Explaining the Ditransitive Person-Role Constraint

This paper proposes a frequency-based explanation of the Ditransitive Person-Role Constraint, a cross-linguistic generalization that can be formulated as follows: "Combinations of bound pronouns with the roles Recipient and Theme are disfavored if the Theme pronoun is first or second person and the Recipient pronoun is third person."

The verb slot in causative constructions. Finding the best fit

Using the technique of multiple distinctive collexeme analysis, this paper seeks to determine the verbs that are distinctively associated with the non-finite verb slot of English periphrastic causative constructions. Not only does the analysis reveal that the various causative constructions are attracted to essentially different verbs, but by examining how these verbs fall into semantic classes, it also hints at subtle differences in meaning between the constructions. In addition, the paper shows how the technique of multiple distinctive collexeme analysis can be usefully combined with other, complementary methods, and briefly discusses a number of factors which influence the results of multiple distinctive collexeme analysis and should therefore ideally be taken into account.

Learning Two-Person Interaction Models for Responsive Synthetic Humanoids

Imitation learning is a promising approach for generating life-like behaviors of virtual humans and humanoid robots. So far, however, imitation learning has been mostly restricted to single agent settings where observed motions are adapted to new environment conditions but not to the dynamic behavior of interaction partners. In this paper, we introduce a new imitation learning approach that is based on the simultaneous motion capture of two human interaction partners. From the observed interactions, low-dimensional motion models are extracted and a mapping between these motion models is learned. This interaction model allows the real-time generation of agent behaviors that are responsive to the body movements of an interaction partner. The interaction model can be applied both to the animation of virtual characters as well as to the behavior generation for humanoid robots.