Paper: A Simple Domain-Independent Probabilistic Approach to Generation

ACL ID D10-1049
Title A Simple Domain-Independent Probabilistic Approach to Generation
Venue Conference on Empirical Methods in Natural Language Processing
Session Main Conference
Year 2010
Authors

We present a simple, robust generation system which performs content selection and surface realization in a unified, domain-independent framework. In our approach, we break up the end-to-end generation process into a se- quence of local decisions, arranged hierar- chically and each trained discriminatively. We deployed our system in three different domains—Robocup sportscasting, technical weather forecasts, and common weather fore- casts, obtaining results comparable to state-of- the-art domain-specific systems both in terms of BLEU scores and human evaluation.