A model of rapid phonotactic generalization

Tal Linzen, Timothy J. O'Donnell

    Research output: Chapter in Book/Report/Conference proceedingConference contribution


    The phonotactics of a language describes the ways in which the sounds of the language combine to form possible morphemes and words. Humans can learn phonotactic patterns at the level of abstract classes, generalizing across sounds (e.g., "words can end in a voiced stop"). Moreover, they rapidly acquire these generalizations, even before they acquire soundspecific patterns. We present a probabilistic model intended to capture this earlyabstraction phenomenon. The model represents both abstract and concrete generalizations in its hypothesis space from the outset of learning. This-combined with a parsimony bias in favor of compact descriptions of the input data-leads the model to favor rapid abstraction in a way similar to human learners.

    Original languageEnglish (US)
    Title of host publicationConference Proceedings - EMNLP 2015
    Subtitle of host publicationConference on Empirical Methods in Natural Language Processing
    PublisherAssociation for Computational Linguistics (ACL)
    Number of pages6
    ISBN (Electronic)9781941643327
    StatePublished - 2015
    EventConference on Empirical Methods in Natural Language Processing, EMNLP 2015 - Lisbon, Portugal
    Duration: Sep 17 2015Sep 21 2015

    Publication series

    NameConference Proceedings - EMNLP 2015: Conference on Empirical Methods in Natural Language Processing


    OtherConference on Empirical Methods in Natural Language Processing, EMNLP 2015

    ASJC Scopus subject areas

    • Computational Theory and Mathematics
    • Computer Science Applications
    • Information Systems


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