Paper: A Model Of Competence For Corpus-Based Machine Translation

ACL ID C00-2145
Title A Model Of Competence For Corpus-Based Machine Translation
Venue International Conference on Computational Linguistics
Session Main Conference
Year 2000
Authors

In this paper I claborate a model of colnpetencc for corpus-based machine translation (CBMT) along the lines of the representations used in the transla- tion system. Representations in CBMT-systems can be rich or austere, molecular or holistic and they can be fine-grained or coarse-grained. The paper shows that different CBMT architectures are required de- pendent on whether a better translation quality or a broader coverage is preferred according to Boitct (1999)'s formula: "Coverage * Quality = K".