Does domain size impact speech onset time during reference production?

In referring to a target referent, speakers need to choose a set of properties that jointly distinguish it from its distractors. Current computational models view this as a search process in which the decision to include a prop- erty requires checking how many distractors it excludes. Thus, these models predict that identifying descriptions should take longer to produce the larger the distractor set is, independent of how many properties are required to identify a target. Since every property that is selected is checked, they also predict that distinguishing a tar- get should take longer the more properties are required to distinguish it. This paper tests this prediction em- pirically, contrasting it with two alternative predictions based on models of visual search. Our results provide support for the predictions of computational models, suggesting a crucial di erence between the mechanisms underlying reference production and object identi ca- tion.peer-reviewe

Referring Expression Generation in Situated Interaction

While most current frameworks for reference handling are based on binary truth-theoretic knowledge representation, in this thesis I argue for a perspective on reference which emphasises the collaborative nature of reference. I present the Probabilistic Reference And GRounding mechanism (PRAGR) which uses flexible concept assignment based on vague property models and situational context in order to maximise the chance of communicative success. I demonstrate that PRAGR is capable of dealing with several property domains with different internal structures, such as graded adjectives, colour, shape, projective terms, and projective regions. Further, I show that PRAGR is fit to handle in an integrated fashion the most relevant challenges of Referring Expression Generation, in particular graded properties, spatial relations, and salience effects. In three empirical evaluation studies, I demonstrate the usefulness of PRAGR for situated referential communication