I currently teach modules at masters level focused on how technology impacts the work of translators and interpreters. When I was teaching on a masters in computational linguistics, I was involved in the delivery of modules related to Natural Language Processing (NLP) like Python programming for linguists, Machine learning for NLP and introductory modules on computational linguistics. I also contribute sometimes on a research methods module.
Modules taught this academic year
- TRAM500: Introduction to computational thinking for translators (module leader)
- The purpose of this module is to enable students to acquire basic and intermediate concepts of computer science and programming, and to learn how to apply them to problems related to translation-related tasks such as glossary creation, error analysis, automatic substitution. The programming language used in the class is Python.
- TRAM502: Smart technologies for translators (module leader)
- The module explores the main theoretical and practical aspects of smart technologies for translation, with emphasis on how to use methods from Natural Language Processing and Corpus Linguistics to help translators. The purpose of this module is to enable students to understand the challenges faced when using computers to process text automatically or when they need to process speech as an input.
- TRAM449: Interpreting and technologies
- This module introduces students to the principles and practical implications of using technologies in the interpreting profession. In this module, I contributed with lectures on machine translation and speech to speech translation.
- TRAM495: Principles and challenges of translation and interpreting
- This module provides students with a systematic framework for understanding the key concepts in Translation and Interpreting Studies and how they relate and apply to everyday professional practice. In this module, I contributed with lectures on human-computer interaction for translators and interpreters and quality in translation.