Towards Readability-Controlled Machine Translation of COVID-19 Texts


This project investigates the capabilities of machine translation (MT) models for generating translations at varying levels of readability, focusing on texts about COVID-19. Funded by the European Association for Machine Translation and by the Centre for Advanced Computational Sciences at Manchester Metropolitan University, we collected manual simplifications for English and Spanish texts in the TICO-19 dataset, and assessed the performance of neural MT models in this new benchmark. Future work will implement models that jointly translate and simplify, and develop suitable evaluation metrics.

EAMT 2022
Fernando Alva-Manchego
Fernando Alva-Manchego

My research interests include text simplification, readability assessment, evaluation of natural language generation, and writing assistance.