Literature DB >> 28418456

Mapping the Early Language Environment Using All-Day Recordings and Automated Analysis.

Jill Gilkerson1, Jeffrey A Richards1, Steven F Warren2, Judith K Montgomery3, Charles R Greenwood4, D Kimbrough Oller5, John H L Hansen6, Terrance D Paul1.   

Abstract

PURPOSE: This research provided a first-generation standardization of automated language environment estimates, validated these estimates against standard language assessments, and extended on previous research reporting language behavior differences across socioeconomic groups.
METHOD: Typically developing children between 2 to 48 months of age completed monthly, daylong recordings in their natural language environments over a span of approximately 6-38 months. The resulting data set contained 3,213 12-hr recordings automatically analyzed by using the Language Environment Analysis (LENA) System to generate estimates of (a) the number of adult words in the child's environment, (b) the amount of caregiver-child interaction, and (c) the frequency of child vocal output.
RESULTS: Child vocalization frequency and turn-taking increased with age, whereas adult word counts were age independent after early infancy. Child vocalization and conversational turn estimates predicted 7%-16% of the variance observed in child language assessment scores. Lower socioeconomic status (SES) children produced fewer vocalizations, engaged in fewer adult-child interactions, and were exposed to fewer daily adult words compared with their higher socioeconomic status peers, but within-group variability was high.
CONCLUSIONS: The results offer new insight into the landscape of the early language environment, with clinical implications for identification of children at-risk for impoverished language environments.

Entities:  

Mesh:

Year:  2017        PMID: 28418456      PMCID: PMC6195063          DOI: 10.1044/2016_AJSLP-15-0169

Source DB:  PubMed          Journal:  Am J Speech Lang Pathol        ISSN: 1058-0360            Impact factor:   2.408


  30 in total

1.  Learning words through overhearing.

Authors:  N Akhtar; J Jipson; M A Callanan
Journal:  Child Dev       Date:  2001 Mar-Apr

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

Authors:  D K Oller; P Niyogi; S Gray; J A Richards; J Gilkerson; D Xu; U Yapanel; S F Warren
Journal:  Proc Natl Acad Sci U S A       Date:  2010-07-19       Impact factor: 11.205

3.  The significance of pauses in spontaneous speech.

Authors:  S R Rochester
Journal:  J Psycholinguist Res       Date:  1973-03

4.  Responsive parenting: establishing early foundations for social, communication, and independent problem-solving skills.

Authors:  Susan H Landry; Karen E Smith; Paul R Swank
Journal:  Dev Psychol       Date:  2006-07

5.  A longitudinal investigation of the role of quantity and quality of child-directed speech in vocabulary development.

Authors:  Meredith L Rowe
Journal:  Child Dev       Date:  2012-06-20

6.  Parental sensitivity and attachment in children with autism spectrum disorder: comparison with children with mental retardation, with language delays, and with typical development.

Authors:  Marinus H van Ijzendoorn; Anna H Rutgers; Marian J Bakermans-Kranenburg; Sophie H N Swinkels; Emma van Daalen; Claudine Dietz; Fabienne B A Naber; Jan K Buitelaar; Herman van Engeland
Journal:  Child Dev       Date:  2007 Mar-Apr

7.  Using the Language Environment Analysis (LENA) system in preschool classrooms with children with autism spectrum disorders.

Authors:  Jessica R Dykstra; Maura G Sabatos-Devito; Dwight W Irvin; Brian A Boyd; Kara A Hume; Sam L Odom
Journal:  Autism       Date:  2012-07-02

8.  What automated vocal analysis reveals about the vocal production and language learning environment of young children with autism.

Authors:  Steven F Warren; Jill Gilkerson; Jeffrey A Richards; D Kimbrough Oller; Dongxin Xu; Umit Yapanel; Sharmistha Gray
Journal:  J Autism Dev Disord       Date:  2010-05

9.  Maternal responsiveness to young children at three ages: longitudinal analysis of a multidimensional, modular, and specific parenting construct.

Authors:  Marc H Bornstein; Catherine S Tamis-Lemonda; Chun-Shin Hahn; O Maurice Haynes
Journal:  Dev Psychol       Date:  2008-05

10.  Using Language ENvironment Analysis to improve outcomes for children who are deaf or hard of hearing.

Authors:  Miranda Aragon; Christine Yoshinaga-Itano
Journal:  Semin Speech Lang       Date:  2012-10-18       Impact factor: 1.761

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  46 in total

1.  A survey on the attitudes of parents with young children on in-home monitoring technologies and study designs for infant research.

Authors:  Laurel A Fish; Emily J H Jones
Journal:  PLoS One       Date:  2021-02-05       Impact factor: 3.240

2.  The education word gap emerges by 18 months: findings from an Australian prospective study.

Authors:  Mary E Brushe; John Lynch; Sheena Reilly; Edward Melhuish; Murthy N Mittinty; Sally A Brinkman
Journal:  BMC Pediatr       Date:  2021-05-21       Impact factor: 2.125

3.  A meta-analysis of the predictability of LENA™ automated measures for child language development.

Authors:  Yuanyuan Wang; Rondeline Williams; Laura Dilley; Derek M Houston
Journal:  Dev Rev       Date:  2020-06-11

4.  The Distributed L1 and L2 Language-Learning Environments of Dual Language Learners Across Home and School Settings.

Authors:  Pui Fong Kan; Annaliese Miller; Shirley Cheung; Angela Brickman
Journal:  Lang Speech Hear Serv Sch       Date:  2020-07-10       Impact factor: 2.983

5.  Automated Language Environment Analysis: A Research Synthesis.

Authors:  Charles R Greenwood; Alana G Schnitz; Dwight Irvin; Shu Fe Tsai; Judith J Carta
Journal:  Am J Speech Lang Pathol       Date:  2018-05-03       Impact factor: 2.408

6.  Look who's talking: A comparison of automated and human-generated speaker tags in naturalistic day-long recordings.

Authors:  Federica Bulgarelli; Elika Bergelson
Journal:  Behav Res Methods       Date:  2020-04

7.  How effective is LENA in detecting speech vocalizations and language produced by children and adolescents with ASD in different contexts?

Authors:  Rebecca M Jones; Daniela Plesa Skwerer; Rahul Pawar; Amarelle Hamo; Caroline Carberry; Eliana L Ajodan; Desmond Caulley; Melanie R Silverman; Shannon McAdoo; Steven Meyer; Anne Yoder; Mark Clements; Catherine Lord; Helen Tager-Flusberg
Journal:  Autism Res       Date:  2019-01-14       Impact factor: 5.216

8.  Beyond the 30-Million-Word Gap: Children's Conversational Exposure Is Associated With Language-Related Brain Function.

Authors:  Rachel R Romeo; Julia A Leonard; Sydney T Robinson; Martin R West; Allyson P Mackey; Meredith L Rowe; John D E Gabrieli
Journal:  Psychol Sci       Date:  2018-02-14

9.  Cognitive Stimulation as a Mechanism Linking Socioeconomic Status With Executive Function: A Longitudinal Investigation.

Authors:  Maya L Rosen; McKenzie P Hagen; Lucy A Lurie; Zoe E Miles; Margaret A Sheridan; Andrew N Meltzoff; Katie A McLaughlin
Journal:  Child Dev       Date:  2019-10-08

10.  Biological aging in childhood and adolescence following experiences of threat and deprivation: A systematic review and meta-analysis.

Authors:  Natalie L Colich; Maya L Rosen; Eileen S Williams; Katie A McLaughlin
Journal:  Psychol Bull       Date:  2020-08-03       Impact factor: 17.737

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