Toward Multi-engine Machine Translation

Current MT systems, whatever translation method they at present employ, do not reach an optimum output on free text. Our hy-pothesis for the experiment reported in this paper is that if an MT environment can use the best results from a variety of MT systems working simultaneously on the same text, the overallquality will im-prove. Using this novel approach to MT in the latest version of the Pangloss MT project, we submit an input text to a battery of machine translation systems (engines), coLlect heir (possibly, incomplete) re-sults in a joint chaR-like data structure and select the overall best translation using a set of simple heuristics. This paper describes the simple mechanism we use for combining the findings of the various translation engines. 1