Paper: Toward Multi-Engine Machine Translation

ACL ID H94-1026
Title Toward Multi-Engine Machine Translation
Venue Human Language Technologies
Session Main Conference
Year 1994

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 their (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.