CourseSpecifications
Valid as from the academic year 2024-2025

Machine Translation and Post-editing (A704028)

Course size
Credits 5.0(nominal values; actual values may depend on programme)
Study time 150 h

Course offerings and teaching methods in academic year 2024-2025
A (semester 1)
EnglishGent

Lecturers in academic year 2024-2025
Macken, Lieve
Daems, Jokepractical
lectureindependent work

LW22
LW22

Offered in the following programmes in 2024-2025
Master of Arts in Translation: a combination of at least two languages(main subjectDutch, English)
Master of Arts in Translation: a combination of at least two languages(main subject
Dutch, English, French)
Master of Arts in Translation: a combination of at least two languages(main subject
Dutch, English, German)
Master of Arts in Translation: a combination of at least two languages(main subject
Dutch, English, Italian)
Master of Arts in Translation: a combination of at least two languages(main subject
Dutch, English, Russian)
Master of Arts in Translation: a combination of at least two languages(main subject
Dutch, English, Spanish)
Master of Arts in Translation: a combination of at least two languages(main subject
Dutch, French)
Master of Arts in Translation: a combination of at least two languages(main subject
Dutch, French, German)
Master of Arts in Translation: a combination of at least two languages(main subject
Dutch, French, Italian)
Master of Arts in Translation: a combination of at least two languages(main subject
Dutch, French, Russian)
Master of Arts in Translation: a combination of at least two languages(main subject
Dutch, French, Spanish)
Master of Arts in Translation: a combination of at least two languages(main subjectDutch, German)
Master of Arts in Translation: a combination of at least two languages(main subject
Dutch, German, Italian)
Master of Arts in Translation: a combination of at least two languages(main subjectDutch, German, Russian)
Master of Arts in Translation: a combination of at least two languages(main subject
Dutch, German, Spanish)
Master of Arts in Translation: a combination of at least two languages(main subject
Dutch, Italian)
Master of Arts in Translation: a combination of at least two languages(main subject
Dutch, Russian)
Master of Arts in Translation: a combination of at least two languages(main subjectDutch, Spanish)
Master of Arts in Translation: a combination of at least two languages(main subjectDutch, Turkish)
Master of Arts in Technology for Translation and Interpreting
Postgraduate Certificate Computer-Assisted Language Mediation(Approved)

lecturer-in-charge
co-lecturer
crdts
5offering
A

5A

5A

5A

5A

5A

5A

5A

5A

5A

5A

5A

5A

5A

5A

5A

5A

5A

5A

55A
A1

Teaching languages
EnglishKeywords
Machine translation, post-editing
Position of the course
Machine Translation (MT) is the translation of text by a computer. To produce high-qualitytranslations, humans still need to intervene in the process either by making the input moresuitable for MT (pre-editing) or changing the output (post-editing).
Contents
The course deals with the following topics:• Challenges for MT;• Architecture of MT systems (rule-based MT, statistical MT and neural MT• systems; interactive and adaptive systems; large language models (e.g. ChatGPT));• Evaluation of MT output (automatic vs. manual evaluation methods);• Post-editing and post-editing tools;• Integration of MT in the translation workflow;• Creation and evaluation of a customized MT engine.
Initial competences
The student is proficient in English and has good knowledge of at least one of the following
languages: Dutch, French, Spanish, German, Russian or Turkish.
Final competences
1 The student has advanced knowledge of different machine translation architectures and can,1 based on that knowledge, critically assess different machine translation systems;
2 The student has advanced knowledge of the evaluation methods that are used in the field of
1 MT;
3 The student has advanced knowledge of the post-editing process and the typical MT errors;
4 The student has knowledge of how MT is integrated in translation workflows.
5 The student can critically read and assess scientific work in the field of machine translation.
Conditions for credit contract
This course unit cannot be taken via a credit contract
Conditions for exam contract
This course unit cannot be taken via an exam contract
Teaching methods
Lecture, Practical, Independent work
Extra information on the teaching methods
Lectures and hands-on seminars
Guided self-study/team work at home.
Study material
Type: Slides
Name: Slides
Indicative price: Free or paid by faculty
Optional: noLanguage : English
Type: Software
Name: Online MT engines, MutNMT, MATEO, adaptive MT systems (e.g. ModernMT or Lilt), generative AI-system (e.g.
ChatGPT)
Indicative price: Free or paid by faculty
Optional: no
Online Available : Yes
References• Koehn, P. Neural Machine Translation. Cambridge University Press, 2020
• O’Brien, S., Balling L., Carl, M. , Simard, M., Specia, L. Post-editing of Machine Translation:• Processes and Applications. Cambridge Scholar Publishing, 2014
Course content-related study coaching
Interactive support via UFORA and during the lectures. Individual and collective feedback(Approved)2during lectures, or via UFORA.
Assessment moments
end-of-term and continuous assessment
Examination methods in case of periodic assessment during the first examination period
Examination methods in case of periodic assessment during the second examination period
Written assessment with open-ended questions
Examination methods in case of permanent assessment
Skills test, Assignment
Possibilities of retake in case of permanent assessment
examination during the second examination period is possible
Extra information on the examination methods
First session:• Skills test (30%)• Assignment (70%)
The skills test consists of several practical assignments that are completed during the classes.
The assignment consists of several more elaborate tasks.
Second session:• Written exam (100%)
Calculation of the examination markFirst session: skills test 30%; assignment 70%
Second session: exam 100%
In order to pass, students must participate in at least 80% of all evaluations and obligatory
activities such as guest lectures. If a student is absent due to a legitimate reason, an individual
alternative assignment can be given.
Facilities for Working Students
Class attendance is strongly recommended.
Limited possibility of feedback via e-mail, restricted to answering specific questions.

(Approved)3