Utterance templates merging in automaton-based dialogue systems

Many of the implemented dialog systems in industry are based on a state automaton. Most of these systems rely on predefined messages, where a message is an ordered set of utterance templates, in order to produce the output message. The automaton-based dialog manager computes the correspondence of a particular predefined message to a given user´s request. However, a rather common event in the dialog system´s workflow is the dialog manager´s highlighting of multiple messages in response to a user´s request. In order to produce an appropriate output message, the templates of all messages need to be merged and restructured. In this paper, we introduce a natural language generation (NLG) module to the automaton based dialog system in order to perform this task.