This paper presents collaborative decoding (co-decoding), a new method to improve machine translation accuracy by leveraging translation consensus between multiple machine transla...
Mu Li, Nan Duan, Dongdong Zhang, Chi-Ho Li, Ming Z...
In this paper, with a belief that a language model that embraces a larger context provides better prediction ability, we present two extensions to standard n-gram language models ...
This paper presents a novel online relevant set algorithm for a linearly-scored block sequence translation model. The key component is a new procedure to directly optimize the glob...
In this paper, we propose a linguistically annotated reordering model for BTG-based statistical machine translation. The model incorporates linguistic knowledge to predict orders ...
In this paper, we argue that n-gram language models are not sufficient to address word reordering required for Machine Translation. We propose a new distortion model that can be u...