodologies as well as language-related applications of computational tools and resources.


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How DOES Google Translate? Belinda Maia and Rui Sousa-Silva


Abstract In this paper we shall look at how Google Translate is contributing to the world of professional translation. We argue in favour of training translators to accept machine translation, to learn how to use it as a tool and to revise the result for clients who need translations for urgent and more ephemeral use, like the background for tomorrow’s meeting We investigate whether Google actually uses the vast material at its disposal efficiently to obtain its results, and examine its claims to use only statistical means. The objective is to increase awareness of the strengths and weaknesses of machine translation as a tool. Keywords Machine translation, professional human translation and research. Introduction The background to this paper involves the EMT - European Master’s in Translation Network1 and the Academic Network OPTIMALE – Optimising Professional Translator Training in a Multilingual Europe2, and the perceived need to understand how the demands on the professional translator and language service provider will evolve. Experience shows that revision of MT is becoming an essential skill for professional translators, and we shall consider how human translation – HT – can use Google Translate – GT – and other MT systems for professional language services. Our personal interest is in observing how online text resources are used for Natural Language Processing – NLP – generally, and Machine Translation - MT - in particular, and how training future translators to use MT can contribute to linguistic analysis and topics for research. While the MT world debates the value of rule-based MT (RBMT) versus example-based...

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