Infant artificial language learning and language acquisition

2000 ◽  
Vol 4 (5) ◽  
pp. 178-186 ◽  
Author(s):  
Rebecca L. Gómez ◽  
LouAnn Gerken
Keyword(s):  
Language Acquisition ◽  
Language Learning ◽  
Artificial Language ◽  
Artificial Language Learning

scholarly journals Children’s sensitivity to phonological and semantic cues during noun class learning: evidence for a phonological bias

2018 ◽  
Author(s):  
Jennifer Culbertson ◽  
Hanna Jarvinen ◽  
Frances Haggarty ◽  
Kenny Smith
Keyword(s):  
Language Acquisition ◽  
Language Learning ◽  
Classification Systems ◽  
Developmental Changes ◽  
Artificial Language ◽  
Phonological Information ◽  
Semantic Cues ◽  
Artificial Language Learning ◽  
Cue Use ◽  
Noun Class

Previous research on the acquisition of noun classification systems (e.g., grammatical gender) has found that child learners rely disproportionately on phonological cues to determine the class of a new noun, even when competing semantic cues are more reliable in their language. Culbertson, Gagliardi, and Smith (2017) argue that this likely results from the early availability of phonological information during acquisition; learners base their initial representations on formal features of nouns, only later integrating semantic cues from noun meanings . Here, we use artificial language learning experiments to show that early availability drives cue use in children (67 year-olds). However, we also find evidence of developmental changes in sensitivity to semantics; when both cues types are simultaneously available, children are more likely to rely on phonology than adults. Our results suggest that early availability and a bias favoring phonological cues both contribute to children’s over-reliance on phonology in natural language acquisition.

scholarly journals Do children privilege phonological cues in noun class learning?

2018 ◽  
Author(s):  
Jennifer Culbertson ◽  
Kenny Smith ◽  
Hanna Jarvinen ◽  
Frances Haggarty
Keyword(s):  
Language Acquisition ◽  
Natural Language ◽  
Language Learning ◽  
Grammatical Gender ◽  
Developmental Changes ◽  
Artificial Language ◽  
Semantic Cues ◽  
Artificial Language Learning ◽  
Noun Class

Previous research on acquisition of noun class systems, such as grammatical gender, has shown that child learners rely disproportionately on phonological cues to class, even when competing semantic cues are more reliable. Culbertson, Gagliardi, and Smith (2017) use artificial language learning experiments with adults to argue that over-reliance on phonology may be due to the fact that phonological cues are available first; learners base early representations on surface phonological dependencies, only later integrating semantic cues from noun meanings. Here, we show that child learners (6-7 year-olds) show this same sensitivity to early availability. However, we also find intriguing evidence of developmental changes in sensitivity to semantics; when both cues are simultaneously available children are more likely to rely on a phonology cue than adults. Our results suggest that early availability and a bias in favor of phonological cues may both contribute to children’s over- reliance on phonology in natural language acquisition.

scholarly journals Nobody Doesn’t Like Negative Concord

2021 ◽  
Author(s):  
Mora Maldonado ◽  
Jennifer Culbertson
Keyword(s):  
Language Acquisition ◽  
Natural Language ◽  
Language Learning ◽  
English Speakers ◽  
Artificial Language ◽  
Negative Concord ◽  
Double Negation ◽  
Artificial Language Learning ◽  
The Status ◽  
Negative Marker

AbstractLanguages vary with respect to whether sentences with two negative elements give rise to double negation or negative concord meanings. We explore an influential hypothesis about what governs this variation: namely, that whether a language exhibits double negation or negative concord is partly determined by the phonological and syntactic nature of its negative marker (Zeijlstra 2004; Jespersen 1917). For example, one version of this hypothesis argues that languages with affixal negation must be negative concord (Zeijlstra 2008). We use an artificial language learning experiment to investigate whether English speakers are sensitive to the status of the negative marker when learning double negation and negative concord languages. Our findings fail to provide evidence supporting this hypothesised connection. Instead, our results suggest that learners find it easier to learn negative concord languages compared to double negation languages independently of whether the negative marker is an adverb or an affix. This is in line with evidence from natural language acquisition (Thornton et al. 2016).

