Comma Analysis and Processing for Improving Translation Quality of Long Sentences in Rule-based English-Korean Machine Translation

Current English-Korean machine translation system cannot provide practical translation quality mainly due to the difficulties in long sentence parsing. Long sentences generally include commas, resulting in lots of different possible sentence structures. It is very difficult to accurately parse the long sentences that have commas. The roles of the commas in constructing sentences have to be identified and then the syntactic analysis should be performed according to the roles of the commas for accurate parsing of the long sentences. This paper presents the analysis results of the comma usages and the comma processing methods for each comma usage. And it also proposes the comma usage classification method using machine learning technique. In experiment, some improved translation results, by identifying comma usage and processing the commas, are also presented.