When
Sara Benham, Ph.D., CCC-SLP
Assistant Professor
College of Nursing and Health Sciences
University of Vermont
Zoom: https://arizona.zoom.us/j/86020102033
Leveraging tools of network science to characterize sound and word learning in children with typical and atypical language development
The application of network science to empirical paradigms in cognitive and linguistic processing has provided critical insights into the nature of the mental lexicon (e.g., Levy et al., 2021; Vitevitch et al., 2014). A growing area of research is the implementation of network science for detecting the structure and organization of word learning processes in children (Beckage et al., 2011; Stella et al., 2017). For many children, learning sounds and words unfolds seamlessly over time. However, for preschoolers with developmental language disorder (DLD), the process of mapping a phonological form to a referent results in difficulties in sound production accuracy and stability (Benham et al., 2018; Benham & Goffman, 2020; 2022). I will demonstrate how principles of network science, rooted in a graph theoretical approach, provide new insights into: 1) mechanisms of disorder for children with DLD; and 2) emergent patterns in young learners’ speech sound production. I will present findings from a series of studies in which children between the ages of 2 and 8 years with typical and atypical language development produce novel disyllabic words, some that are paired with a consistent visual referent, and some that are not. Using a combination of novel network science analyses and standard phonological measures, I show that, for preschoolers with DLD, the incorporation of a referent with a novel word form induces the production of stable syllable sequences, but does not affect segmental or phonetic feature accuracy. Typically developing children who are 2 years old show a different pattern of results: sound feature accuracy is disrupted by a referent, but not syllable organization. These findings elucidate the interactivity of words and sounds within the mental lexicon, and also point to new directions in our understanding of the phonological factors underpinning word learning. This work ultimately demonstrates how the study of phonology across key developmental periods can be enhanced by tools of network science, providing new insights into the shifting organization of sounds and words.
References
Beckage, N., Smith, L., & Hills, T. (2011). Small worlds and semantic network growth in typical and late talkers. PloS one, 6(5), e19348.
Benham, S., & Goffman, L. (2020). Lexical–semantic cues induce sound pattern stability in children with developmental language disorder. Journal of Speech, Language, and Hearing Research, 63(12), 4109-4126.
Benham, S., & Goffman, L. (2022). A longitudinal study of the phonological organisation of novel word forms in children with developmental language disorder. International journal of speech-language pathology, 24(2), 212-223.
Benham, S., Goffman, L., & Schweickert, R. (2018). An application of network science to phonological sequence learning in children with developmental language disorder. Journal of Speech, Language, and Hearing Research, 61(9), 2275-2291.
Levy, O., Kenett, Y. N., Oxenberg, O., Castro, N., De Deyne, S., Vitevitch, M. S., & Havlin, S. (2021). Unveiling the nature of interaction between semantics and phonology in lexical access based on multilayer networks. Scientific reports, 11(1), 14479.
Stella, M., Beckage, N. M., & Brede, M. (2017). Multiplex lexical networks reveal patterns in early word acquisition in children. Scientific reports, 7(1), 46730.
Vitevitch, M. S., Goldstein, R., Siew, C. S., & Castro, N. (2014). Using complex networks to understand the mental lexicon. In Yearbook of the Poznań Linguistic Meeting (Vol. 1, No. 1). Uniwersytet im. Adama Mickiewicza w Poznaniu.