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The effect of lexicalization biases on cross-situational statistical learning of novel verbs
Languages vary in the mapping of relational terms onto events. For instance, English motion descriptions favor manner (how something moves) verbs over path (where something move) verbs, whereas those of other languages, like Spanish, show the opposite pattern. While these lexicalization biases are m...
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Published in: | Language and cognition 2024-12, Vol.16 (4), p.1007-1025 |
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Main Authors: | , , , |
Format: | Article |
Language: | English |
Subjects: | |
Citations: | Items that this one cites |
Online Access: | Get full text |
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Summary: | Languages vary in the mapping of relational terms onto events. For instance, English motion descriptions favor manner (how something moves) verbs over path (where something move) verbs, whereas those of other languages, like Spanish, show the opposite pattern. While these lexicalization biases are malleable, adopting a novel lexicalization pattern can be slow for second language learners. One potential mechanism for learning non-native verb mappings is cross-situational statistical learning (CSSL). However, the application of CSSL to verbs is limited and does not explicitly examine how lexicalization biases may complicate adults’ ability to resolve the referential uncertainty of multiple referents. We ask English-speaking monolingual adults to learn the mappings of ten verbs via CSSL. Verbs mapped onto either manner or path of motion, with the other event component held constant. Adults in both conditions demonstrated successful learning of novel verbs, with adults learning the manner verbs showing more consistent performance across accepting correct referents and rejecting incorrect ones. Our results are the first to demonstrate adults’ use of CSSL to acquire verb meanings that both align with and cut against native lexicalization biases and suggest a limited influence of lexicalization biases on adults’ learning in idealized CSSL conditions. |
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ISSN: | 1866-9808 1866-9859 |
DOI: | 10.1017/langcog.2023.70 |