Stochastic language generation for spoken dialogue systems

Abstract

The two uen_.t approaches to language generation, emplatebased and rule-based (linguistic) NLG, have limitations when applied to spoken dialogue systems, in part because they were developed for text generation. In this paper, we propose a new corpus-based approach to natural language generation, specifically designed for spoken dialogue systems.