Neural Agent-based Models To Study Language Contact Using Linguistic Data

Peter Dekker, Bart De Boer

Research output: Unpublished contribution to conference › Poster

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Abstract

In this paper, we propose an outline for linguistic research on language change, as observed in the languages of the world, using neural agent-based models of emergent communication. We describe how such models could be used to study morphological simplification, using a case study of language contact in Eastern Indonesia. A neural architecture is used to represent hypothesized cognitive mechanisms of language change: a generalization mechanism, the procedural/declarative model, and a phonological mechanism, the hyper & hypo articulation model, that involves a theory of mind of the listener.
Original languageEnglish
Pages1-6
Number of pages6
Publication statusPublished - 12 Dec 2020
Event4th NeurIPS Workshop on Emergent Communication: Talking to Strangers: Zero-Shot Emergent Communication - Vancouver, Canada
Duration: 12 Dec 2020 → 12 Dec 2020
https://sites.google.com/view/emecom2020/home

Workshop

Workshop4th NeurIPS Workshop on Emergent Communication
CountryCanada
CityVancouver
Period12/12/20 → 12/12/20
Internet address

Keywords

  • agent-based models
  • neural networks
  • emergent communication
  • language change
  • language contact
  • deep learning

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