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  5. Linguistics and Tools for Translation

Linguistics and Tools for Translation

Objectives

Development of key competences for applying linguistic knowledge in current translation practices, understanding the importance of linguistic knowledge in professional practice and in the development of studies and innovation in the fields of Linguistics and Translation. In particular, students should be able to:
a) recognize and assess current translation work contexts and their scientific and technological requirements;
b) know and handle machine translation and computer-assisted translation systems;
c) acquire skills in analyzing and solving linguistic problems.

General characterization

Code

01107260

Credits

6.0

Responsible teacher

Raquel Fonseca Amaro

Hours

Weekly - 4

Total - 168

Teaching language

Portuguese

Prerequisites

N/A

Bibliography

  • do Campo, María & Sánchez-Gijón, Pilar. (2024). Evaluating NMT using the non-inferiority principle. Natural Language Processing. 1-20. 10.1017/nlp.2024.4.
  • Carl, M. & Toledo Báez, M. C. (2019) MT errors and the translation process: a study across different languages. The Journal of Specialised Translation 31, 107-132.
  • Carmo, F. et al. (2021) A review of the state-of-the-art in automatic post-editing. Machine Translation 35, 101–143.
  • Comparin, L., & Mendes, S. (2017). Error detection and error correction for improving quality in MT. International Journal of Computer Applications.
  • Huertas Barros, E. et al. (eds.) (2019) Quality assurance and assessment practices in translation and interpreting. Advances in linguistics and communication studies series. IGI Global.
  • Naveen, P., Trojovský, P. (2024). Overview and challenges of machine translation for contextually appropriate translations, iScience 27: 10, ISSN 2589-0042,https://doi.org/10.1016/j.isci.2024.110878

Teaching method

Theoretical and practical classes and tutorial guidance, using case studies and practical application of acquired knowledge, including: (i) presentation and explanation of contents; (ii) use of machine translation systems and computer-assisted translation systems, including terminology management systems; (iii) strategic reflection on the usefulness and applicability of these types of technologies in different contexts; (iii) analysis of results and error resolution; (iv) practical work on input control, data management and output improvement.

Evaluation method

Continuous assessment - Continuous assessment, including Individual and Collective essays (50%), Written test (50%)

Subject matter

1. Linguistic knowledge and translation techniques and technologies
1.1 Individual translation and network translation: features and specificities
1.2 Use of machine translation, computer-aided translation and hybrid processes
1.3 Skills of the modern translator
2. Machine translation
2.1 Analysis and types of errors
2.2 Pre and post-editing
3. Computer-aided translation
3.1 Translation memories and linguistic data management
3.2 Terminology management
3.3. Terminology Databases
4. Analysis and improvement of translation processes
4.1 Controlled Languages
4.2 Problem identification, explanation and resolution