Divergences in the Usage of Discourse Markers in English and Mandarin Chinese

Statistical machine translation (SMT) has, in recent years, improved the accuracy of automated translations. However, SMT systems often fail to deliver human quality translations especially with complex sentences and distant language pairs. Current SMT systems often focus on translating single sentences with clauses being treated in isolation, leading to a loss of contextual information. Discourse markers (DMs) are vital contextual links between discourse segments and this paper examines the divergences in their usage across English and Mandarin Chinese. We highlight important structural differences in composite sentences extracted from a number of parallel corpora, and show examples of how these cases are dealt with by popular SMT systems. Numerous significant divergences, such as contextual omissions, were observed, which can lead to incoherent automatic translations. Our objective is to use these findings to guide a framework proposal to address divergences in DM usage in order to improve SMT output quality.