Program Overview

TRAM502 Smart Technologies for Translation

Key Information

• Start date: 02 February 2026
• Attendance dates: 3 February 2025 to 6 June 2025
• Location: Stag Hill campus, University of Surrey, Guildford, Surrey GU2 7XH

Overview

The TRAM502 Smart Technologies for Translation module explores the main theoretical and practical aspects of smart technologies for translation. It emphasizes how the latest developments in natural language processing, large language models, and corpus linguistics can aid translators. The module aims to enable students to understand the challenges faced when using computers and artificial intelligence to process text automatically or when processing speech as input. The focus is on enhancing students' digital capabilities, especially those linked to the translation industry.

Learning Outcomes

By the end of the module, students will be able to demonstrate:

• An in-depth knowledge base of specific topics within the area of smart technologies for translation
• Practical skills in using a wide variety of state-of-the-art tools and resources relevant to NLP, CL, and MT
• A critical understanding of the published literature and current debates in these areas
• Ability to communicate findings in writing
• Understanding of new societal, technological, and language-industry demands

Course Content

• Introduction to natural language processing and machine translation
• Using large language models like ChatGPT to solve translation-related problems
• Existing paradigms in machine translation, how to train a machine translation engine, and how to evaluate machine translation
• Building corpora from the web using data scraping and cleaning of files
• Building parallel corpora and automatic alignment of corpora
• Terminology extraction

Learning and Teaching Methods

The learning and teaching strategy is designed to provide students with a good understanding of the practical aspects of using natural language processing and corpus linguistics in translation workflows towards a smarter use of technologies in translation. This includes:

• Workshops with opportunities for group and whole-class discussions
• Captured content addressing module content
• Guided learning such as signposted hands-on exercises and guidelines relevant to advanced practice in the field
• Problem-based practical exercises
• Discussion and group work (in-class)
• Practice-based learning application of knowledge acquired throughout the module in realistic or academically simulated contexts

Assessment

Essay (40%)

Students will submit an essay on one of the more theoretical topics covered in the first half of the semester.

Portfolio of Solutions (60%)

Students will be given practical homework every two weeks and will prepare a portfolio with their answers. The portfolio will include solutions to homework, reflective analysis, and discussions of practical topics.

Course Leader

Professor Constantin Orasan

Professor of Language and Translation Technologies

Entry Requirements

1. Fluency in English, as students will be required to process texts and discuss practice and/or concepts in detail.
2. A first degree.

Fees and Funding

• Price per person: Ł800
• A 25% discount is available for CTS graduates or for applicants who have previously done a CTS CPD course.