• shareshare
  • link
  • cite
  • add
auto_awesome_motion View all 5 versions
Publication . Preprint . Article . 2020

Bilingual and multilingual mental lexicon: a modeling study with Linear Discriminative Learning

Yu Ying Chuang; Melanie J. Bell; Isabelle Banke; R. Harald Baayen;
Open Access
Published: 10 Jan 2020
Country: United Kingdom

This study addresses the question of whether there is anything special about learning a third language, as compared to learning a second language, just by virtue of the third language being the third language acquired, and independently of the specific properties of the third language. We used computational modeling to explore this question for the learning of a small vocabulary of some 400 words, with English as L1, German or Mandarin as L2, and Mandarin and alternatively Dutch, as L3. For computational modeling, we made use of the mathematical framework of linear discriminative learning, which we extended with the learning rule of Widrow-Hoff to enable the modeling of incremental learning of the mappings between form and meaning when words' meanings are represented by vectors of real numbers (embeddings) rather than by abstract symbolic units. A series of simulation experiments covering single-language learning, bilingual learning, and finally trilingual learning, clarified that within the framework of discrimination learning, within-language homophones give rise to frailty in comprehension that in turn for production gives rise to semantic errors in L1, and language intrusions in L2 and L3. Our model correctly predicts production to lag behind comprehension in learning, and it clarified that, within the boundaries of discrimination learning, the properties of the L3 crucially determine whether L3 learning appears to involve a language that is `dormant' with respect to L1 and L2. Qualitatively surprisingly different patterns of acquisition of the L3, and its interactions with L1 and L2, can arise in our simulations without any changes in the mathematics driving learning. Our simulations also show that when words' forms incorporate not only segmental but also suprasegmental information, the nature of errors that arise in production changes. In the general discussion, we reflect on the implications of our findings for the question of what is special about multilingualism.

Subjects by Vocabulary

Microsoft Academic Graph classification: Neuroscience of multilingualism Psycholinguistics Multilingualism Indo-European languages Psychology Mental lexicon Vocabulary development First language Artificial intelligence business.industry business Computational linguistics Natural language processing computer.software_genre computer


bepress|Social and Behavioral Sciences, bepress|Social and Behavioral Sciences|Linguistics, bepress|Social and Behavioral Sciences|Linguistics|Computational Linguistics, PsyArXiv|Social and Behavioral Sciences, PsyArXiv|Social and Behavioral Sciences|Linguistics, PsyArXiv|Social and Behavioral Sciences|Linguistics|Computational Linguistics, Linguistics and Language, Language and Linguistics, Education

Related Organizations
Funded by
Wide Incremental learning with Discrimination nEtworks
  • Funder: European Commission (EC)
  • Project Code: 742545
  • Funding stream: H2020 | ERC | ERC-ADG
Validated by funder
Related to Research communities
Digital Humanities and Cultural Heritage