Course Code: CTI215

Synopsis

CTI215 equips students with the knowledge and skills required to effectively use AI for translation in specialised fields. The course introduces basic principles and concepts related to AI and machine learning in the context of translation. Students will learn to evaluate AI-powered translation tools and integrate them into a Computer-Aided Translation (CAT) environment to improve quality and productivity in translation. Industry-based rubrics and metrics will be used to assess and estimate the quality of AI translation. Machine translation post-editing (MTPE) and terminology management (TM) will be a focus of the course. Students will apply MTPE and TM strategies to specialised translation in domains such as law, medicine, science and technology, and sustainability. Challenges specific to each of these domains and strategies to tackle the challenges will be discussed. Ethical implications such as confidentiality, intellectual property and data security will also be addressed. At the end of the course, students will work on a domain-specific translation project using AI-powered tools to gain practical experience.
Level: 2
Credit Units: 5
Presentation Pattern: EVERY JULY

Topics

  • Fundamental Concepts of AI and Specialised Translation
  • AI-Powered Translation Tools
  • Ethical Issues in AI-Powered Translation
  • Editing for Machine Translation
  • Translation Quality
  • Terminology Management-Core concepts
  • Terminography and AI
  • Overview of Law and Legal Texts
  • Tackling Legal Translation with AI
  • Technical Communication
  • Translating Scientific and Technical Texts With AI
  • Medical Communication
  • Pharmaceutical Translation
  • Translation of Traditional Chinese Medicine (TCM)

Learning Outcome

  • Discuss core concepts in AI-powered translation technology
  • Describe challenges and strategies in specialised translation
  • Demonstrate an understanding of ethical issues related to AI translation
  • Distinguish AI-powered translation tools and platforms
  • Use rubrics and metrics to evaluate and estimate the quality of AI translation 2.
  • Practise machine translation post-editing and terminology management skills in specialised fields