Researchers recommend collecting repeated or prolonged natural language samples to supplement direct assessments and anecdotal reports in language studies for autistic children. Several studies have used the Language Environment Analysis® (LENA) system to collect language samples from autistic children. However, there has been little research that investigates the reliability of using the LENA system for autistic children in an educational setting such as a classroom. The current study compared language data disaggregated by the LENA system from 40 autistic children in educational settings with data from human coders. Specifically, we calculated three separate correlational and reliability analyses between the LENA system and human coders. Results showed that although the aggregated coefficients could be interpreted as fair, LENA systems should be used with caution due to high variability between the LENA system and human coders. Implications for future research and limitations are also discussed.

Background/Objectives: This study aimed to investigate whether day-long recordings with Language Environment Analysis (LENA) can be utilized in a hospital-based Auditory Verbal Therapy (AVT) program in Denmark for children with hearing loss and to conduct a pilot validation in the Danish language.

Recent advances in audiological early intervention and hearing technologies have significantly improved access to spoken language for children with hearing loss (CwHL), but many CwHL require additional support to match the language development of their peers with normal hearing (PwNH). Programmes such as It Takes Two to Talk®, the Hanen Program® and Talking Matters focus on supporting parents to enhance children’s language development in natural environments. Analysis of response types has become a significant trend, facilitated by technological developments like Language ENvironment Analysis (LENA®), which provides uninterrupted recordings and automated calculations of adult–child interactions. This research examined three child language measures, child vocalisation counts, total number of words, and mean length of utterance, comparing CwHL and PwNH. Transcribed excerpts of LENA recordings were coded to determine caregivers’ use of ‘high-level’ responses in exchanges with their children and were correlated with child language outcomes. The results confirm the crucial role of caregiver response types in enhancing child language outcomes and exemplify the bidirectional relationship of caregiver-child interactions. The findings add to the literature to suggest that families and educators would benefit from guidance and coaching to acquire and apply high-level response types during natural spoken language interactions with CwHL.

This study investigated language input (adult word count, AWC; conversational turn count, CTC; response types; high-, mid-, and low-level) and language outcomes (receptive, expressive) in children aged 2–5 years with hearing loss (CwHL) and those with normal hearing (CwNH). Associations between language input and outcomes, relationships between language input, and demographics were examined. Language input was analyzed using full-day Language Environment Analysis (LENA) audio-recordings, and language outcomes were assessed using standardized language assessments in 14 CwHL and 20 CwNH. There were no significant differences in language input between CwHL (AWC/hr: M = 1137, SD = 554; CTC/hr: M = 48.26, SD = 19.18) and CwNH (AWC/hr: M = 1243, SD = 426; CTC/hr: M = 60.94, SD = 21.34). There were, however, significant differences between groups in response types and language outcomes. Caregivers of CwHL used less high- and more mid- and low-level responses than caregivers of CwNH (p = < .01). Language input in CwHL showed no association with language outcomes, and there were no correlations with demographic factors. For CwNH, receptive language was correlated with AWC/hr, CTC/hr, and high- and low-level response types (p = < .01); and expressive language was correlated with AWC/hr (p = < .01), CTC/hr (p = .02), and high- (p = .02) and low-level (p = < .01) response types significantly. Correlations were negative for low-level response types, with lower language scores associated with relatively more use of low-level responses. For CwNH, maternal education correlated with AWC/hr (p = < .01), and caregivers of younger CwNH had significantly more CTC/hr (p = < .01). Quantitative LENA data suggested comparable interaction frequency between groups. CwHL were exposed to more low-level response types, had significantly lower language scores. Further investigation into response types, child language outcomes, and therapeutic implications for CwHL is needed.

Introduction: Previous studies underscore the importance of speech input, particularly infant-directed speech (IDS) during one-on-one (1:1) parent–infant interaction, for child language development. We hypothesize that infants’ attention to speech input, specifically IDS, supports language acquisition. In infants, attention and orienting responses are associated with heart rate deceleration. We examined whether individual differences in infants’ heart rate measured during 1:1 mother–infant interaction is related to speech input and later language development scores in a longitudinal study.

