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Translation Studies and Translation Practice: Proceedings of the 2nd International TRANSLATA Conference, 2014

Part 1

Series:

Edited By Lew N. Zybatow, Andy Stauder and Michael Ustaszewski

TRANSLATA II was the second in a series of triennial conferences on Translation and Interpreting Studies, held at the University of Innsbruck. The series is conceptualized as a forum for Translation Studies research. The contributions to this volume focus on humo(u)r translation, legal translation, and human-machine interaction in translation. The contributors also regard computer-aided translation, specialised translation, terminology as well as audiovisual translation and professional aspects in translation and interpreting.

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What can Linguistics do for Translation Technology? (Andy Stauder)

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Andy Stauder, University of Innsbruck (Austria)

What can Linguistics do for Translation Technology?

Abstract: Modern CAT/NLP is based largely on statistics, analogous text, and human-machine interaction. Despite improvements over rule-based and machine-only systems, it has been struggling with non-standardised text. This could be overcome with traditional linguistic approaches and a possible future neurolinguistic type of translation studies.

Много несчастий произошло на свете от недоумений и от недосказанности.

[Much misfortune has come about in the world because of incomprehension and things unsaid.]

F. Dostoyevsky (1861: 44), my translation

1. Introduction

The modern translator’s toolset has been characterised by a number of electronic aids for years now. These range from word processors, which have basically replaced typewriters, pen and paper for an even longer period of time, to what is referred to as natural language processing (NLP) in a wider sense. The latter is a field that concerns itself with the analysis and transformation of natural language input in order to produce an output that should qualify as natural language as well. The field has become an extensive one, and has one sub-field which is still most prominent in terms of translators’ toolsets: computer-aided translation (CAT). This has been in widespread use for almost ten years now (see e.g. Lagoudaki 2006, 15) among more than 80 percent of professional translators. NLP in a narrower sense, i.e. fully automated language processing, has been more of an academic field and commercial pursuit that seems to compete with human translation – however,...

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