We present a machine learning approach to evaluating the wellformedness of output of a machine translation system, using classifiers that learn to distinguish human reference tran...
Simon Corston-Oliver, Michael Gamon, Chris Brocket...
The need for automated text evaluation is common to several AI disciplines. In this work, we explore the use of Machine Translation (MT) evaluation metrics for Textual Case Based R...
Ibrahim Adeyanju, Nirmalie Wiratunga, Robert Lothi...
This paper advocates a complementary measure of translation performance that focuses on the constrastive ability of two or more systems or system versions to adequately translate ...
Many automatic evaluation metrics for machine translation (MT) rely on making comparisons to human translations, a resource that may not always be available. We present a method f...
In this paper, we t)resent and compare various alignnmnt models for statistical machine translation. We propose to measure tile quality of an aligmnent model using the quality of ...