Singapore University of Social Sciences

Human and Machine Translation Quality Assessment

Human and Machine Translation Quality Assessment (TNT501)

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

TNT501 Human and Machine Translation Quality Assessment provides students with a comprehensive view of different models and tools that can be used to evaluate the quality of translation done by human and machine. Students will explore existing translation quality assessment frameworks set out by professional bodies in the world. Taking into consideration socio-cultural and situational contexts, students will select relevant models and tools to evaluate human and machine translation output of different genres, registers, media and purposes. Through practice, students will gain insights into differences between human translation and machine translation in terms of quality. Such insights will enable students to recommend a quality assessment strategy appropriate to a specific project. At the end of the course, students will be able to construct models of translation quality assessment with objectivity, validity and inter-rater reliability.

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

  • Translation theory and quality assessment
  • Fundamental concepts in translation quality assessment
  • Overview of language service industry
  • Approaches to human translation quality assessment
  • Approaches to machine translation quality assessment
  • Machine Translation Post-Editing (MTPE) quality assessment

Learning Outcome

  • Critique models of translation quality assessment
  • Compare human translation with machine translation
  • Set up linguistic, cultural and technical framework for translation quality assessment
  • Formulate strategies to evaluate human and machine translation
  • Construct models of translation quality assessment specific to different contexts
  • Appraise the effectiveness of the quality assessment models
  • Improve the translation quality assessment models
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