Towards Generating Spatial Referring Expressions in a Social Robot: Dynamic vs Non-Ambiguous

Abstract

We present in this paper our work towards a new dynamic method of generating spatial referring expressions. While people are generally ambiguous in their description of locations, previous methods of artificial generation mostly considered non-ambiguous descriptions. However, to increase the naturalness of interaction and share workload in the communication, robots should be able to generate language in a more dynamic way. Our method initially produces ambiguous spatial referring expressions followed by dynamically generating repair statements. We built a classifier using data from 18 participants as they described locations to each other. We perform a preliminary analysis on this method using two further pilot studies.