Language Learning and Processing in People and Machines
Name
N19-5005.pdf
Description
Published version
Size
113.11 KB
Format
Adobe PDF
Checksum (MD5)
2232ebbc2accdb94946f55e8cd7704eb
Author(s)
Nematzadeh, Aida
Futrell, Richard
Levy, Roger P
Date Issued
June 2019
Journal
2019 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies
Publisher
Association for Computational Linguistics
Citation
Nematzadeh, Aida et al. "Language Learning and Processing in People and Machines." 2019 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, June 2019, Minneapolis, Minnesota, Association for Computational Linguistics, June 2019.
Version
Final published version
Abstract
The goal of this tutorial is to bring the fields of computational linguistics and computational cognitive science closer: we will introduce different stages of language acquisition and their parallel problems in NLP. As an example, one of the early challenges children face is mapping the meaning of word labels (such as “cat”) to their referents (the furry animal in the living room). Word learning is similar to the word alignment problem in machine translation. We explain the current computational models of language acquisition, their limitations, and how the insights from these models can be incorporated into NLP applications. Moreover, we discuss how we can take advantage of the cognitive science of language in computational linguistics: for example, by designing cognitively-motivated evaluations task or buildings language-learning inductive biases into our models.
MIT Department
Massachusetts Institute of Technology. Department of Brain and Cognitive Sciences
Terms of Use
Article is made available in accordance with the publisher's policy and may be subject to US copyright law. Please refer to the publisher's site for terms of use.
Persistent DSpace Link
DOI of Published Version
https://doi.org/10.18653/v1/n19-5005
