Semantic Cues Facilitate Structural Generalizations in Artificial Language Learning

ABSTRACT

Natural languages contain systematic relationships between verb meaning and verb argument structure. Artificial language learning studies typically remove those relationships and instead pair verb meanings randomly with structures. Adult participants in such studies can detect statistical regularities associated with words in these languages and their use of novel words will adhere to those statistical regularities. However, word use in natural languages is associated with more than distributional statistics. Using an artificial language learning paradigm, we asked how a relationship between verb meaning and sentence structure affected learning and structure generalization. Twenty-four English-speaking adults watched videos described in an artificial language with two possible sentence structures. Half of the participants (statistics-only condition) learned a language with no relationship between verb meaning and sentence structure. The other half (semantics condition) learned a language in which verb meaning predicted which structures a verb occurred in. Although all learners were able to comprehend the learned structures with novel verbs, participants in the semantics conditions made grammaticality judgments and productions with novel verbs that were more consistent with the target language than participants in the statistics-only condition. The availability of semantic cues to verb subcategory supports artificial language learning.

Acknowledgments

This research was funded by NIH T32 MH067556-05, NSF-BCS 0921012 to JS, and NIH P20 GM103505 (Pilot funding to EC, Mark McCourt, PI). The content is solely the responsibility of the authors and does not necessarily reflect the views of the NSF or NIH. We thank the members of the Harvard Laboratory for Developmental Studies for comments on the design and Chelsea Sargent, Garrett Bowen, Matthew Kramer, Rachel Helgeson, Shaun Anderson, and Kathryn Dockter for assistance creating stimuli, running participants and organizing data. We also thank three anonymous reviewers for their constructive comments on a previous version of the manuscript.

Disclosure statement

No potential conflict of interest was reported by the author(s).

Notes

¹ In the language used by Wonnacott et al. (2008), all verbs described simple transitive events, mostly involving brief contact, although some involved a change in location or posture. Critically, the structural properties of those verbs were completely randomized across participants and meaning never predicted subclass.

Additional information

Funding

The work was supported by the National Science Foundation, Division of Behavioral and Cognitive Sciences [0921012]; National Institutes of Health [P20 GM103505].