Learning Paradigmatic Structure

2018 ◽  
pp. 179-200
Author(s):  
Vsevolod Kapatsinski
Keyword(s):  
Language Learning ◽  
Grammatical Gender ◽  
Second Order ◽  
Production Plan ◽  
Artificial Language ◽  
Artificial Language Learning ◽  
Noun Classes ◽  
Paradigmatic Structure ◽  
New Evidence

This chapter reviews research on the acquisition of paradigmatic structure (including research on canonical antonyms, morphological paradigms, associative inference, grammatical gender and noun classes). It discusses the second-order schema hypothesis, which views paradigmatic structure as mappings between constructions. New evidence from miniature artificial language learning of morphology is reported, which suggests that paradigmatic mappings involve paradigmatic associations between corresponding structures as well as an operation, copying an activated representation into the production plan. Producing a novel form of a known word is argued to involve selecting a prosodic template and filling it out with segmental material using form-meaning connections, syntagmatic and paradigmatic form-form connections and copying, which is itself an outcome cued by both semantics and phonology.

Learning biases in opaque interactions

Phonology ◽  
2019 ◽  
Vol 36 (4) ◽  
pp. 627-653
Author(s):  
Brandon Prickett
Keyword(s):  
Neural Network ◽  
Language Learning ◽  
Learning Process ◽  
Computational Modelling ◽  
Artificial Language ◽  
Phonological Acquisition ◽  
Learning Biases ◽  
Learning Experiment ◽  
Artificial Language Learning ◽  
Harmonic Serialism

This study uses an artificial language learning experiment and computational modelling to test Kiparsky's claims about Maximal Utilisation and Transparency biases in phonological acquisition. A Maximal Utilisation bias would prefer phonological patterns in which all rules are maximally utilised, and a Transparency bias would prefer patterns that are not opaque. Results from the experiment suggest that these biases affect the learnability of specific parts of a language, with Maximal Utilisation affecting the acquisition of individual rules, and Transparency affecting the acquisition of rule orderings. Two models were used to simulate the experiment: an expectation-driven Harmonic Serialism learner and a sequence-to-sequence neural network. The results from these simulations show that both models’ learning is affected by these biases, suggesting that the biases emerge from the learning process rather than any explicit structure built into the model.

scholarly journals Compositional Hierarchical Structure Evolves through Cultural Transmission: An Experimental Study

2019 ◽  
Vol 4 (2) ◽  
pp. 83-107 ◽  
Author(s):  
Carmen Saldana ◽  
Simon Kirby ◽  
Robert Truswell ◽  
Kenny Smith
Keyword(s):  
Language Learning ◽  
Language Learners ◽  
Hierarchical Structure ◽  
Cultural Transmission ◽  
Artificial Language ◽  
Compositional Structure ◽  
Evolutionary Linguistics ◽  
Artificial Language Learning ◽  
Learning Techniques ◽  
Iterated Learning

AbstractCompositional hierarchical structure is a prerequisite for productive languages; it allows language learners to express and understand an infinity of meanings from finite sources (i.e., a lexicon and a grammar). Understanding how such structure evolved is central to evolutionary linguistics. Previous work combining artificial language learning and iterated learning techniques has shown how basic compositional structure can evolve from the trade-off between learnability and expressivity pressures at play in language transmission. In the present study we show, across two experiments, how the same mechanisms involved in the evolution of basic compositionality can also lead to the evolution of compositional hierarchical structure. We thus provide experimental evidence showing that cultural transmission allows advantages of compositional hierarchical structure in language learning and use to permeate language as a system of behaviour.

scholarly journals The importance of correctly characterising the English spelling system when devising and evaluating methods of reading instruction: Comment on Taylor, Davis, and Rastle (2017)

2018 ◽  
Vol 71 (7) ◽  
pp. 1497-1500 ◽  
Author(s):  
Jeffrey S Bowers ◽  
Peter N Bowers
Keyword(s):  
Language Learning ◽  
Reading Instruction ◽  
Test Performance ◽  
Artificial Language ◽  
Main Function ◽  
Artificial Language Learning ◽  
Mistaken Assumption ◽  
Basic And Applied Research ◽  
Based Instruction ◽  
Evaluating Methods

Taylor, Davis, and Rastle employed an artificial language learning paradigm to compare phonics and meaning-based approaches to reading instruction. Adults were taught consonant, vowel, and consonant (CVC) words composed of novel letters when the mappings between letters and sounds were completely systematic and the mappings between letters and meaning were completely arbitrary. At test, performance on naming tasks was better following training that emphasised the phonological rather than the semantic mappings, whereas performance on semantic tasks was similar in the two conditions. The authors concluded that these findings support phonics for early reading instruction in English. However, in our view, these conclusions are not justified given that the artificial language mischaracterised both the phonological and semantic mappings in English. Furthermore, the way participants studied the arbitrary letter-meaning correspondences bears little relation to meaning-based strategies used in schools. To compare phonics with meaning-based instruction it must be determined whether phonics is better than alternative forms of instruction that fully exploit the regularities within the semantic route. This is rarely assessed because of a widespread and mistaken assumption that underpins so much basic and applied research, namely, that the main function of spellings is to represent sounds.

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