liu.seSearch for publications in DiVA
Change search
CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • harvard1
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • oxford
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf
Understanding and enhancing translation by parallel text processing
Linköping University, Department of Computer and Information Science. Linköping University, The Institute of Technology.
1999 (English)Doctoral thesis, monograph (Other academic)
Abstract [en]

In recent years the fields of translation studies, natural language processing and corpus linguistics have come to share one object of study, namely parallel text corpora, and more specifically translation corpora. In this thesis it is shown how all three fields can benefit from each other, and, in particular, that a prerequisite for making better translations (whether by humans or with the aid of computer-assisted tools) is to understand features and relationships that exist in a translation corpus. The Linköping Translation Corpus (LTC) is the empirical foundation for this work. LTC is comprised of translations from three different domains and translated with different degrees of computer support. Results in the form of tools, measures and analyses of translations in LTC are presented.

In the translation industry, the use of translation memories, which are based on the concept of reusability, has been increasing steadily in recent years. In an empirical study, the notion of reusability in technical translation is investigated as well as translators' attitudes towards translation tools.

A toolbox for creating and analysing parallel corpora is also presented. The tools are then used for uncovering relationships between the originals and their corresponding translations. The Linköping Word Aligner (LWA) is a portable tool for linking words and expressions between a source and target text. LWA is evaluated with the aid of reference data compiled before the system evaluation. The reference data are created and evaluated automatically with the help of an annotation tool, called the PLUG Link Annotator.

Finally, a model for describing correspondences between a source text and a target text is introduced. The model uncovers voluntary shifts concerning structure and content. The correspondence model is then applied to the LTC.

Place, publisher, year, edition, pages
Linköping: Linköpings universitet , 1999. , 232 p.
Series
Linköping Studies in Science and Technology. Dissertations, ISSN 0345-7524 ; 607
National Category
Computer Science
Identifiers
URN: urn:nbn:se:liu:diva-35741Local ID: 28387ISBN: 91-7219-614-9 (print)OAI: oai:DiVA.org:liu-35741DiVA: diva2:256589
Public defence
1999-12-10, I:101, Hus I, Linköpings universitet, Linköping, 13:15 (Swedish)
Available from: 2009-10-10 Created: 2009-10-10 Last updated: 2013-02-21

Open Access in DiVA

No full text

Authority records BETA

Merkel, Magnus

Search in DiVA

By author/editor
Merkel, Magnus
By organisation
Department of Computer and Information ScienceThe Institute of Technology
Computer Science

Search outside of DiVA

GoogleGoogle Scholar

isbn
urn-nbn

Altmetric score

isbn
urn-nbn
Total: 246 hits
CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • harvard1
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • oxford
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf