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...
Translating between dissimilar languages requires an account of the use of divergent word orders when expressing the same semantic content. Reordering poses a serious problem for s...
BLEU is the de facto standard for evaluation and development of statistical machine translation systems. We describe three real-world situations involving comparisons between diff...
David Chiang, Steve DeNeefe, Yee Seng Chan, Hwee T...
Recent work in the field of machine translation (MT) evaluation suggests that sentence level evaluation based on machine learning (ML) can outperform the standard metrics such as B...
Antoine Veillard, Elvina Melissa, Cassandra Theodo...
In this paper, we present ParaEval, an automatic evaluation framework that uses paraphrases to improve the quality of machine translation evaluations. Previous work has focused on...