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Learning Morphological Constructions

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The Construction of Words

Part of the book series: Studies in Morphology ((SUMO,volume 4))

Abstract

The great variability of morphological structure across languages makes it uncontroversial that morphology is learned. Yet, morphology presents formidable learning challenges, on par with those of syntax. This article takes a constructionist perspective in assuming that morphological constructions are a major outcome of the learning process. However, the existence of morphological paradigms in many languages suggests that they are often not the only outcome. The article reviews domain-general approaches to achieving this outcome. The primary focus is on mechanisms proposed within the associative/connectionist tradition, which are compared with Bayesian approaches. The issues discussed include the role of prediction and prediction error in learning, generative vs. discriminative learning models, directionality of associations, the roles of (unexpectedly) present vs. absent stimuli, general-to-specific vs. specific-to-general learning, and the roles of type and token frequency. In the process, the notion of a construction itself is shown to be more complicated that it first appears.

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Notes

  1. 1.

    Bayesian models make a similar prediction, except that competition occurs between inferred causes rather than predictive cues.

  2. 2.

    This result suggests that the difference between child and adult learners in Ramscar et al. (2013b) may be quantitative rather than qualitative in nature: children may be habituated by repetition more quickly than adults are, and therefore shift attention away from repeated stimuli more quickly than an adult would.

  3. 3.

    p(form|meaning) = p(form,meaning)/p(meaning), where p(form,meaning) is frequency of the form-meaning mapping and p(meaning) is the sum of these frequencies across all forms sharing a meaning. Assuming that forms sharing a meaning compete with each other for selection, with the outcome of this competition determined by relative schema strength, schema strength could be proportional to either frequency of the schema or the conditional probability of form given meaning without any consequences for the outcome of the competition.

  4. 4.

    One may also consider updating blig- in the opposite, non-normative direction based on the fact that unused connections are pruned.

  5. 5.

    This point is traditionally emphasized by error-driven models of learning, where unexpected means predicted but not observed. This point may therefore appear to be inconsistent with the Hebbian approach taken to modeling the data below, which does not rely on prediction. However, even in the Hebbian framework, in order to notice the absence of something, one needs to have experienced it. Otherwise, there is no representation for the absent stimulus in the learner’s mind.

  6. 6.

    Instead, unfaithful mappings might benefit from encountering the outputs of such mappings as a block at an early point during the experiment (a la Carvalho and Goldstone 2016), when the learner’s impression of what plural forms are like is still easily malleable.

  7. 7.

    With respect to form-meaning mappings, language calls for bidirectionality because a listener who encounters a form and links it to a meaning wishes to be able to reproduce what she just heard when expressing the same meaning. Similarly, when acquiring a morphological paradigm, one wishes to be able to fill in any form in a paradigm given any other form (Ackerman and Malouf 2013). Unfortunately, we know very little about directionality in paradigm learning (though see Jun and Albright 2017, for first steps in addressing this question).

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    Vsevolod Kapatsinski

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Kapatsinski, V. (2018). Learning Morphological Constructions. In: Booij, G. (eds) The Construction of Words. Studies in Morphology, vol 4. Springer, Cham. https://doi.org/10.1007/978-3-319-74394-3_19

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