Text Revision: A Model and Its Implementation

To generate good text, many kinds of decisions should be made. Many researchers have spent much time searching for the architecture that would determine a proper order for these decisions. However, even if such an architecture is found, there are still certain kinds of problems that are difficult to consider during the generation process. Those problems can be more easily detected and solved by introducing a revision process after generation. In this paper, we argue the importance of text revision with respect to natural language generation, and propose a computational model of text revision. We also discuss its implementation issues and describe an experimental Japanese text generation system, WeiveR.

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