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Evaluating RBMT output for -ing forms: A study of four tar-get languages
Author(s) -
Nora Aranberri-Monasterio,
Sharon O’Brien
Publication year - 2021
Publication title -
linguistica antverpiensia new series – themes in translation studies
Language(s) - English
Resource type - Journals
ISSN - 2295-5739
DOI - 10.52034/lanstts.v8i.247
Subject(s) - computer science , natural language processing , focus (optics) , artificial intelligence , domain (mathematical analysis) , mathematics , mathematical analysis , physics , optics
-ing forms in English are reported to be problematic for Machine Transla-tion and are often the focus of rules in Controlled Language rule sets. We investigated how problematic -ing forms are for an RBMT system, translat-ing into four target languages in the IT domain. Constituent-based human evaluation was used and the results showed that, in general, -ing forms do not deserve their bad reputation. A comparison with the results of five automated MT evaluation metrics showed promising correlations. Some issues prevail, however, and can vary from target language to target lan-guage. We propose different strategies for dealing with these problems, such as Controlled Language rules, semi-automatic post-editing, source text tagging and “post-editing” the source text.

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