Recent research has shown that a balanced harmonic mean (F1 measure) of unigram precision and recall outperforms the widely used BLEU and NIST metrics for Machine Translation evalu...
Automatic evaluation of Machine Translation (MT) quality is essential to developing highquality MT systems. Various evaluation metrics have been proposed, and BLEU is now used as ...
Hideki Isozaki, Tsutomu Hirao, Kevin Duh, Katsuhit...
Recently system combination has been shown to be an effective way to improve translation quality over single machine translation systems. In this paper, we present a simple and ef...
Minimum-error-rate training (MERT) is a bottleneck for current development in statistical machine translation because it is limited in the number of weights it can reliably optimi...
In this paper we describe recent improvements to components and methods used in our statistical machine translation system for ChineseEnglish used in the January 2008 GALE evaluat...
Almut Silja Hildebrand, Kay Rottmann, Mohamed Noam...