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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 Journal: Language Learning, volume 71, pages 219-292 (issn: 0023-8333, eissn: 1467-9922, Copyright policy )
Publisher: Wiley
Country: United Kingdom
Abstract

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

Subjects

Linguistics and Language, Language and Linguistics, Education, 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

Related Organizations
Funded by
EC| WIDE
Project
WIDE
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
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