tailieunhanh - Báo cáo khoa học: "Mapping Scrambled Korean Sentences into English Using Synchronous TAGs"

Synchronous Tree Adjoining Grammars can be used for Machine Translation. However, translating a free order language such as Korean to English is complicated. I present a mechanism to translate scrambled Korean sentences into English by combining the concepts of Multi-Component TAGs (MC-TAGs) and Synchronous TAGs (STAGs). | Mapping Scrambled Korean Sentences into English Using Synchronous TAGs Hyun s. Park Computer Laboratory University of Cambridge Cambridge CB2 3QG . Abstract Synchronous Tree Adjoining Grammars can be used for Machine Translation. However translating a free order language such as Korean to English is complicated. I present a mechanism to translate scrambled Korean sentences into English by combining the concepts of Multi-Component TAGs MC-TAGs and Synchronous TAGs STAGs . 1 Motivation Tree Adjoining Grammars TAGs were first developed by Joshi Levy and Takahashi Joshi et al. 1975 . There are other variants of TAGs such as STAGs Shieber and Schabes 1990 and MC-TAGs Weir 1988 . STAGs in particular can be used for machine translation and were applied to Korean-English machine translation in a military message domain Palmer et al. 1995 . Park Park 1995 suggested a way of handling Korean scrambling using MC-TAGs together with a priority concept. However as scrambled argument structures in Korean were represented as sets using MC-TAGs a mechanism to combine MC-TAGs and STAGs was necessary to translate Korean scrambled sentences into English. 2 Korean-English Machine Translation Using STAGs STAGs are a variant of TAGs introduced to characterize correspondences between tree adjoining languages. They can be used to relate TAGs for two different languages for machine translation Abeillé et al. 1990 . The translation process consists of three steps. The source sentence is parsed according to the source grammar. Each elementary tree in the derivation is considered with the features given from the derivation through unification. Second the source derivation tree is transferred to a target derivation. This step maps each elementary tree in the source derivation tree to a tree in the target derivation tree by looking in the transfer lexicon. And finally the target sentence is generated from the target derivation tree obtained in the previous step. The .