Paper: Multi-Engine Machine Translation Guided By Explicit Word Matching

ACL ID P05-3026
Title Multi-Engine Machine Translation Guided By Explicit Word Matching
Venue Annual Meeting of the Association of Computational Linguistics
Session System Demonstration
Year 2005
Authors

We describe a new approach for syntheti- cally combining the output of several dif- ferent Machine Translation (MT) engines operating on the same input. The goal is to produce a synthetic combination that surpasses all of the original systems in translation quality. Our approach uses the individual MT engines as “black boxes” and does not require any explicit coopera- tion from the original MT systems. A de- coding algorithm uses explicit word matches, in conjunction with confidence estimates for the various engines and a tri- gram language model in order to score and rank a collection of sentence hypothe- ses that are synthetic combinations of words from the various original engines. The highest scoring sentence hypothesis is selected as the final output of our sys- tem. Experiments, ...