TRAM502 Smart Technologies for Translation
Key information
- Start date:
- 03 February 2025
- Attendance dates:
- 3 February 2025 to 6 June 2025
- Venue:
- Stag Hill campus, University of Surrey, Guildford, Surrey GU2 7XH
- Contact details:
- Email: cts@surrey.ac.uk
Overview
Students taking this module explore the main theoretical and practical aspects of smart technologies for translation, with emphasis on how the latest developments in Natural Language Processing, Large Language Models (e.g. ChatGPT) and Corpus Linguistics can to help translators. The purpose of this module is to enable students to understand the challenges faced when using computers artificial intelligence to process text automatically or when they need to process speech as an input. The focus is on enhancing students’ digital capabilities, especially those linked to the translation industry. The module will provide students with knowledge about the fields of Machine Translation (MT), Natural Language Processing (NLP), Large Language Models (LLMs) and Corpus Linguistics (CL).
The module will start with an introduction to NLP and machine translation and will present different paradigms to produce automatic translations. Students will be provided with hands-on experience on how to train translation engines, and how it is possible to evaluate MT, as well as how to use LLMs for translation related tasks. . Other topics such as terminology extraction, speech recognition and translation will also be covered. The students will learn how to harvest relevant corpora from the web, clean them and use them for translation-related tasks.The practical tasks addressed in the module will improve students’ problem-solving skills and contribute to their future career development.
Knowledge of programming will not be necessary, but students who have a programming background will be given the opportunity to use this knowledge in the module.
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
- Demonstrate practical skills in using a wide variety of state-of-the-art tools and resources relevant to NLP, CL, and MT
- Demonstrate a critical understanding of the published literature and current debates in these areas
- Demonstrate ability to communicate findings in writing
- Appreciate new societal, technological and language-industry demands
Course content
- Introduction to Natural Language Processing (NLP) and Machine Translation (MT)
- Using Large Language Models like ChatGPT to solve translation related problems
- Existing paradigms in MT, how to train an MT engine and how to evaluate MT
- 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 NLP and CL in translation workflows towards a smarter use of technologies in translation. This is in line with the MA in Translation’s overall aims of enhancing students’ background in technologies for translation.
Learning and teaching 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
An Essay on a Given Topic (1,000 - 1,200 words) (40%)
Students will have to submit an essay on one of the more theoretical topics covered in the first half of the semester. The essay will be due at the middle of the semester.
Portfolio of Solutions to the Weekly Homework (60%)
Students will be given practical homework every two weeks and will be asked to prepare a portfolio with their answers. In some cases, students will be asked to write "small essays" (250-300 words) discussing a practical topic, whilst in other cases they will need to explain their experience using a smart technology. The portfolio can be seen as diary of the practical activities covered in this module and it is expected to indicate any problems that the students encountered and how they solved them. Part of the workshops will be used to discuss the solution for the homework given in the first half of the module. After these discussions, students will be asked to update their portfolio with reflective analysis of their initial solutions. All the pieces of homework given during the semester will have to be included in the final portfolio, which will be due at the end of the semester. The marking will focus both on the answers to the homework and on the reflective analysis.
Course leader
![Constantin Orasan profile image](/sites/default/files/styles/image_150x150_scale_and_crop/public/2020-03/constantin-orasan.jpg?itok=bSdZ22gq)
Professor Constantin Orasan
Professor of Language and Translation Technologies
Reading list
Entry requirements
- You need to be fluent in English as you will be required to process texts and discuss practice and/or concepts in detail (IELTS level of 6.5 overall, or equivalent)
- You should have a first degree
Fees and funding
Price per person:
£800
A 25% discount is available for CTS graduates or for applicants who have previously done a CTS CPD course.
How to apply
Apply online below where you will be asked to upload your CV, academic and language qualifications and respond to a few brief questions about yourself.
Terms and conditions
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Further details of our terms and conditions will follow.
Disclaimer
This online prospectus has been prepared and published in advance of the commencement of the course. The University of Surrey has used its reasonable efforts to ensure that the information is accurate at the time of publishing, but changes (for example to course content or additional costs) may occur given the interval between publishing and commencement of the course. It is therefore very important to check this website for any updates before you apply for a course with us. Read the full disclaimer.
Course location and contact details
Campus location
Stag HillStag Hill is the University's main campus and where the majority of our courses are taught.
- Email: cts@surrey.ac.uk
University of Surrey
Guildford
Surrey GU2 7XH