Assessing The Comprehensibility of Automatic Translations

Start date
Jan. 1, 2017
End date
Dec. 31, 2020
Sponsor
FWO

About ArisToCAT

Machine translation systems cannot guarantee that the text they produce will be fluent and coherent in both syntax and semantics. Erroneous words and syntax occur frequently in machine-translated text, leaving the reader to guess parts of the intended message.

This project (i) analyzes eye movement data to investigate to what extent the lack of predictability in texts that were created by MT impairs comprehension, and (ii) tries to automatically estimate the comprehensibility of machine-translated text.