Paper: Context-Dependent SMT Model Using Bilingual Verb-Noun Collocation

ACL ID P05-1068
Title Context-Dependent SMT Model Using Bilingual Verb-Noun Collocation
Venue Annual Meeting of the Association of Computational Linguistics
Session Main Conference
Year 2005

In this paper, we propose a new context- dependent SMT model that is tightly cou- pled with a language model. It is de- signed to decrease the translation ambi- guities and efficiently search for an opti- mal hypothesis by reducing the hypothe- sis search space. It works through recipro- cal incorporation between source and tar- get context: a source word is determined by the context of previous and correspond- ing target words and the next target word is predicted by the pair consisting of the previous target word and its correspond- ing source word. In order to alleviate the data sparseness in chunk-based trans- lation, we take a stepwise back-off trans- lation strategy. Moreover, in order to ob- tain more semantically plausible transla- tion results, we use bilingual verb-noun collocati...