Publishing Partner: Cambridge University Press CUP Extra Publisher Login

New from Cambridge University Press!


Revitalizing Endangered Languages

Edited by Justyna Olko & Julia Sallabank

Revitalizing Endangered Languages "This guidebook provides ideas and strategies, as well as some background, to help with the effective revitalization of endangered languages. It covers a broad scope of themes including effective planning, benefits, wellbeing, economic aspects, attitudes and ideologies."

We Have a New Site!

With the help of your donations we have been making good progress on designing and launching our new website! Check it out at!
***We are still in our beta stages for the new site--if you have any feedback, be sure to let us know at***

Academic Paper

Title: Machine Translation of Various Text Genres
Paper URL:
Author: Andreea Simona Calude
Email: click here TO access email
Institution: University of Reading
Linguistic Field: Translation
Subject Language: English
Abstract: Machine translation (MT) has been both praised and criticized since the 1930’s when it was first introduced. Today, MT − much improved since then, is a vital tool for the human translator, although not without its problems. One important issue which to our knowledge has not yet been investigated is the success of MT for different text types. In the present study, we compare the performance of German-English machine translation in four different text genres which vary in their structures, using Systran Systems. Systran Company, one of the oldest and most reputable MT producers (dating back to 1968), has been involved with top governmental agencies, such as the US National Air Intelligence Center and the US Air Force’s Foreign Technology Division. The texts are analysed with respect to two types of linguistic errors; errors which impede correct transfer of meaning (such as mistranslation of idioms) and errors which merely affect the flow and readability of the texts (e.g., mistranslation of prepositions). These error types can be roughly equated to the traditional measures of intelligibility and fidelity, respectively. Our results show that MT is still limited in its ability to process certain text types, namely those with complex sentence structures, high amounts of pragmatic information and broad semantic domains. In addition, MT tends to produce a number of linguistic errors, most notably the mistranslation of polysemous items. In the final part of the paper, we identify the most frequent linguistic errors and the texts genres MT is best suited for. The theoretical implications of the methodology proposed and the hypotheses investigated constitute the core of the contribution made by this paper.
Type: Individual Paper
Status: Completed
Venue: Presented at the 7th Language and Society Conference organised by the New Zealand Linguistics Society, Hamilton, Auckland, November 2002
Publication Info: Te Reo, the Journal of the New Zealand Linguistics Society, Volume 46, 2004, p. 67-94
Add a new paper
Return to Academic Papers main page
Return to Directory of Linguists main page