Singapore University of Social Sciences

Computer-Assisted Translation

Computer-Assisted Translation (TNT503)

Applications Open: To be confirmed

Applications Close: To be confirmed

Next Available Intake: To be confirmed

Course Types: To be confirmed

Language: English

Duration: 6 months

Fees: To be confirmed

Area of Interest: Linguistics and Languages

Schemes: To be confirmed

Funding: To be confirmed

School/Department: School of Humanities & Behavioural Sciences


Synopsis

TNT503 Computer-Assisted Translation provides a comprehensive analysis of the development of translation technology that has revolutionised the field of translation and interpretation. Students will explore the increasing interdependency between translation and technology, tackling issues arising from human-machine interaction. Differences between Machine-Aided Human Translation and Human-Aided Machine Translation will be discussed. Students will learn to use different types of computer-assisted translation (CAT) technologies: translation memory, translation management system, terminology extraction and management, parallel corpora, text scanner, speech recognition and synthesis technology, etc. Software or tools that are commonly used in the language service industry will be made available to students. At the end of the course, students will carry out a mini-project to evaluate various tools and select an approach that offers the best solution to a real-life multilingual problem.

Level: 5
Credit Units: 5
Presentation Pattern: Every January
E-Learning: BLENDED - Learning is done MAINLY online using interactive study materials in Canvas. Students receive guidance and support from online instructors via discussion forums and emails. This is supplemented with SOME face-to-face sessions. If the course has an exam component, This will be administered on-campus.

Topics

  • Introduction to translation technology
  • Machine-aided human translation vs human-aided machine translation
  • Translation memory
  • Terminology extraction and management
  • Translation management system
  • Cloud-based project management

Learning Outcome

  • Categorise different types of translation technology
  • Compare human-aided machine translation with machine-aided human translation
  • Combine different technologies to solve real-life problems
  • Appraise CAT tools and platform
  • Formulate a technological solution to a multilingual project
  • Propose quality assessment framework to ensure the quality of the CAT output
  • Improve the current strategy for better outcome
Back to top
Back to top