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The crosslinguistic acquisition of sentence structure: Computational modeling and grammaticality judgments from adult and child speakers of English, Japanese, Hindi, Hebrew and K'iche'()
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...
Autores principales: | , , , , , , , , , , , , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Elsevier
2020
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7397526/ https://www.ncbi.nlm.nih.gov/pubmed/32623135 http://dx.doi.org/10.1016/j.cognition.2020.104310 |
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author | Ambridge, Ben Maitreyee, Ramya Tatsumi, Tomoko Doherty, Laura Zicherman, Shira Pedro, Pedro Mateo Bannard, Colin Samanta, Soumitra McCauley, Stewart Arnon, Inbal Bekman, Dani Efrati, Amir Berman, Ruth Narasimhan, Bhuvana Sharma, Dipti Misra Nair, Rukmini Bhaya Fukumura, Kumiko Campbell, Seth Pye, Clifton Pixabaj, Sindy Fabiola Can Pelíz, Mario Marroquín Mendoza, Margarita Julajuj |
author_facet | Ambridge, Ben Maitreyee, Ramya Tatsumi, Tomoko Doherty, Laura Zicherman, Shira Pedro, Pedro Mateo Bannard, Colin Samanta, Soumitra McCauley, Stewart Arnon, Inbal Bekman, Dani Efrati, Amir Berman, Ruth Narasimhan, Bhuvana Sharma, Dipti Misra Nair, Rukmini Bhaya Fukumura, Kumiko Campbell, Seth Pye, Clifton Pixabaj, Sindy Fabiola Can Pelíz, Mario Marroquín Mendoza, Margarita Julajuj |
author_sort | Ambridge, Ben |
collection | PubMed |
description | 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. |
format | Online Article Text |
id | pubmed-7397526 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | Elsevier |
record_format | MEDLINE/PubMed |
spelling | pubmed-73975262020-09-01 The crosslinguistic acquisition of sentence structure: Computational modeling and grammaticality judgments from adult and child speakers of English, Japanese, Hindi, Hebrew and K'iche'() Ambridge, Ben Maitreyee, Ramya Tatsumi, Tomoko Doherty, Laura Zicherman, Shira Pedro, Pedro Mateo Bannard, Colin Samanta, Soumitra McCauley, Stewart Arnon, Inbal Bekman, Dani Efrati, Amir Berman, Ruth Narasimhan, Bhuvana Sharma, Dipti Misra Nair, Rukmini Bhaya Fukumura, Kumiko Campbell, Seth Pye, Clifton Pixabaj, Sindy Fabiola Can Pelíz, Mario Marroquín Mendoza, Margarita Julajuj Cognition Article 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. Elsevier 2020-09 /pmc/articles/PMC7397526/ /pubmed/32623135 http://dx.doi.org/10.1016/j.cognition.2020.104310 Text en © 2020 The Author(s) http://creativecommons.org/licenses/by/4.0/ This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/). |
spellingShingle | Article Ambridge, Ben Maitreyee, Ramya Tatsumi, Tomoko Doherty, Laura Zicherman, Shira Pedro, Pedro Mateo Bannard, Colin Samanta, Soumitra McCauley, Stewart Arnon, Inbal Bekman, Dani Efrati, Amir Berman, Ruth Narasimhan, Bhuvana Sharma, Dipti Misra Nair, Rukmini Bhaya Fukumura, Kumiko Campbell, Seth Pye, Clifton Pixabaj, Sindy Fabiola Can Pelíz, Mario Marroquín Mendoza, Margarita Julajuj The crosslinguistic acquisition of sentence structure: Computational modeling and grammaticality judgments from adult and child speakers of English, Japanese, Hindi, Hebrew and K'iche'() |
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'() |
title_full | The crosslinguistic acquisition of sentence structure: Computational modeling and grammaticality judgments from adult and child speakers of English, Japanese, Hindi, Hebrew and K'iche'() |
title_fullStr | The crosslinguistic acquisition of sentence structure: Computational modeling and grammaticality judgments from adult and child speakers of English, Japanese, Hindi, Hebrew and K'iche'() |
title_full_unstemmed | The crosslinguistic acquisition of sentence structure: Computational modeling and grammaticality judgments from adult and child speakers of English, Japanese, Hindi, Hebrew and K'iche'() |
title_short | The crosslinguistic acquisition of sentence structure: Computational modeling and grammaticality judgments from adult and child speakers of English, Japanese, Hindi, Hebrew and K'iche'() |
title_sort | crosslinguistic acquisition of sentence structure: computational modeling and grammaticality judgments from adult and child speakers of english, japanese, hindi, hebrew and k'iche'() |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7397526/ https://www.ncbi.nlm.nih.gov/pubmed/32623135 http://dx.doi.org/10.1016/j.cognition.2020.104310 |
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