An Enhanced Model for Lexical Gap Processing in English-Vietnamese Machine Translation

Lexical gap is a non-trivial problem in English-Vietnamese Machine translation. The gap occurs when a word in source language does not have any equivalent word in target language. Recently, some studies have found that well-processing method can improve quality of machine translation such as a model for word-to-phrase translation. However, there are still cases that the word -- to -- phrase model cannot pick a correct phrase to build target sentence. This study establishes a model, based on word -- to -- phrase translation model, which enhances quality of machine translation using Vietnamese Lexical Functional Grammar (VLFG) rule set for Vietnamese noun phrase in reconstruction algorithm.