Please use this identifier to cite or link to this item: http://hdl.handle.net/1893/31354
Appears in Collections:Psychology Journal Articles
Peer Review Status: Refereed
Title: The crosslinguistic acquisition of sentence structure: Computational modeling and grammaticality judgments from adult and child speakers of English, Japanese, Hindi, Hebrew and K'iche'
Author(s): Ambridge, Ben
Tatsumi, Tomoko
Doherty, Laura
Maitreyee, Ramya
Bannard, Colin
Samanta, Soumitra
McCauley, Stewart
Arnon, Inbal
Zicherman, Shira
Bekman, Dani
Efrati, Amir
Berman, Ruth
Narasimhan, Bhuvana
Sharma, Dipti Misra
Fukumura, Kumiko
Keywords: Child language acquisition
Verb semantics
Preemption
Entrenchment
Causative
English
Japanese
Hindi
Hebrew
K'iche
Issue Date: Sep-2020
Citation: Ambridge B, Tatsumi T, Doherty L, Maitreyee R, Bannard C, Samanta S, McCauley S, Arnon I, Zicherman S, Bekman D, Efrati A, Berman R, Narasimhan B, Sharma DM & Fukumura K (2020) The crosslinguistic acquisition of sentence structure: Computational modeling and grammaticality judgments from adult and child speakers of English, Japanese, Hindi, Hebrew and K'iche'. Cognition, 202, Art. No.: 104310. https://doi.org/10.1016/j.cognition.2020.104310
Abstract: This preregistered study tested three theoretical proposals for how children form productive yet restricted linguistic generalizations, avoiding errors such as *The clown laughed the man, across three age groups (5–6 years, 9–10 years, adults) and five languages (English, Japanese, Hindi, Hebrew and K'iche'). Participants rated, on a five-point scale, correct and ungrammatical sentences describing events of causation (e.g., *Someone laughed the man; Someone made the man laugh; Someone broke the truck; ?Someone made the truck break). The verb-semantics hypothesis predicts that, for all languages, by-verb differences in acceptability ratings will be predicted by the extent to which the causing and caused event (e.g., amusing and laughing) merge conceptually into a single event (as rated by separate groups of adult participants). The entrenchment and preemption hypotheses predict, for all languages, that by-verb differences in acceptability ratings will be predicted by, respectively, the verb's relative overall frequency, and frequency in nearly-synonymous constructions (e.g., X made Y laugh for *Someone laughed the man). Analysis using mixed effects models revealed that entrenchment/preemption effects (which could not be distinguished due to collinearity) were observed for all age groups and all languages except K'iche', which suffered from a thin corpus and showed only preemption sporadically. All languages showed effects of event-merge semantics, except K'iche' which showed only effects of supplementary semantic predictors. We end by presenting a computational model which successfully simulates this pattern of results in a single discriminative-learning mechanism, achieving by-verb correlations of around r = 0.75 with human judgment data.
DOI Link: 10.1016/j.cognition.2020.104310
Rights: This is an open access article distributed under the terms of the Creative Commons CC-BY license (https://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. You are not required to obtain permission to reuse this article.
Notes: Additional co-authors: Rukmini Bhaya Nair, Seth Campbell, Clifton Pye, Pedro Mateo Pedro, Sindy Fabiola Can Pixabaj, Mario Marroquín Pelíz, Margarita Julajuj Mendoza
Licence URL(s): http://creativecommons.org/licenses/by/4.0/

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