Incremental Semantics Driven Natural Language Generation with Self-Repairing Capability

This paper presents the on-going development of a model of incremental semantics driven natural language generation (NLG) for incremental dialogue systems. The approach is novel in its tight integration of incremental goal-driven semantics and syntactic construction, utilizing Type Theory with Records (TTR) record types for goal concepts as its input and the grammar formalism Dynamic Syntax (DS) for a wordby-word tactical generation procedure. The characterization of generation in terms of semantic input and word output graphs allows an integration into the incremental dialogue system Jindigo and facilitates the generation of human-like self-repairs in a semantically and syntactically motivated way.