Natural Noun Phrase Variation for Interactive Characters

Abstract

Interactive characters that cohabit a shared space with human partners need to generate and interpret references to elements of the virtual world. Natural language allows for a wide range of phrasings for referring to any particular object, and this variation is thought to reflect not only spatial but also cognitive and linguistic factors. Our study attempts to account for the variability in referring forms found in a set of dialogs of two human partners performing a treasure-hunt task in a virtual world. A decision tree classifier was built that predicts the form of 51% of the referring expressions, compared to a baseline of 39% achieved by a heuristic classifier. The classification algorithm can be used by conversational characters to generate referring expressions of the appropriate form.