TRAM511 Introduction to Artificial Intelligence for Translators and Interpreters

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

• A thorough understanding of the basic and intermediate concepts from artificial intelligence and machine learning
• The ability to analyse and implement AI-based solutions for problems from the field of translation and interpretation
• Intermediate knowledge of how to use LLMS and prompts
• The ability to communicate solutions in writing using the required conventions of the field.

• Introduction to artificial intelligence (AI) and natural language processing (NLP)
• Introduction to large language models and prompting techniques
• Examples of how to use AI and NLP in tasks related to translation and interpreting
• Hands-on exercise on how to tune an automatic speech engine
• Automatic processing of multilingual texts.

The learning and teaching strategy is designed to provide students with problem-solving skills and a good understanding of artificial intelligence with emphasis on how it can be used to tackle problems from translation. By the end of the module, students will feel confident of their ability to use AI-based tools that allow them to accomplish useful goals related to translation and interpreting technologies. This is in line with our masters programmes overall aims of enhancing students' background in technologies for translation and interpreting, as well as enhancing their employability and resourcefulness and resilience.

The learning and teaching methods include:

• Seminars and workshops will be interspersed with opportunities for group and whole class discussions
• Contact hours will be complemented with materials and activities for guided study posted on SurreyLearn
• Self-study.

Portfolio of Solutions to the Exercise and Reflective Comments on the Solutions (60%)

Students will be given homework every two weeks and will be asked to prepare a portfolio with their answers to the homework. In some cases, students will be asked to write "small essays" (200 - 250 words) explaining how they used some tools, whilst in other cases they will need to provide a short explanation of on a topic related to the ones discussed in the class. The portfolios can be seen as a diary of the practical activities covered in this module. The solutions are expected to indicate any problems that the students encountered and how they solved them. In order to pass, the students will have to submit all the homework. For the homework given in the first eight weeks, the solutions will be discussed in class and the students will have the chance to update their portfolios 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 and the marking will focus on both how the solution was achieved and on the reflective analysis. The portfolios will be due at the end of the semester.

Short essay (1000-1200) on a topic given in the class (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.

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