Explores a surface generation framework that allows a dynamic word re-ordering in the context of a conversational system. The system attempts to duplicate the use of ""word re-ordering"" in order to maximize their communicative effectiveness. The surface NLG module expresses new information differently from old information. The input to the system consists of attribute-value pairs, some mandatory, some optional. Generation is a carried out by a hybrid statistical and grammar-based process.