General provisions

The course can be given within the Master's Programme in Language Technology and as a freestanding course.

Entry requirements

A Bachelor's degree and (1) 60 credits in language technology/computational linguistics, or (2) 60 credits in computer science, or (3) 60 credits in a language subject, 7.5 credits in computer programming and 7.5 credits in logic/discrete mathematics. Proficiency in English equivalent to the general entry requirements for first-cycle (Bachelor's level) studies.

Learning outcomes

On completion of the course, to earn the grade Pass the student should at least be able to:

1. explain, apply, and assess manual and automatic evaluation methods for machine translation;
2. analyse and critically review scientific publications in the field of machine translation;
3. describe and critically discuss the architecture of machine translation systems;
4. build their own translation model using existing tools for machine translation and evaluate and analyse the translation results;
5. compare different types of machine translation strategies, such as rule-based, statistical, and neural machine translation;
6. implement components of machine translation systems or components used in evaluation or preprocessing.

Content

See the intended learning outcomes.

Instruction

The teaching consists of lectures and laboratory sessions under supervision.

Assessment

Examination takes place through oral and written presentation of assignments. The teacher can, as part of the examination require compulsory attendance and active participation in teaching modulees. Details about the examination are provided at the start of the course.

If there are special reasons for doing so, an examiner may make an exception from the method of assessment indicated and allow a student to be assessed by another method. An example of special reasons might be a certificate regarding special pedagogical support from the University's disability coordinator.