DevSci Colloquium: Meg Cychosz (HESP)
Harnessing Children’s Messy, Naturalistic Environments to Understand Speech and Language Development
Abstract: Children learn the patterns of their native language(s) from years spent interacting and observing in their everyday environments. How can we model these daily experiences at a large scale? It is no longer a question of if sufficiently comprehensive datasets can be constructed, but rather how to harness these messy, naturalistic observations of how children and their caregivers communicate. In this talk, I will present recent work illustrating several different methods of analyzing longform audio recordings of children’s everyday lives to understand their speech and language development. Doing so allows me to compare the learning experiences of infants and children from a variety of backgrounds (large cross-cultural samples, children with hearing loss) to better understand how all children develop speech and language.
Bio: Meg Cychosz is an NIH-NIDCD postdoctoral researcher in the Department of Hearing and Speech Sciences and Center for Comparative and Evolutionary Biology of Hearing at the University of Maryland-College Park. She employs computational modeling and digital signal processing to study how the auditory environment and speech-motor apparatus interact to shape human speech patterns. Currently, she is examining these questions in cochlear implant users. She earned a Master 1 in Phonetics from Université Sorbonne Nouvelle-Paris 3 in 2015, a Ph.D. in Linguistics from UC Berkeley in 2020, and is an incoming assistant professor in the Department of Linguistics at UCLA.