There is little systematically collected quantitative empirical data on how much linguistic input children in small-scale societies encounter, with some estimates suggesting low levels of directed speech. We report on an ecologically-valid analysis of speech experienced over the course of a day by young children (N = 24, 6–58 months old, 33% female) in a forager-horticulturalist population of lowland Bolivia. A permissive definition of input (i.e., including overlapping, background, and non-linguistic vocalizations) leads to massive changes in terms of input quantity, including a quadrupling of the estimate for overall input compared to a restrictive definition (only near and clear speech), while who talked to and around a focal child is relatively stable across input definitions. We discuss implications of these results for theoretical and empirical research into language acquisition.

Previous studies underscore the importance of social interactions for child language development— particularly interactions characterized by maternal sensitivity, infant-directed speech (IDS), and conversational turn-taking (CT) in one-on-one contexts. Although infants engage in such interactions from the third month after birth, the prospective link between speech input and maternal sensitivity in the first half year of life and later language development has been understudied. We hypothesized that social interactions embodying maternal sensitivity, IDS and CTs in the first 3 months of life, are significantly associated with later language development and tested this using a longitudinal design. Using a sample of 40 3-month-old infants, we assessed maternal sensitivity during a structured mother–infant one-on-one (1:1) interaction based on a well-validated scoring system (the Coding Interactive Behavior system). Language input (IDS, CT) was assessed during naturally occurring interactions at home using the Language ENvironment Analysis (LENA) system. Language outcome measures were obtained from 18 to 30 months of age using the MacArthur-Bates Communicative Development Inventory. Three novel findings emerged. First, maternal sensitivity at 3 months was significantly associated with infants’ productive language scores at 18, 21, 24, 27, and 30 months of age. Second, LENA-recorded IDS during mother–infant 1:1 interaction in the home environment at 3 months of age was positively correlated with productive language scores at 24, 27, and 30 months of age. Third, mother–infant CTs during 1:1 interaction was significantly associated with infants’ productive language scores at 27 and 30 months of age. We propose that infants’ social attention to speech during this early period—enhanced by sensitive maternal one-on-one interactions and IDS—are potent factors in advancing language development.

Introduction: There is substantial diversity within and between contexts globally in caregiving practices and family composition, which may have implications for the early interaction’s infants engage in. We draw on data from the Brain Imaging for Global Health (BRIGHT, www.globalfnirs.org/the-bright-project) project, which longitudinally examined infants in the UK and in rural Gambia, West Africa. In The Gambia, households are commonly characterized by multigenerational, frequently polygamous family structures, which, in part, is reflected in the diversity of caregivers a child spends time with. In this paper, we aim to 1) evaluate and validate the Language Environment Analysis (LENA) for use in the Mandinka speaking families in The Gambia, 2) examine the nature (i.e., prevalence of turn taking) and amount (i.e., adult and child vocalizations) of conversation that infants are exposed to from 12 to 24 months of age and 3) investigate the link between caregiver diversity and child language outcomes, examining the mediating role of contingent turn taking.

Non-random exploration of infant speech-like vocalizations (e.g., squeals, growls, and vowel-like sounds or “vocants”) is pivotal in speech development. This type of vocal exploration, often noticed when infants produce particular vocal types in clusters, serves two crucial purposes: it establishes a foundation for speech because speech requires formation of new vocal categories, and it serves as a basis for vocal signaling of wellness and interaction with caregivers. Despite the significance of clustering, existing research has largely relied on subjective descriptions and anecdotal observations regarding early vocal category formation. In this study, we aim to address this gap by presenting the first large-scale empirical evidence of vocal category exploration and clustering throughout the first year of life. We observed infant vocalizations longitudinally using all-day home recordings from 130 typically developing infants across the entire first year of life. To identify clustering patterns, we conducted Fisher’s exact tests to compare the occurrence of squeals versus vocants, as well as growls versus vocants. We found that across the first year, infants demonstrated clear clustering patterns of squeals and growls, indicating that these categories were not randomly produced, but rather, it seemed, infants actively engaged in practice of these specific categories. The findings lend support to the concept of infants as manifesting active vocal exploration and category formation, a key foundation for vocal language.

