%0 Conference Proceedings %T Evaluation of Domain Adaptation Techniques for TRANSLI in a Real-World Environment %A Farzindar, Atefeh %A Khreich, Wael %S Proceedings of the 10th Conference of the Association for Machine Translation in the Americas: Commercial MT User Program %D 2012 %8 oct 28 nov 1 %I Association for Machine Translation in the Americas %C San Diego, California, USA %F farzindar-khreich-2012-evaluation %X Statistical Machine Translation (SMT) systems specialized for one domain often perform poorly when applied to other domains. Domain adaptation techniques allow SMT models trained from a source domain with abundant data to accommodate different target domains with limited data. This paper evaluates the performance of two adaptive techniques based on log-linear and mixture models on data from the legal domain in real-world settings. Performance evaluation includes post-editing time and effort required by a professional post-editor to improve the quality of machine-generated translations to meet industry standards, as well as traditional automated scoring techniques (BLEU scores). Results indicates that the domain adaptation techniques can yield a significant increase in BLEU score (up to three points) and a significant reduction in post-editing time of about one second per word in an operational environment. %U https://aclanthology.org/2012.amta-commercial.6