We present a hierarchical phrase-based statistical machine translation in which a target sentence is efficiently generated in left-to-right order. The model is a class of synchron...
This paper proposes a learning method of translation rules from parallel corpora. This method applies the maximum entropy principle to a probabilistic model of translation rules. ...
In hierarchical phrase-based SMT systems, statistical models are integrated to guide the hierarchical rule selection for better translation performance. Previous work mainly focus...
Lei Cui, Dongdong Zhang, Mu Li, Ming Zhou, Tiejun ...
We devised a novel statistical technique for the identification of the translation equivalents of source words obtained by transformation rule based translation (TRT). The effecti...
Ari Pirkola, Jarmo Toivonen, Heikki Keskustalo, Ka...
The tree sequence based translation model allows the violation of syntactic boundaries in a rule to capture non-syntactic phrases, where a tree sequence is a contiguous sequence o...