Evaluating RBMT output for -ing forms: A study of four tar-get languages

Nora Aranberri-Monasterio, Sharon O‘Brien

Abstract


-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.

Keywords


Machine Translation; -ing words; controlled language; post-editing source text; automatic evaluation metrics; Machine Translation evaluation correlations; IT domain; commercial machine translation; RBMT

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