Modeling misretrieval and feature substitution in agreement attraction: a computational evaluation

  • We present computational modeling results based on a self-paced reading study investigating number attraction effects in Eastern Armenian. We implement three novel computational models of agreement attraction in a Bayesian framework and compare their predictive fit to the data using k-fold cross-validation. We find that our data are better accounted for by an encoding-based model of agreement attraction, compared to a retrieval-based model. A novel methodological contribution of our study is the use of comprehension questions with open-ended responses, so that both misinterpretation of the number feature of the subject phrase and misassignment of the thematic subject role of the verb can be investigated at the same time. We find evidence for both types of misinterpretation in our study, sometimes in the same trial. However, the specific error patterns in our data are not fully consistent with any previously proposed model.
Author:Dario PaapeORCiDGND, Serine Avetisyan, Sol LagoORCiD, Shravan VasishthORCiDGND
Parent Title (English):Cognitive science
Place of publication:Malden, Mass.
Document Type:Article
Date of Publication (online):2021/08/11
Date of first Publication:2021/08/11
Publishing Institution:Universitätsbibliothek Johann Christian Senckenberg
Release Date:2022/06/15
Tag:Agreement attraction; Computational modeling; Eastern Armenian; Self-paced reading
Issue:8, art. e13019
Article Number:e13019
Page Number:30
First Page:1
Last Page:30
This work was supported partly by the University of Potsdam. The second author was funded through an Erasmus Mundus Joint Doctorate (EMJD) Fellowship for “International Doctorate for Experimental Approaches to Language and Brain” (IDEALAB) under grant no. 2012-0025-EMII-EMJ. Open Access funding enabled and organized by Projekt DEAL.
Institutes:Neuere Philologien
Dewey Decimal Classification:4 Sprache / 40 Sprache / 400 Sprache
4 Sprache / 41 Linguistik / 410 Linguistik
Licence (German):License LogoCreative Commons - Namensnennung 4.0