Preprint

Stratification without morphological strata, syllable counting without counts - modelling English stress assignment with Naive Discriminative Learning

This article is a preprint and has not been certified by peer review [What does this mean?].

Author(s) / Creator(s)

Arndt-Lappe, Sabine
Schrecklinger, Robin
Tomaschek, Fabian

Abstract / Description

Stress position in English words is well-known to correlate with both their morphological properties and their phonological organisation in terms of non-segmental, prosodic categories like syllable and foot structure. While two generalisations capturing this correlation, directionality and strati cation, are well established, the exact nature of the interaction of phonological and morphological factors in English stress assignment is a much debated issue in the literature. The present study investigates if and how directionality and strati cation e ects in English can be learned by means of Naive Discriminative Learning, a computational model that is trained using error-driven learning and that does not make any a-priori assumptions about the higher-level phonological organisation and morphological structure of words. Based on a series of simulation studies we show that neither directionality nor strati cation need to be stipulated as a-priori properties of words or constraints in the lexicon. Stress can be learned solely on the basis of very at word representations. Morphological strati cation emerges as an e ect of the model learning that informativity with regard to stress position is unevenly distributed across all trigrams constituting a word. Morphological a x classes like stress-preserving and stress-shifting a xes are, hence, not prede ned classes but sets of trigrams that have similar informativity values with regard to stress position. Directionality, by contrast, emerges as spurious in our simulations; no syllable counting or recourse to abstract prosodic representations seems to be necessary to learn stress position in English.

Keyword(s)

naive discriminative learning error-driven learning morphological strata stress assignment directionality

Persistent Identifier

Date of first publication

2021-09-04

Publisher

PsychArchives

Is version of

Citation

Arndt-Lappe, S., Schrecklinger, R., & Tomaschek, F. (2021). Strati cation without morphological strata, syllable counting without counts - modelling English stress assignment with Naive Discriminative Learning. PsychArchives. https://doi.org/10.23668/PSYCHARCHIVES.5082
  • Author(s) / Creator(s)
    Arndt-Lappe, Sabine
  • Author(s) / Creator(s)
    Schrecklinger, Robin
  • Author(s) / Creator(s)
    Tomaschek, Fabian
  • PsychArchives acquisition timestamp
    2021-09-04T09:21:48Z
  • Made available on
    2021-09-04T09:21:48Z
  • Date of first publication
    2021-09-04
  • Abstract / Description
    Stress position in English words is well-known to correlate with both their morphological properties and their phonological organisation in terms of non-segmental, prosodic categories like syllable and foot structure. While two generalisations capturing this correlation, directionality and strati cation, are well established, the exact nature of the interaction of phonological and morphological factors in English stress assignment is a much debated issue in the literature. The present study investigates if and how directionality and strati cation e ects in English can be learned by means of Naive Discriminative Learning, a computational model that is trained using error-driven learning and that does not make any a-priori assumptions about the higher-level phonological organisation and morphological structure of words. Based on a series of simulation studies we show that neither directionality nor strati cation need to be stipulated as a-priori properties of words or constraints in the lexicon. Stress can be learned solely on the basis of very at word representations. Morphological strati cation emerges as an e ect of the model learning that informativity with regard to stress position is unevenly distributed across all trigrams constituting a word. Morphological a x classes like stress-preserving and stress-shifting a xes are, hence, not prede ned classes but sets of trigrams that have similar informativity values with regard to stress position. Directionality, by contrast, emerges as spurious in our simulations; no syllable counting or recourse to abstract prosodic representations seems to be necessary to learn stress position in English.
    en
  • Publication status
    unknown
    en
  • Review status
    peerReviewed
    en
  • Sponsorship
    Support for this research was provided by the Deutsche Forschungsgemeinschaft, grant FOR 2373
    en
  • Citation
    Arndt-Lappe, S., Schrecklinger, R., & Tomaschek, F. (2021). Strati cation without morphological strata, syllable counting without counts - modelling English stress assignment with Naive Discriminative Learning. PsychArchives. https://doi.org/10.23668/PSYCHARCHIVES.5082
    en
  • Persistent Identifier
    https://hdl.handle.net/20.500.12034/4506
  • Persistent Identifier
    https://doi.org/10.23668/psycharchives.5082
  • Language of content
    eng
  • Publisher
    PsychArchives
    en
  • Is version of
    https://doi.org/10.1007/s11525-022-09399-9
  • Keyword(s)
    naive discriminative learning
    en
  • Keyword(s)
    error-driven learning
    en
  • Keyword(s)
    morphological strata
    en
  • Keyword(s)
    stress assignment
    en
  • Keyword(s)
    directionality
    en
  • Dewey Decimal Classification number(s)
    150
  • Title
    Stratification without morphological strata, syllable counting without counts - modelling English stress assignment with Naive Discriminative Learning
    en
  • DRO type
    preprint
    en
  • Leibniz subject classification
    Sprache, Linguistik
    de_DE
  • Visible tag(s)
    Linguistics
    en
  • Visible tag(s)
    morphology
    en
  • Visible tag(s)
    phonology
    en
  • Visible tag(s)
    computational modelling
    en