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We present an alternative method of evaluating Quality Estimation systems,which is based on a linguistically-motivated Test Suite. We create a test-setconsisting of 14 linguistic error categories and we gather for each of them aset of samples with both correct and erroneous translations. Then, we measurethe performance of 5 Quality Estimation systems by checking their ability todistinguish between the correct and the erroneous translations. The detailedresults are much more informative about the ability of each system. The factthat different Quality Estimation systems perform differently at variousphenomena confirms the usefulness of the Test Suite.

Fine-grained evaluation of Quality Estimation for Machine translation based on a linguistically-motivated Test Suite