This paper presents a machine learning approach to the study of translationese. The goal is to train a computer system to distinguish between translated and non-translated text, in...
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...
Phrase level translation models are effective in improving translation quality by addressing the problem of local re-ordering across language boundaries. Methods that attempt to f...
The POSSLT 1 is a Korean to English spoken language translation (SLT) system. Like most other SLT systems, automatic speech recognition (ASR), machine translation (MT), and text-t...
Selecting the right word translation among several options in the lexicon is a core problem for machine translation. We present a novel approach to this problem that can be traine...