tailieunhanh - Báo cáo khoa học: "Incremental generation of spatial referring expressions in situated dialog∗"

This paper presents an approach to incrementally generating locative expressions. It addresses the issue of combinatorial explosion inherent in the construction of relational context models by: (a) contextually defining the set of objects in the context that may function as a landmark, and (b) sequencing the order in which spatial relations are considered using a cognitively motivated hierarchy of relations, and visual and discourse salience. | Incremental generation of spatial referring expressions in situated dialog John D. Kelleher Dublin Institute of Technology Dublin Ireland Geert-Jan M. Kruijff dFkI GmbH Saarbrucken Germany gj@ Abstract This paper presents an approach to incrementally generating locative expressions. It addresses the issue of combinatorial explosion inherent in the construction of relational context models by a contextually defining the set of objects in the context that may function as a landmark and b sequencing the order in which spatial relations are considered using a cognitively motivated hierarchy of relations and visual and discourse salience. 1 Introduction Our long-term goal is to develop conversational robots with whom we can interact through natural fluent visually situated dialog. An inherent aspect of visually situated dialog is reference to objects located in the physical environment Moratz and Tenbrink 2006 . In this paper we present a computational approach to the generation of spatial locative expressions in such situated contexts. The simplest form of locative expression is a prepositional phrase modifying a noun phrase to locate an object. 1 illustrates the type of locative we focus on generating. In this paper we use the term target T to refer to the object that is being located by a spatial expression and the term landmark L to refer to the object relative to which the target s location is described. 1 a. the book T on the table L Generating locative expressions is part of the general field of generating referring expressions GRE . Most GRE algorithms deal with the same problem given a domain description and a target object generate a description of the target object that distinguishes it from the other objects in the domain. We use distractor objects to indicate the The research reported here was supported by the CoSy project EU FP6 IST Cognitive Systems FP6-0O425O-IP. objects in the context excluding the target that at a given