Universität Wien

340372 VU Translation Technologies (2022W)

4.00 ECTS (2.00 SWS), SPL 34 - Translationswissenschaft
Prüfungsimmanente Lehrveranstaltung
Moodle

An/Abmeldung

Hinweis: Ihr Anmeldezeitpunkt innerhalb der Frist hat keine Auswirkungen auf die Platzvergabe (kein "first come, first served").

Details

max. 40 Teilnehmer*innen
Sprache: Englisch

Lehrende

Termine (iCal) - nächster Termin ist mit N markiert

- This course will be taught in person in the ZTW computer lab, without a hybrid or online option -

Mittwoch 12.10. 16:45 - 18:15 Medienlabor II ZfT Gymnasiumstraße 50 4.OG
Mittwoch 19.10. 16:45 - 18:15 Medienlabor II ZfT Gymnasiumstraße 50 4.OG
Mittwoch 09.11. 16:45 - 18:15 Medienlabor II ZfT Gymnasiumstraße 50 4.OG
Mittwoch 16.11. 16:45 - 18:15 Medienlabor II ZfT Gymnasiumstraße 50 4.OG
Mittwoch 30.11. 16:45 - 18:15 Medienlabor II ZfT Gymnasiumstraße 50 4.OG
Mittwoch 07.12. 16:45 - 18:15 Medienlabor II ZfT Gymnasiumstraße 50 4.OG
Mittwoch 14.12. 16:45 - 18:15 Medienlabor II ZfT Gymnasiumstraße 50 4.OG
Mittwoch 11.01. 16:45 - 18:15 Medienlabor II ZfT Gymnasiumstraße 50 4.OG
Mittwoch 18.01. 16:45 - 18:15 Medienlabor II ZfT Gymnasiumstraße 50 4.OG
Mittwoch 25.01. 16:45 - 18:15 Medienlabor II ZfT Gymnasiumstraße 50 4.OG

Information

Ziele, Inhalte und Methode der Lehrveranstaltung

- This course will be taught in person in the ZTW computer lab –

Goals:

Students will become familiar with the state of the art in a range of translation technologies used to manage and complete localisation projects, and will be able to apply their knowledge to solve a range of localisation challenges.

In particular, by the end of the course they will be able to:
- design effective localisation workflows and create collaborative localisation projects;
- suggest a variety of ways in which localisation project automation can be achieved fully or partially;
- create, maintain, and exchange language assets (translation memories, termbases, segmentation rules, etc.) between computer-assisted translation (CAT) tools;
- integrate and customise machine translation (MT) engines for localisation workflows;
- use several CAT tools for the translation/revision/post-editing of content in a variety of file formats;
- use and customise quality assurance (QA) features of CAT tools.
- export localisation project deliverables in a range of formats, including standardised translation content exchange formats;
- assess critically the merits and challenges of several translation technologies and automation approaches used in localisation projects.
Didactic approach:
The content of this course is acquired by students in an interactive and blended way between in-class tasks and hands-on home assignments studying the research literature and reflecting on a variety of Language Services Industry business and technical problems. The course is delivered in English.

Art der Leistungskontrolle und erlaubte Hilfsmittel

Students will need to use all the knowledge and experience regarding a wide range of aspects connected with various translation technologies which they have acquired during the course to complete several assessed tasks, as well as write an end-of-course essay.

Mindestanforderungen und Beurteilungsmaßstab

MT VO marking map
excellent - sehr gut (1)
good - gut (2)
average - befriedigend (3)
sufficient - genügend (4)
insufficient - nicht genügend (5)

Prüfungsstoff

Continuous evaluation:
- attendance, seminar presentation and weekly reflections count for 20% of the mark.
- student portfolio counts for 40% of the mark.
- final essay counts for 40% of the mark.

Literatur

Core text and resources:
- Chan, Sin-Wai. Ed. 2015. Routledge encyclopedia of translation technology Abingdon, Oxon : Routledge.
- DigiLing Project, Localization Tools and Workflows course: https://learn.digiling.eu/course/view.php?id=5

Additional recommended resources:
- Globally Speaking: A podcast for and by localization professionals. https://www.globallyspeakingradio.com/

- Carstensen, K-U. 2017. Sprachtechnologie - Ein Überblick. http://kai-uwe-carstensen.de/
Publikationen/Sprachtechnologie.pdf
- Depraetere, I. Ed. 2011. Perspectives on translation quality. Berlin: de Gruyter Mouton
- Hausser, Roland. 2000. Grundlagen der Computerlinguistik - Mensch-Maschine-Kommunikation in natürlicher Sprache (mit 772 – Übungen). Springer.
- Kenny, Dorothy. 2022. Machine translation for everyone: Empowering users in the age of artificial intelligence. (Translation and Multilingual Natural Language Processing 18). Berlin: Language Science Press. DOI: 10.5281/zenodo.6653406 (url: https://langsci-press.org/catalog/book/342)
- Kockaert, H. J. and Steurs, F. Eds. 2015. Handbook of terminology. Amsterdam; Philadelphia: John Benjamins Publishing Company.
- Koehn, P. 2020. Neural Machine Translation. Cambridge University Press
- Munday, J. 2012. Evaluation in translation: critical points of translator decision-making: Routledge.
- O'Hagan, M. Ed. 2019. The Routledge Handbook of Translation and Technology. Abingdon: Routledge
- Waibel, A. 2015. Sprachbarrieren durchbrechen: Traum oder Wirklichkeit? Nova Acta Leopoldina NF 122, Nr. 410, 101–123. https://isl.anthropomatik.kit.edu/downloads/
NAL_Bd122_Nr410_101-124_Waibel_low_res.pdf
- Wright, S. E. and Budin, G. 1997/2001. The Handbook of Terminology Management. Two volumes. Amsterdam/Philadelphia: John Benjamins Publishing Company.
- BS EN ISO 17100:2015: Translation Services. Requirements for translation services
- ISO/DIS 18587 Translation services - Post-editing of machine translation output – Requirements

Zuordnung im Vorlesungsverzeichnis

Letzte Änderung: Do 06.07.2023 17:08