Advanced Information Technology for Translation - 2nd semester
Objectives
Acquire more advanced competencies in the use of technology in translation. Increase student awareness of the scope and limitations of Computer Assisted Language (CAT) Tools. Increase their interoperability skills in creating, processing and transferring data between Computer Assisted Language (CAT) Tools. Increase student awareness of major developments in translation and technology.
General characterization
Code
711121071
Credits
6
Responsible teacher
David Hardisty
Hours
Weekly - 4
Total - Available soon
Teaching language
Portuguese
Prerequisites
Bibliography
Kirchhoff, Katrin, Capurro, Daniel & Turner, AnneM. \"A conjoint analysis framework for evaluating user references in machine translation\", Machine Translation, March 2014, Volume 28, Issue 1, pp 117.
SDL Trados Studio 2014 SP1 Migration Guide, SDL; Maidenhead, 2014.
SDL Trados Studio 2014. Advanced Manual, SDL; Maidenhead, 2014.
Steinberger Ralf, Bruno Pouliquen, Anna Widiger, Camelia Ignat, Toma Erjavec, Dan Tufis, Dániel Varga (2006). The JRC-Acquis: A multilingual aligned parallel corpus with 20+ languages. Proceedings of the 5th International Conference on Language Resources and Evaluation (LREC´2006). Genoa, Italy, 2426 May 2006.
Zetzsche, Jost, The Translators Tool Box: A Computer Primer for Translators. Version 11; Winchester Bay. International writers Group,. 2014.
Teaching method
The classes take place in a computer room. They include short demonstrations by the teacher to show software functions, or demonstrations where students also do the steps being shown. Students will also research one particular specialised area in the second half of the course and present their findings to their peers. Material will be made available on the Faculty´s elearning platform.
Evaluation method
Students will be given an oral exam at the computer to show the software competencies they have acquired during the course.
Subject matter
Students will build on the fundamental concepts of Computer Assisted Translation (CAT) Tools and develop skills and competencies in:
Translation Memory (TM) Management;
More Advanced Termbase Record Structures;
Familiarity of the use of TMX and TBX standards to process and transfer data between CAT systems;
Larger Aligning Projects and their Workflows;
Developments in Machine Translation and Automatic Speech Recognition.