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 shows the best performance in combining outputs from multiple machine translation (MT) systems. However, overcoming different word orders prese...
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...
Currently there are several approaches to machine translation (MT) based on different paradigms; e.g., phrasal, hierarchical and syntax-based. These three approaches yield similar...
Antti-Veikko I. Rosti, Necip Fazil Ayan, Bing Xian...
Given a number of machine translations of a source segment, the goal of system combination is to produce a new translation that has better quality than all of them. This paper des...