Controlled Natural Languages for language generation in artificial cognition
Nicholas Hubert Kirk, Daniel Nyga, Michael Beetz · 2014
In this paper we discuss, within the context of artificial assistants performing everyday activities, a resolution method to disambiguate missing or not satisfactorily inferred action-specific information via explicit clarification. While arguing the lack of preexisting robot to human linguistic interaction methods, we introduce a novel use of Controlled Natural Languages (CNL) as means of output language and sentence construction for doubt verbalization. We additionally provide implemented working scenarios, state future possibilities and problems related to verbalization of technical cognition when making use of Controlled Natural Languages.