License: Creative Commons Attribution 4.0 International license (CC BY 4.0)
When quoting this document, please refer to the following
DOI: 10.4230/OASIcs.LDK.2021.4
URN: urn:nbn:de:0030-drops-145402
URL: https://drops.dagstuhl.de/opus/volltexte/2021/14540/
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Ambridge, Ben

A Computational Simulation of Children’s Language Acquisition (Crazy New Idea)

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OASIcs-LDK-2021-4.pdf (0.4 MB)


Abstract

Many modern NLP models are already close to simulating children’s language acquisition; the main thing they currently lack is a "real world" representation of semantics that allows them to map from form to meaning and vice-versa. The aim of this "Crazy Idea" is to spark a discussion about how we might get there.

BibTeX - Entry

@InProceedings{ambridge:OASIcs.LDK.2021.4,
  author =	{Ambridge, Ben},
  title =	{{A Computational Simulation of Children’s Language Acquisition}},
  booktitle =	{3rd Conference on Language, Data and Knowledge (LDK 2021)},
  pages =	{4:1--4:3},
  series =	{Open Access Series in Informatics (OASIcs)},
  ISBN =	{978-3-95977-199-3},
  ISSN =	{2190-6807},
  year =	{2021},
  volume =	{93},
  editor =	{Gromann, Dagmar and S\'{e}rasset, Gilles and Declerck, Thierry and McCrae, John P. and Gracia, Jorge and Bosque-Gil, Julia and Bobillo, Fernando and Heinisch, Barbara},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/opus/volltexte/2021/14540},
  URN =		{urn:nbn:de:0030-drops-145402},
  doi =		{10.4230/OASIcs.LDK.2021.4},
  annote =	{Keywords: Child language acquisition, language development, deep learning, BERT, ELMo, GPT-3}
}

Keywords: Child language acquisition, language development, deep learning, BERT, ELMo, GPT-3
Collection: 3rd Conference on Language, Data and Knowledge (LDK 2021)
Issue Date: 2021
Date of publication: 30.08.2021


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