Collaboration between Machine Translation and Human Translation for Higher Quality and More Production in Translation

The present study aims at creating a level of collaboration between MT and HT in order to obtain more production in translation projects and save time, money and effort for translators, businessmen and any other non-specialist MT users. This can be carried out by applying both pre-editing and post-editing on the ST before entering to MT, in a specific way. Hence, the present study is based on approaching the techniques in which MT runs and to what extent we can make it more effective and more productive. MT users should understand that MT includes two types; direct and indirect. Direct type works on the word level while indirect types work on higher levels (i.e. phrase, sentence levels). On the other hand, indirect levels are divided into two approaches; transfer approach which is language -dependent and interlingua approach which is non-linguistic specific. Indirect approaches are capable of translating better than direct approach. A MT user should pay heed to the fact that these approaches run better because they are based on ST analysis and then TT generation. In order to benefit more from MT, facilitate translation process, and make the TT seem as natural as possible, each MT user should pay heed to the fact that the more he simplifies the analysis process, the more he gets more natural translation. A MT user can achieve this simplicity in the analysis process by means of pre-editing ST before submitting it to MT. In fact, pre-editing cannot be performed randomly. Hence, the present study encourages MT users to use the rules of controlling language to simplify and adjust STs according to their business requirements. This, in turn, alleviates the load on post-editing because the ST to be entered to MT becomes easy enough to be understood by MT.