About this session

Friday, 11:30 AM - 1:00 PM

Methodological Insights for Analyzing Children’s Diverse Language Environments and Development with Daylong Audio Recordings

Examining how children’s language environments shape development has been of interest to researchers for decades. To assess language environments, it is essential to obtain reliable and representative data of what children usually hear. However, gathering and processing recordings of naturalistic language environments is time-consuming and labor-intensive. A burgeoning literature using Language ENvironment Analysis (LENA) has arisen to address this issue with a lightweight audio recording device that fits in a child’s t-shirt pocket with a proprietary algorithm that processes the audio signal. LENA can automatically analyze hours of data into several metrics such as adult word count, child vocalizations, conversational turns, and more. While the benefits of quick, large-scale language processing are clear, many questions remain regarding the validity of LENA output and how to maximize its potential. This symposium offers methodological insights for analyzing children’s language environments with daylong recordings across socioeconomically, linguistically, and developmentally diverse populations. The first talk examines how language sampling changes the relationship between two commonly used LENA metrics: conversational turns and children’s vocalizations. The second talk investigates reliable sampling rates for measuring lexical diversity. The third talk focuses on how LENA metrics change whether and how periods of sleep are excluded. Finally, the last talk explores how LENA can predict language growth in children at increased familial likelihood for autism and language disorder. Overall, this symposium will provide valuable insights into effective approaches for analyzing daylong recordings to measure children’s language environments and their associations with child development accurately.

Paper #1
Title	Disentangling the Relation between Conversational Turns and Children’s Talkativeness
Presenting author	Alexus Ramirez, University of Maryland, College Park, United States

Paper #2
Title	Complexity in Bilingual Infant-Directed Speech: Establishing Reliable Random Sampling and Segmentation Strategies for Daylong Recordings
Presenting author	Nicola Phillips, McGill University, Canada

Paper #3
Title	Finding Signal in Noise: Human vs. Machine-learning Approaches to Cleaning Daylong Recordings of Bilingual Preschoolers
Presenting author	Dr. Sarah Surrain, Ph.D., The Children’s Learning Institute at the University of Texas Health Science Center at Houston, United States

Paper #4
Title	Approaches to Predicting Expressive Language Growth in Infants at High and Low Likelihood for Autism
Presenting author	Jennifer Markfeld, Vanderbilt University, Vanderbilt Frist Center for Autism and Innovation, United States

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Session chair
Alexus Ramirez, University of Maryland, College Park, USA

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