Modeling the Relationship between Input Distributions and Learning Trajectories with the Tolerance Principle

Jordan Kodner

doi:10.18653/v1/2022.cmcl-1.7

Modeling the Relationship between Input Distributions and Learning Trajectories with the Tolerance Principle

Jordan Kodner

Linguistics

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

1 Scopus citations

Abstract

Child language learners develop with remarkable uniformity, both in their learning trajectories and ultimate outcomes, despite major differences in their learning environments. In this paper, we explore the role that the frequencies and distributions of irregular lexical items in the input plays in driving learning trajectories. I conclude that while the Tolerance Principle, a type-based model of productivity learning, accounts for inter-learner uniformity, it also interacts with input distributions to drive cross-pattern variation in learning trajectories.

Original language	English
Title of host publication	CMCL 2022 - Workshop on Cognitive Modeling and Computational Linguistics, Proceedings of the Workshop
Editors	Emmanuele Chersoni, Nora Hollenstein, Cassandra L. Jacobs, Yohei Oseki, Laurent Prevot, Enrico Santus
Publisher	Association for Computational Linguistics (ACL)
Pages	61-67
Number of pages	7
ISBN (Electronic)	9781955917292
DOIs	https://doi.org/10.18653/v1/2022.cmcl-1.7
State	Published - 2022
Event	12th Workshop on Cognitive Modeling and Computational Linguistics, CMCL 2022 - Dublin, Ireland Duration: May 26 2022 → …

Publication series

Name	CMCL 2022 - Workshop on Cognitive Modeling and Computational Linguistics, Proceedings of the Workshop

Conference

Conference	12th Workshop on Cognitive Modeling and Computational Linguistics, CMCL 2022
Country/Territory	Ireland
City	Dublin
Period	05/26/22 → …

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10.18653/v1/2022.cmcl-1.7

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Kodner, J. (2022). Modeling the Relationship between Input Distributions and Learning Trajectories with the Tolerance Principle. In E. Chersoni, N. Hollenstein, C. L. Jacobs, Y. Oseki, L. Prevot, & E. Santus (Eds.), CMCL 2022 - Workshop on Cognitive Modeling and Computational Linguistics, Proceedings of the Workshop (pp. 61-67). (CMCL 2022 - Workshop on Cognitive Modeling and Computational Linguistics, Proceedings of the Workshop). Association for Computational Linguistics (ACL). https://doi.org/10.18653/v1/2022.cmcl-1.7

Kodner, Jordan. / Modeling the Relationship between Input Distributions and Learning Trajectories with the Tolerance Principle. CMCL 2022 - Workshop on Cognitive Modeling and Computational Linguistics, Proceedings of the Workshop. editor / Emmanuele Chersoni ; Nora Hollenstein ; Cassandra L. Jacobs ; Yohei Oseki ; Laurent Prevot ; Enrico Santus. Association for Computational Linguistics (ACL), 2022. pp. 61-67 (CMCL 2022 - Workshop on Cognitive Modeling and Computational Linguistics, Proceedings of the Workshop).

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title = "Modeling the Relationship between Input Distributions and Learning Trajectories with the Tolerance Principle",

abstract = "Child language learners develop with remarkable uniformity, both in their learning trajectories and ultimate outcomes, despite major differences in their learning environments. In this paper, we explore the role that the frequencies and distributions of irregular lexical items in the input plays in driving learning trajectories. I conclude that while the Tolerance Principle, a type-based model of productivity learning, accounts for inter-learner uniformity, it also interacts with input distributions to drive cross-pattern variation in learning trajectories.",

author = "Jordan Kodner",

note = "Publisher Copyright: {\textcopyright} 2022 Association for Computational Linguistics.; 12th Workshop on Cognitive Modeling and Computational Linguistics, CMCL 2022 ; Conference date: 26-05-2022",

year = "2022",

doi = "10.18653/v1/2022.cmcl-1.7",

language = "English",

series = "CMCL 2022 - Workshop on Cognitive Modeling and Computational Linguistics, Proceedings of the Workshop",

publisher = "Association for Computational Linguistics (ACL)",

pages = "61--67",

editor = "Emmanuele Chersoni and Nora Hollenstein and Jacobs, \{Cassandra L.\} and Yohei Oseki and Laurent Prevot and Enrico Santus",

booktitle = "CMCL 2022 - Workshop on Cognitive Modeling and Computational Linguistics, Proceedings of the Workshop",

}

Kodner, J 2022, Modeling the Relationship between Input Distributions and Learning Trajectories with the Tolerance Principle. in E Chersoni, N Hollenstein, CL Jacobs, Y Oseki, L Prevot & E Santus (eds), CMCL 2022 - Workshop on Cognitive Modeling and Computational Linguistics, Proceedings of the Workshop. CMCL 2022 - Workshop on Cognitive Modeling and Computational Linguistics, Proceedings of the Workshop, Association for Computational Linguistics (ACL), pp. 61-67, 12th Workshop on Cognitive Modeling and Computational Linguistics, CMCL 2022, Dublin, Ireland, 05/26/22. https://doi.org/10.18653/v1/2022.cmcl-1.7

Modeling the Relationship between Input Distributions and Learning Trajectories with the Tolerance Principle. / Kodner, Jordan.
CMCL 2022 - Workshop on Cognitive Modeling and Computational Linguistics, Proceedings of the Workshop. ed. / Emmanuele Chersoni; Nora Hollenstein; Cassandra L. Jacobs; Yohei Oseki; Laurent Prevot; Enrico Santus. Association for Computational Linguistics (ACL), 2022. p. 61-67 (CMCL 2022 - Workshop on Cognitive Modeling and Computational Linguistics, Proceedings of the Workshop).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

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AB - Child language learners develop with remarkable uniformity, both in their learning trajectories and ultimate outcomes, despite major differences in their learning environments. In this paper, we explore the role that the frequencies and distributions of irregular lexical items in the input plays in driving learning trajectories. I conclude that while the Tolerance Principle, a type-based model of productivity learning, accounts for inter-learner uniformity, it also interacts with input distributions to drive cross-pattern variation in learning trajectories.

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Kodner J. Modeling the Relationship between Input Distributions and Learning Trajectories with the Tolerance Principle. In Chersoni E, Hollenstein N, Jacobs CL, Oseki Y, Prevot L, Santus E, editors, CMCL 2022 - Workshop on Cognitive Modeling and Computational Linguistics, Proceedings of the Workshop. Association for Computational Linguistics (ACL). 2022. p. 61-67. (CMCL 2022 - Workshop on Cognitive Modeling and Computational Linguistics, Proceedings of the Workshop). doi: 10.18653/v1/2022.cmcl-1.7

Modeling the Relationship between Input Distributions and Learning Trajectories with the Tolerance Principle

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