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Hits 1 – 15 of 15

1
When missing NPs make double center-embedding sentences acceptable
In: Glossa: a journal of general linguistics; Vol 6, No 1 (2021); 37 ; 2397-1835 (2021)
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2
Children’s Learning of a Semantics-Free Artificial Grammar with Center Embedding
In: BIOLINGUISTICS; Vol. 14 (2020); 21-48 ; 1450-3417 (2020)
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3
Children’s Learning of a Semantics-Free Artificial Grammar with Center Embedding
In: Biolinguistics, Vol 14 (2020) (2020)
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4
Children’s Learning of a Semantics-Free Artificial Grammar with Center Embedding
In: Biolinguistics, Vol 14 (2020) (2020)
Abstract: Whether non-human animals have an ability to learn and process center embedding, a core property of human language syntax, is still debated. Artificial-grammar learning (AGL) has been used to compare humans and animals in the learning of center embedding. However, up until now, human participants have only included adults, and data on children, who are the key players of natural language acquisition, are lacking. We created a novel game-like experimental paradigm combining the go/no-go procedure often used in animal research with the stepwise learning methods found effective in human adults’ center-embedding learning. Here we report that some children succeeded in learning a semantics-free artificial grammar with center embedding (A2B2 grammar) in the auditory modality. Although their success rate was lower than adults’, the successful children looked as efficient learners as adults. Where children struggled, their memory capacity seemed to have limited their AGL performance.
Keyword: artificial grammar; biolinguistics; center embedding; children; go/no-go; Language and Literature; P; P1-1091; Philology. Linguistics
URL: https://doaj.org/article/494c98a4236b4dd08726b05e30abbc7e
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5
Short-term memory and sign languages : sign span and its linguistic implications
In: Linguística : Revista de Estudos Linguísticos da Universidade do Porto, Vol 11, Iss a11, Pp 59-89 (2016) (2016)
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6
The Non-Hierarchical Nature of the Chomsky Hierarchy-Driven Artificial-Grammar Learning
In: BIOLINGUISTICS; Vol. 8 (2014); 163-180 ; 1450-3417 (2014)
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7
The Non-Hierarchical Nature of the Chomsky Hierarchy-Driven Artificial-Grammar Learning
In: Biolinguistics, Vol 8, Iss 0, Pp 163-180 (2014) (2014)
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8
Third Factors and the Performance Interface in Language Design
In: BIOLINGUISTICS; Vol. 7 (2013); 1-34 ; 1450-3417 (2013)
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9
Third factors and the performance interface in language design
In: Biolinguistics ; 7 (2013). - S. 1-34. - eISSN 1450-3417 (2013)
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10
Sobre complejidad gramatical y complejidad de conocimiento ; Sobre complexitat gramatical i complexitat de processament ; On grammatical and processing complexity
In: Llengua, societat i comunicació; Núm. 11 Llengua i complexitat; 99 - 107 ; Lengua, sociedad y comunicación; Núm. 11 Llengua i complexitat; 99 - 107 ; Language, society and communication; Núm. 11 Llengua i complexitat; 99 - 107 ; 1697-5928 (2013)
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11
Third Factors and the Performance Interface in Language Design
In: Biolinguistics, Vol 7, Iss 0, Pp 1-34 (2013) (2013)
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12
Sobre complexitat gramatical i complexitat de processament ; About grammar complexity and knowledge complexity ; Sobre complejidad gramatical y complejidad de conocimiento
In: LSC– Llengua, societat i comunicació; 2013: Núm.: 11 Monogràfic: 'Llengua i complexitat'; 90-97 (2013)
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13
Recursive Misrepresentations: a Reply to Levinson (2013)
In: http://ling.auf.net/lingbuzz/001822/current.pdf?_s=XVi5nq1suJy3KNKF
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14
Structurally informative prosodic cues in center-embedded and right-branching sentences
In: http://cuny2012.commons.gc.cuny.edu/files/2012/03/cuny2012_37.pdf
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15
The Non-Hierarchical Nature of the Chomsky Hierarchy-Driven Artificial-Grammar Learning
In: http://biolinguistics.eu/index.php/biolinguistics/article/viewFile/348/336/
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