We proposed a method of machine translation using inductive learning with genetic algorithms, and confirmed the effectiveness of applying genetic algorithms. However, the system b...
In this paper we report our recent development of an end-to-end integrative design methodology for speech translation. Specifically, a novel decision function is proposed based o...
We present a comparative evaluation of two data-driven models used in translation selection of English-Korean machine translation. Latent semantic analysis(LSA) and probabilistic ...
We propose a distance phrase reordering model (DPR) for statistical machine translation (SMT), where the aim is to capture phrase reorderings using a structure learning framework....
In recent years, corpus based approaches to machine translation have become predominant, with Statistical Machine Translation (SMT) being the most actively progressing area. Succe...