Abstract
This project investigates the capabilities of Machine Translation models for generating translations at varying levels of readability, focusing on texts related to COVID-19. Whilst it is possible to automatically translate this information, the resulting text may contain specialised terminology, or may be written in a style that is difficult for lay readers to understand. So far, we have collected a new dataset with manual simplifications for English and Spanish sentences in the TICO-19 dataset, as well as implemented baseline pipelines combining Machine Translation and Text Simplification models.
Type
Publication
Proceedings of the 23rd Annual Conference of the European Association for Machine Translation
Fernando Alva-Manchego
Lecturer
My research interests include text adaptation, evaluation of natural language generation, and NLP for education.