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Modeling the Directionality of Attention During Spatial Language Comprehension

  • Thomas KluthEmail author
  • Michele Burigo
  • Pia Knoeferle
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 10162)

Abstract

It is known that the comprehension of spatial prepositions involves the deployment of visual attention. For example, consider the sentence “The salt is to the left of the stove”. Researchers [29, 30] have theorized that people must shift their attention from the stove (the reference object, RO) to the salt (the located object, LO) in order to comprehend the sentence. Such a shift was also implicitly assumed in the Attentional Vector Sum (AVS) model by [35], a cognitive model that computes an acceptability rating for a spatial preposition given a display that contains an RO and an LO. However, recent empirical findings showed that a shift from the RO to the LO is not necessary to understand a spatial preposition ([3], see also [15, 38]). In contrast, these findings suggest that people perform a shift in the reverse direction (i.e., from the LO to the RO). Thus, we propose the reversed AVS (rAVS) model, a modified version of the AVS model in which attention shifts from the LO to the RO. We assessed the AVS and the rAVS model on the data from [35] using three model simulation methods. Our simulations show that the rAVS model performs as well as the AVS model on these data while it also integrates the recent empirical findings. Moreover, the rAVS model achieves its good performance while being less flexible than the AVS model. (This article is an updated and extended version of the paper [23] presented at the 8th International Conference on Agents and Artificial Intelligence in Rome, Italy. The authors would like to thank Holger Schultheis for helpful discussions about the additional model simulation.)

Keywords

Spatial language Spatial prepositions Cognitive modeling Model flexibility Visual attention 

Notes

Acknowledgments

This research was supported by the Cluster of Excellence Cognitive Interaction Technology ‘CITEC’ (EXC 277) at Bielefeld University, which is funded by the German Research Foundation (DFG). The authors would also like to thank two anonymous reviewers for their useful comments and suggestions.

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Copyright information

© Springer International Publishing AG 2017

Authors and Affiliations

  1. 1.Language & Cognition Group, CITEC (Cognitive Interaction Technology Excellence Cluster)Bielefeld UniversityBielefeldGermany
  2. 2.Department of German Language and LinguisticsHumboldt UniversityBerlinGermany

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