Machine Translation

Course Information
TitleΜηχανική Μετάφραση / Machine Translation
CodeΚΕ-ΜΕΤ-05
FacultyPhilosophy
SchoolFrench Language and Literature
Cycle / Level1st / Undergraduate
Teaching PeriodWinter/Spring
CommonYes
StatusActive
Course ID280006442

Class Information
Academic Year2020 – 2021
Class PeriodWinter
Faculty Instructors
Weekly Hours3
Total Hours39
Class ID
600179708
Course Type 2016-2020
  • Scientific Area
  • Skills Development
Mode of Delivery
  • Face to face
Erasmus
The course is also offered to exchange programme students.
Language of Instruction
  • Greek (Instruction)
  • French (Instruction, Examination)
Prerequisites
Required Courses
  • Υ-ΜΕΤ-01 Text Analysis and Production in Greek I
  • Υ-ΜΕΤ-02 Text Analysis and Production in Greek II
  • Υ-ΜΕΤ-03 Comprehension Techniques in Translation I
  • Υ-ΜΕΤ-04 Comprehension Techniques in Translation II
  • Υ-ΜΕΤ-05 General Translation I
  • Υ-ΜΕΤ-06 Introduction to Translation Studies
General Prerequisites
Students should have previously succeeded to all the compulsory courses designated by the School for choosing the translation direction.
Learning Outcomes
The aim of this course is the use of machine translation systems and translation memory systems and the identification of the problems which could arise in machine translation.
General Competences
  • Apply knowledge in practice
  • Retrieve, analyse and synthesise data and information, with the use of necessary technologies
  • Make decisions
  • Work autonomously
  • Work in teams
  • Work in an interdisciplinary team
Course Content (Syllabus)
In this course, students will study machine translation systems and translation memory systems in all steps: conception, development and use.
Keywords
Translation, machine translation, translation memory.
Educational Material Types
  • Video lectures
  • Book
Use of Information and Communication Technologies
Use of ICT
  • Use of ICT in Course Teaching
  • Use of ICT in Laboratory Teaching
  • Use of ICT in Communication with Students
Description
80% of the course is based on computer use.
Course Organization
ActivitiesWorkloadECTSIndividualTeamworkErasmus
Lectures130.5
Laboratory Work261.0
Project863.4
Total1255
Student Assessment
Description
The final grade is the result of the computer assisted assignment (50%) and the oral exams (50%).
Student Assessment methods
  • Written Assignment (Summative)
  • Oral Exams (Summative)
Bibliography
Course Bibliography (Eudoxus)
Kyriacopoulou, T. (2005). Analyse automatique des textes écrits : le cas du grec moderne. University Studio Press.
Additional bibliography for study
Επιστημονικά άρθρα από τη διεθνή βιβλιογραφία.
Last Update
10-07-2019