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Polysemous Language in Child Directed Speech

Sammy Floyd, Libby Barak, Adele Goldberg, Casey Lew-Williams


Abstract
Polysemous Language in Child Directed Speech Learning the meaning of words is one of the fundamental building blocks of verbal communication. Models of child language acquisition have generally made the simplifying assumption that each word appears in child-directed speech with a single meaning. To understand naturalistic word learning during childhood, it is essential to know whether children hear input that is in fact constrained to single meaning per word, or whether the environment naturally contains multiple senses. In this study, we use a topic modeling approach to automatically induce word senses from child-directed speech. Our results confirm the plausibility of our automated analysis approach and reveal an increasing rate of using multiple senses in child-directed speech, starting with corpora from children as early as the first year of life.
Anthology ID:
W19-3636
Volume:
Proceedings of the 2019 Workshop on Widening NLP
Month:
August
Year:
2019
Address:
Florence, Italy
Editors:
Amittai Axelrod, Diyi Yang, Rossana Cunha, Samira Shaikh, Zeerak Waseem
Venue:
WiNLP
SIG:
Publisher:
Association for Computational Linguistics
Note:
Pages:
114–117
Language:
URL:
https://aclanthology.org/W19-3636
DOI:
Bibkey:
Cite (ACL):
Sammy Floyd, Libby Barak, Adele Goldberg, and Casey Lew-Williams. 2019. Polysemous Language in Child Directed Speech. In Proceedings of the 2019 Workshop on Widening NLP, pages 114–117, Florence, Italy. Association for Computational Linguistics.
Cite (Informal):
Polysemous Language in Child Directed Speech (Floyd et al., WiNLP 2019)
Copy Citation: