Achieving high translation quality remains the most daunting challenge Machine Translation (MT) systems currently face. Researchers have explored a variety of methods for including translator feedback in the MT loop. However, most MT systems have failed to incorporate post-editing efforts beyond the addition of corrected translations to the parallel training data for Example-Based and Statistical systems or to a translation memory database. This book describes a novel approach that utilizes post-editing information to automatically improve the underlying rules and lexical entries of a...