Automated vocal analysis of naturalistic recordings from children with autism, language delay, and typical development

By D. Kimbrough Oller, Partha Niyogi, S. Gray, J. Richards, Jill Gilkerson, Dong Xu, Umit Yapanel, S. Warren. Proceedings of the National Academy of Sciences of the United States of America, 2010

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Predicting the birth of a spoken word (2015, background): “Word frequencies can easily be calculated from transcripts (7, 8), and overall quantity can even be estimated via automated methods (10).”
Talking to children matters: Early language experience strengthens processing and builds vocabulary (2013, background): “The accuracy of these estimates for English-language recordings has been established in previous studies (Oetting, Hartfield, & Pruitt, 2009; Oller et al., 2010; Xu et al., 2009).”
SAYCam: A Large, Longitudinal Audiovisual Dataset Recorded From the Infant’s Perspective (2020, background): “From the roots of children’s language learning to their experiences with objects and faces, naturalistic data about children’s home environment provides an important constraint on theories of development (Fausey et al., 2016; MacWhinney, 2000; Oller et al., 2010).”
Mapping the Early Language Environment Using All-Day Recordings and Automated Analysis. (2017, methodology): “For more detail on LENA System processing, see Oller et al. (2010) and Xu et al. (2008a, 2008b).”