340119 UE Machine translation (2026S)
Continuous assessment of course work
Labels
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).
- Registration is open from Mo 09.02.2026 09:00 to Fr 20.02.2026 17:00
- Registration is open from Mo 09.03.2026 09:00 to Fr 13.03.2026 17:00
- Deregistration possible until Fr 20.03.2026 23:59
Details
max. 25 participants
Language: German
Lecturers
Classes (iCal) - next class is marked with N
- Monday 09.03. 15:00 - 16:30 Medienlabor II ZfT Gymnasiumstraße 50 4.OG
- N Monday 16.03. 15:00 - 16:30 Medienlabor II ZfT Gymnasiumstraße 50 4.OG
- Monday 23.03. 15:00 - 16:30 Medienlabor II ZfT Gymnasiumstraße 50 4.OG
- Monday 13.04. 15:00 - 16:30 Medienlabor II ZfT Gymnasiumstraße 50 4.OG
- Monday 27.04. 15:00 - 16:30 Medienlabor II ZfT Gymnasiumstraße 50 4.OG
- Monday 04.05. 15:00 - 16:30 Medienlabor II ZfT Gymnasiumstraße 50 4.OG
- Monday 11.05. 15:00 - 16:30 Medienlabor II ZfT Gymnasiumstraße 50 4.OG
- Monday 18.05. 15:00 - 16:30 Medienlabor II ZfT Gymnasiumstraße 50 4.OG
- Monday 01.06. 15:00 - 16:30 Medienlabor II ZfT Gymnasiumstraße 50 4.OG
- Monday 08.06. 15:00 - 16:30 Medienlabor II ZfT Gymnasiumstraße 50 4.OG
- Monday 15.06. 15:00 - 16:30 Medienlabor II ZfT Gymnasiumstraße 50 4.OG
Information
Aims, contents and method of the course
Assessment and permitted materials
Evaluation:
• Written reflections in the Moodle forum: 30% of the grade
• Short group presentation: 30% of the grade
• MT portfolio (comprising alignment, finetuning, and annotation and post-editing task deliverables): 40% of the gradeAll 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
• Written reflections in the Moodle forum: 30% of the grade
• Short group presentation: 30% of the grade
• MT portfolio (comprising alignment, finetuning, and annotation and post-editing task deliverables): 40% of the gradeAll 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
Es gilt Anwesenheitspflicht. Zwei Abwesenheiten sind erlaubt. Die Anwesenheit ist Mindestvoraussetzung für eine positive Note.Bestehen der Lehrveranstaltung:
Um die Lehrveranstaltung zu bestehen, muss mindestens die Note 4 erzielt werden.Benotung
Sehr gut (1)
Gut (2)
Befriedigend (3)
Genügend (4)
Nicht genügend (5)
Um die Lehrveranstaltung zu bestehen, muss mindestens die Note 4 erzielt werden.Benotung
Sehr gut (1)
Gut (2)
Befriedigend (3)
Genügend (4)
Nicht genügend (5)
Examination topics
• CAT tool use
• MT fine-tuning
• MT evaluation
• MT post-editing
• MT fine-tuning
• MT evaluation
• MT post-editing
Reading list
- BS EN ISO 17100:2015: Translation Services. Requirements for translation services
- ISO/DIS 18587 Translation services - Post-editing of machine translation output Requirements
- 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
-Moorkens, J., Way, A., & S. Lankford. (2025). Automating Translation. Abingdon: Routledge
- 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/10.4324/9781003160793Additional 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.
- Wright, S. E. and Budin, G. 1997/2001. The Handbook of Terminology Management. Two volumes. Amsterdam/Philadelphia: John Benjamins Publishing Company.
- ISO/DIS 18587 Translation services - Post-editing of machine translation output Requirements
- 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
-Moorkens, J., Way, A., & S. Lankford. (2025). Automating Translation. Abingdon: Routledge
- 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/10.4324/9781003160793Additional 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.
- 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: Fr 30.01.2026 13:27
• 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 linguistsDidactic 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.