Early Linguistic Productivity

Acquisition of English Determiners When do children start to develop abstract representations of language structure? In this paper, we use a hiererchical Bayesian model to look for evidence of grammatical generalization in children’s earliest use of articles (“a”, “an,” and “the”). The model, when applied to a large set of longitudinal, developmental corporal, yields evidence of minimal generalization before two years of age, but a rapid increase thereafter. Joint work with Dr. Michael C. Frank, Dr. Roger Levy, and Brandon Roy.

Meylan, S.C., Frank, M.C., Roy, B.C., and Levy, R. (2017). The emergence of an abstract grammatical category in children’s early speech. Psychological Science, 28 (2), pp. 181–192. (pdf)

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Acquisition of the English Regular Plural While English-learning children begin using the regular plural (+s) in their everyday speech around 20 months, it is less clear whether they use it an adult-like way. In this study, we systematically test both what children say as well as what they understand from the speech of others in a lab-based experiment. We find that children between 2 and 3 use the plural—including forming novel plurals—in their own speech, while failing to understand it when used by adults. Children successfully apply a +s rule to derive novel plurals (nops, teps) long mastering familiar plurals (cats, dogs, etc.), suggesting that generalizations emerge early and play a part in the processes of word learning and phoneme sequence discrimination learning.

Meylan, S.C., Levy, R.P., and Bergelson, E. (2020). Children’s Expressive and Receptive Knowledge of the English Regular Plural. Proceedings of the 42nd Annual Meeting of the Cognitive Science Society. (pdf, 5-min talk on YouTube)

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Robust Speech Processing in Adults

Telephone is a web-based experimental platform for running large-scale audio-based games of telephone with adult participants. This process of reptition—called serial transmission by researchers—yields datasets with very special statistical properties that can provide valuable insights regarding the mechanisms underlying human speech regconition. The yielded data is especially useful for evaluating probabilistic models of language structure, and can even be used as a data source for constructing better speech recognition models. Joint work with Sathvik Nair and Dr. Tom Griffiths.

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Caregiver Contributions to L1 Language Learning

While the phenomenon of “child-directed speech” has received considerable attention, how adults listen to children is much less well understood. This is potentially especially important in that adult interpretations (and actions) may be the key to understanding how children’s goal-driven behaviors (like locomotion and grasping) come to include language use. In this work, we show the prevalence of adult recoveries of words that are inconsistent with what children actually said, and demonstrate that this is consistent with a neural model of adult linguistic expectations.

Meylan, S.C., Bergelson, E., and Levy, R.P. (2020). Characterizing Child-Directed Listening with Corpus and Model-based Analyses. 22nd Biennial International Conference of Infant Studies. (pdf, 15-min talk on YouTube)

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Tools for Studying Early Language Acquisition

childes-db is a set of software tools for cognitive scientists, psychologists, and linguists who want to work with child language corpora in the Child Language Data Exchange System (CHILDES). childes-db provides a versioned set of reference parsings, direct MySQL access, an R API, and web-based visualizations for many common tasks. Joint work with Alessandro Sanchez, Mika Braginsky, Kyle MacDonald, Dr. Dan Yurovsky, and Dr. Michael C. Frank.

*Sanchez, A., *Meylan, S.C., Braginsky, M., MacDonald, K.E., Yurovsky, D., and Frank, M.C. (2019). childes-db: A flexible and reproducible interface to the child language data exchange system. Behavior Research Methods, 51 (4), pp. 1928–1941. (pdf)
*co-first authorship

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Wordful is a smartphone app for tracking early vocabulary growth. Wordful builds on proven checklist-based methods to support more engaging, high-touch longitudinal studies of language acquistion, with model-based sampling logic. Multiple caregivers can contribute data for the same child, and each caregiver can contribute data to multiple children. A powerful scheduling and templating system means that the app is highly extensible, and can be customized for many kinds of longitudinal studies of language development.

Meylan, S., Braginsky, M., DeMayo, B., Sanchez, A., Schonberg, C., Srinivasan, M., Vlach, H., Lupyan, G., Griffiths, T., and Frank, M. (2019). Wordful : Tracking Early Productive Vocabulary Growth With Smartphones. 44th Annual Boston University Conference on Language Development. (pdf)

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