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, ...
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...
Recently, confusion network decoding has been applied in machine translation system combination. Due to errors in the hypothesis alignment, decoding may result in ungrammatical co...
Antti-Veikko I. Rosti, Spyridon Matsoukas, Richard...
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,...
Recently confusion network decoding shows the best performance in combining outputs from multiple machine translation (MT) systems. However, overcoming different word orders prese...