Towards Readability-Controlled Machine Translation of COVID-19 Texts
Jun 1, 2022·
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0 min read
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Fernando Alva-Manchego
Matthew Shardlow
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
EAMT 2022