Understanding and enhancing translation by parallel text processing

Sammanfattning: 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.