Universität Wien
Warning! The directory is not yet complete and will be amended until the beginning of the term.

340248 UE Machine translation (2025S)

3.00 ECTS (2.00 SWS), SPL 34 - Translationswissenschaft
Continuous assessment of course work
Moodle
Tu 11.03. 16:45-18:15 Medienlabor II ZfT Gymnasiumstraße 50 4.OG

Registration/Deregistration

Note: The time of your registration within the registration period has no effect on the allocation of places (no first come, first served).
Register/Deregister for this course

Details

max. 25 participants
Language: German

Lecturers

Classes (iCal) - next class is marked with N

  • Tuesday 18.03. 16:45 - 18:15 Medienlabor II ZfT Gymnasiumstraße 50 4.OG
  • Tuesday 25.03. 16:45 - 18:15 Medienlabor II ZfT Gymnasiumstraße 50 4.OG
  • Tuesday 01.04. 16:45 - 18:15 Medienlabor II ZfT Gymnasiumstraße 50 4.OG
  • Tuesday 08.04. 16:45 - 18:15 Medienlabor II ZfT Gymnasiumstraße 50 4.OG
  • Tuesday 29.04. 16:45 - 18:15 Medienlabor II ZfT Gymnasiumstraße 50 4.OG
  • Tuesday 13.05. 16:45 - 18:15 Medienlabor II ZfT Gymnasiumstraße 50 4.OG
  • Tuesday 20.05. 16:45 - 18:15 Medienlabor II ZfT Gymnasiumstraße 50 4.OG
  • Tuesday 27.05. 16:45 - 18:15 Medienlabor II ZfT Gymnasiumstraße 50 4.OG
  • Tuesday 03.06. 16:45 - 18:15 Medienlabor II ZfT Gymnasiumstraße 50 4.OG
  • Tuesday 10.06. 16:45 - 18:15 Medienlabor II ZfT Gymnasiumstraße 50 4.OG
  • Tuesday 17.06. 16:45 - 18:15 Medienlabor II ZfT Gymnasiumstraße 50 4.OG

Information

Aims, contents and method of the course

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

Students will acquire hands-on computer-assisted translation (CAT) tool knowledge alongside machine translation (MT) integration, customisation, annotation, and post-editing expertise. Using state-of-the-art technologies, students will learn to fine-tune pre-trained MT models, evaluate them using automatic and manual metrics, integrate them into a popular CAT tool, annotate their output using popular industry annotation frameworks, and post-edit MT output according to ISO standards.

Content:
• Computer-assisted translation (CAT) tools
• Neural MT architectures and fine-tuning pre-trained models
• MT evaluation metrics and annotation tools and techniques
• MT in professional workflows
• Post-editing machine translation (PEMT) standards and best practices
• Ethics of using MT and impact of MT on freelance linguists

Didactic approach:
This course is likely to appear as a simulated, technology-intensive internship with a language service provider (LSP). Students will need to complete assignments involving a number of technologies ranging from CAT tools to solutions for fine-tuning, integrating, evaluating, and improving MT output. Students will also gain experience of post-editing MT output according to ISO standards.
The course will be taught in German, but the source language of the assigned texts is English. For this reason, basic knowledge of English is required.

Assessment and permitted materials

Evaluation:
• Weekly reflections: 30% of the grade
• MT portfolio (comprising alignment, finetuning, and annotation and post-editing task deliverables): 30% of the grade
• Short group presentation: 40% of the grade

Students must complete all assignments.

All media and tools are allowed, but their use needs to be referenced. Furthermore, if using AI Tools such as ChatGPT for any tasks, you also need to provide the prompt used. Generally, we follow the principles described here: https://libguides.brown.edu/c.php?g=1338928&p=9868287

Minimum requirements and assessment criteria

Attendance is mandatory. Two absences are allowed.

MT UE pass mark
In order to pass this module, a student needs to reach the threshold of 4.

MT UE marking map
Excellent - Sehr Gut (1)
Good - Gut (2)
Satisfactory - Befriedigend (3)
Sufficient - Genügend (4)
Fail - Nicht Genügend (5)

Examination topics

• CAT tool use
• MT fine-tuning
• MT evaluation
• MT post-editing

Reading list

Core texts:
- 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)
- Koehn, P. 2020. Neural Machine Translation. Cambridge University Press
- Moniz, H., & Parra Escartín, C. (Eds.). (2023). Towards Responsible Machine Translation: Ethical and Legal Considerations in Machine Translation (Vol. 4). Springer International Publishing. https://doi.org/10.1007/978-3-031-14689-3
- ISO/DIS 18587 Translation services - Post-editing of machine translation output Requirements
- BS EN ISO 17100:2015: Translation Services. Requirements for translation services
- Rothwell, Andrew, Joss Moorkens, María Fernández-Parra, Joanna Drugan and Frank Austermuehl. 2023. Translation Tools and Technologies (1st ed.). London/New York: Routledge https://doi.org/10.4324/9781003160793

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
- Chan, Sin-Wai. Ed. 2015. Routledge encyclopedia of translation technology Abingdon, Oxon : Routledge.
- 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.
- Kockaert, H. J. and Steurs, F. Eds. 2015. Handbook of terminology. Amsterdam; Philadelphia: John Benjamins Publishing Company.- 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, 101123. 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.

Association in the course directory

Last modified: Tu 04.02.2025 17:06