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Neuroinformatics

, Volume 12, Issue 1, pp 143–179 | Cite as

Towards a Computational Model of Actor-Based Language Comprehension

  • Phillip M. Alday
  • Matthias Schlesewsky
  • Ina Bornkessel-Schlesewsky
Original Article

Abstract

Neurophysiological data from a range of typologically diverse languages provide evidence for a cross-linguistically valid, actor-based strategy of understanding sentence-level meaning. This strategy seeks to identify the participant primarily responsible for the state of affairs (the actor) as quickly and unambiguously as possible, thus resulting in competition for the actor role when there are multiple candidates. Due to its applicability across languages with vastly different characteristics, we have proposed that the actor strategy may derive from more basic cognitive or neurobiological organizational principles, though it is also shaped by distributional properties of the linguistic input (e.g. the morphosyntactic coding strategies for actors in a given language). Here, we describe an initial computational model of the actor strategy and how it interacts with language-specific properties. Specifically, we contrast two distance metrics derived from the output of the computational model (one weighted and one unweighted) as potential measures of the degree of competition for actorhood by testing how well they predict modulations of electrophysiological activity engendered by language processing. To this end, we present an EEG study on word order processing in German and use linear mixed-effects models to assess the effect of the various distance metrics. Our results show that a weighted metric, which takes into account the weighting of an actor-identifying feature in the language under consideration outperforms an unweighted distance measure. We conclude that actor competition effects cannot be reduced to feature overlap between multiple sentence participants and thereby to the notion of similarity-based interference, which is prominent in current memory-based models of language processing. Finally, we argue that, in addition to illuminating the underlying neurocognitive mechanisms of actor competition, the present model can form the basis for a more comprehensive, neurobiologically plausible computational model of constructing sentence-level meaning.

Keywords

Computational model Language processing Emergence Ambiguity resolution Actor identification 

Notes

Acknowledgments

We would like to thank Rick Lewis and Joakim Nivre for valuable discussions and suggestions related to the development of the computational model. We would also like to thank Isabel Plauth for the data acquisition.

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© Springer Science+Business Media New York 2013

Authors and Affiliations

  • Phillip M. Alday
    • 1
  • Matthias Schlesewsky
    • 2
  • Ina Bornkessel-Schlesewsky
    • 1
  1. 1.Department of Germanic LinguisticsUniversity of MarburgMarburgGermany
  2. 2.Department of English and LinguisticsUniversity of MainzMainzGermany

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