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Article published In:
Linguistic Approaches to Bilingualism
Vol. 8:5 (2018) ► pp.561–605

Quantifying cross-linguistic influence with a computational model

A study of case-marking comprehension

ORCID logo | Tilburg Center for Cognition and Communication (TiCC), Tilburg University
 | Tilburg University
 | Tilburg University
Cross-linguistic influence (CLI) is one of the key phenomena in bilingual and second language learning. We propose a method for quantifying CLI in the use of linguistic constructions with the help of a computational model, which acquires constructions in two languages from bilingual input. We focus on the acquisition of case-marking cues in Russian and German and simulate two experiments that employ a picture-choice task tapping into the mechanisms of sentence interpretation. Our model yields behavioral patterns similar to human, and these patterns can be explained by the amount of CLI: the negative CLI in high amounts leads to the misinterpretation of participant roles in Russian and German object-verb-subject sentences. Finally, we make two novel predictions about the acquisition of case-marking cues in Russian and German. Most importantly, our simulations suggest that the high degree of positive CLI may facilitate the interpretation of object-verb-subject sentences.
Keywords: cross-linguistic influence, computational model, case marking
Article outline
  • 1.Introduction
    • 1.1Quantifying cross-linguistic influence
    • 1.2Interpretation of transitive sentences
  • 2.Target studies on case-marking comprehension
    • 2.1Picture-choice task
    • 2.2Bilingual and monolingual Russian children
    • 2.3Adult L2 learners of Russian and German
  • 3.Computational model
    • 3.1Model overview
    • 3.2Input to the model
      • 3.2.1Input representations
      • 3.2.2Data collection
    • 3.3Learning process
      • 3.3.1Key components
      • 3.3.2Interpreting instances
    • 3.4Simulated picture-choice task
    • 3.5Measuring the amount of CLI
  • 4.Simulations and results
    • 4.1Simulation set 1
      • 4.1.1Simulation details
      • 4.1.2Results
      • 4.1.3Analysis of CLI
    • 4.2Simulation set 2
      • 4.2.1Simulation details
      • 4.2.2Results
      • 4.2.3Analysis of CLI
    • 4.3Novel simulations
      • 4.3.1Bilingual Russian-German children
      • 4.3.2Bilingual and monolingual German children
  • 5.Discussion
    • 5.1Quantifying the effect of CLI
    • 5.2CLI and “agent-first” in case-marking cue comprehension
    • 5.3CLI in argument structure constructions
    • 5.4Limitations of the study
    • 5.5Computational modeling: methodological implications
    • 5.6Modeling bilingual populations
  • 6.Conclusion
  • Acknowledgements
  • Notes
  • References
Published online: 2 November 2018
DOI logo
https://doi.org/10.1075/lab.16038.mat
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