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Translation Tools

Translation Memory Systems Text Concordance Tools Useful Websites

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Translation Memory Systems

General principles and features Scope of application with legal texts: pros and cons Demonstration of OmegaT Hands-on experience with OmegaT

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Principles and Features I

Translate only once, re-use of already translated text: Internal recurrence

Segments, which are occur more than once in the source text and have not been translated before and thus have not been saved in the translation memory (exact matches) match propagation.

External recurrencetext segments which have been previously translated in other texts and thus are saved in the translation memory

Consistency of text and terminology:identical text will always be translated the same way

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Principles and Features II

Keep format information intactthat means separating text from layout information edit text in an editor use of filters for different file formats import = replace layout information with placeholders export = replace placeholders with original layout

information

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How does it work? the text is splitted up in text chunks (=segments) which can

be sentences or paragraphs. each segment is matched to the translation memory

exact match fuzzy match match-percentage: value of minimal similarity between a

new text segment to translate and a segment found in the memory

segments will be saved in pairs: source language text and target language text

these form translation units (TU) in translation memories

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Segmentation rules

Sentence level Pro: smaller text segments = higher reusability

better matching Con: sentence for sentence translation method, more post-

editing needed Paragraph level

Pro: bigger text segments = better translation quality, less post-editing

Con: lower reusability

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Best context for the use of TM

Conventionalized text structures Stereotypical formulations Identical macrostructure Frequent updates of a text

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Legal texts types

Best suited for translation memory systems are highly standardized legal text types such as: bylaws (e.g. http://www.weown.net/cooperat.htm) contracts, agreements (e.g.

http://www.lomb.cgil.it/rsuibm/1999627a.htm) sentences administrative legal texts

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Commercial Software

SDL Trados Translator's Workbench SDLX (SDL) DejaVu (Atril) Transit (Star) MemoQ MultiTrans (Multicorpora) Wordfast (Champollion) Heartsome Translation Suite

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OmegaT

OpenSource Translation Memory

http://www.omegat.org/omegat/omegat.html requirements

Java Runtime Environment (http://www.sun.com)

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Corpus and Concordance Tools

A corpus is a collection of pieces of language that are selected and ordered according to explicit linguistic criteria in order to be used as a sample of the language. (EAGLES, 1996)

use of corpora:

– Word frequency

– Lexical context

– Syntactic context

– Semantic context

– Style

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Legal Corpora

Criteria for a legal corpus: Legal system and language General legal corpus (e.g. Austrian legal language) =

extensive, very large to be representativ Specific legal corpus (e.g. Austrian legal language for Civil Law)

= still large Specilized legal corpus (e.g. Austrian legal language for

succession law) = manageable Genre specific corpus (e.g. Austrian testaments) = very

manageable and suited for translation purposes

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Concordance Tools

TextStat2 http://www.niederlandistik.fu-berlin.de/textstat/software-en.html

AntConc 3.2http://www.antlab.sci.waseda.ac.jp/software.html

Literature: Pearson, Jennifer; Bowker, Lynne (2002): Working with specialized

language. a practical guide to using corpora. Routledge, London. Bowker, Lynne (2002): Computer-aided Translation Technology. A

Practical Introduction. University of Ottawa Press, Ottawa. .