Machine translation (MT) systems do not currently achieve optimal quality translation on free text, whatever translation method they employ. Our hypothesis is that the quality of MT will improve if an MT environment uses output from a variety of MT systems working on the same text. In the latest version of the Pangloss MT project, we collect the results of three translation engines --typically, subsentential chunks --in a chart data structure. Since the individual MT systems operate completely independently, their results may be incomplete, conflicting, or redundant. We use simple scoring heuristics to estimate the quality of each chunk, and find the highest-score sequence of chunks (the "best cover"). This paper describes in detail the combining method, presenting the algorithm and illustrations of its progress on one of many actual translations it has produced. It uses dynamic programming to efficiently compare weighted averages of sets of adjacent scored component translations. The current system operates primarily in a human-aided MT mode. The translation delivery system and its associated post-editing aide are briefly described, as is an initial evaluation of the usefulness of this method. Individual M T engines will be reported separately and are not, therefore, described in detail here.
Current MT systems, whatever translation method they at present employ, do not reach an optimum output on free text. Our hypothesis 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 improve. 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) results 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.
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