Current phrase-based SMT systems perform poorly when using small training sets. This is a consequence of unreliable translation estimates and low coverage over source and target p...
System combination has emerged as a powerful method for machine translation (MT). This paper pursues a joint optimization strategy for combining outputs from multiple MT systems, ...
We present a framework where auxiliary MT systems are used to provide lexical predictions to a main SMT system. In this work, predictions are obtained by means of pivoting via aux...
This paper presents a new hypothesis alignment method for combining outputs of multiple machine translation (MT) systems. An indirect hidden Markov model (IHMM) is proposed to add...
Xiaodong He, Mei Yang, Jianfeng Gao, Patrick Nguye...
Given several systems' automatic translations of the same sentence, we show how to combine them into a confusion network, whose various paths represent composite translations...
Damianos Karakos, Jason Eisner, Sanjeev Khudanpur,...