Discourse Generation Using Utility-Trained Coherence Models

  title={Discourse Generation Using Utility-Trained Coherence Models},
  author={Radu Soricut and Daniel Marcu},
We describe a generic framework for integrating various stochastic models of discourse coherence in a manner that takes advantage of their individual strengths. An integral part of this framework are algorithms for searching and training these stochastic coherence models. We evaluate the performance of our models and algorithms and show empirically that utilitytrained log-linear coherence models outperform each of the individual coherence models considered. 
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