A growing body of research suggests that young children’s early speech and language exposure is associated with later language development (including delays and diagnoses), school readiness, and academic performance. The last decade has seen increasing use of child-worn devices to collect long-form audio recordings by educators, economists, and developmental psychologists. The most commonly used system for analyzing this data is LENA, which was trained on North American English child-centered data and generates estimates of children’s speech-like vocalization counts, adult word counts, and child-adult turn counts. Recently, cheaper and open-source non-LENA alternatives with multilingual training have been proposed. Both kinds of systems have been employed in under-resourced, sometimes multilingual contexts, including Africa, where access to printed or digital linguistic resources may be limited. In this paper, we describe each kind of system (LENA, non-LENA), provide information on audio data collected with them that is available for reuse, review evidence of the accuracy of extant automated analyses, and note potential strengths and shortcomings of their use in African communities.

Automated methods for processing of daylong audio recordings are efficient and may be an effective way of assessing developmental stage for typically developing children; however, their utility for children with developmental disabilities may be limited by constraints of algorithms and the scope of variables produced. Here, we present a novel utterance-level processing (ULP) system that 1) extracts utterances from daylong recordings, 2) verifies automated speaker tags using human annotation, and 3) provides vocal maturity metrics unavailable through automated systems. Study 1 examines the reliability and validity of this system in low-risk controls (LRC); Study 2 extends the ULP to children with Angelman syndrome (AS). Results showed that ULP annotations demonstrated high coder agreement across groups. Further, ULP metrics aligned with language assessments for LRC but not AS, perhaps reflecting limitations of language assessments in AS. We argue that ULP increases accuracy, efficiency, and accessibility of detailed vocal analysis for syndromic populations.

Purpose: This study evaluates the extent to which automated indices of vocal development are stable and valid for predicting language in infants at increased familial likelihood for autism and/or language impairment and relatively lower likelihood infants.

Classroom engagement plays a crucial role in preschoolers’ development, yet the correlates of engagement, especially among children with Autism Spectrum Disorder (ASD) and developmental delays (DD), remains unknown. This study examines levels of engagement with classroom social partners and tasks among children in three groups ASD, DD, and typical development (TD). Here, we asked whether children’s vocal interactions (vocalizations to and from peers and teachers) were associated with their classroom engagement with social partners (peers and teachers) and with tasks, and whether the association between classroom engagement and vocal interactions differed between children in the ASD group and their peers in the DD and TD groups. Automated measures of vocalizations and location quantified children’s vocal interactions with peers and teachers over the course of the school year. Automated location and vocalization data were used to capture both (1) children’s vocal output to specific peers and teachers, and (2) the vocal input they received from those peers and teachers. Participants were 72 3–5-year-olds (Mage = 48.6 months, SD = 7.0, 43% girls) and their teachers. Children in the ASD group displayed lower engagement with peers, teachers, and tasks than children in the TD group; they also showed lower engagement with peers than children in the DD group. Overall, children’s own vocalizations were positively associated with engagement with social partners. Thus, although children in the ASD group tend to have lower engagement scores than children in the TD group, active participation in vocal interactions appears to support their classroom engagement with teachers and peers.

Purpose: This study presents an exploration of facilitative language techniques (FLTs) used by fathers of children who are deaf or hard of hearing (DHH) in the natural environment.

Preschoolers’ language abilities are associated with their social interactions in early childhood classrooms. Few studies, however, have examined associations between social interactions and objective measures of children’s real-time classroom language environments, information key to informing interventions to support preschool children at risk for language delays. In this pilot study, we examined associations between objective measures of real-time language environments (input and output) recorded via the Language ENvironment Analysis (LENA) system and observations of children’s positive and negative interactions with peers and teachers in an early intervention classroom for children with developmental delays (n = 9, seven girls). Mixed effects regression models revealed associations between children’s language environments (input and output) and their social interactions with peers and teachers. More talkative children were more likely to have a high number of positive peer interactions. Children who received more language input from teachers were more likely to have a higher number of positive teacher–child interactions, an effect that was stronger for children with the lowest language output. The results of this pilot study build on prior research by using real-time objective measurement to examine how children’s language input from peers and teachers and children’s own language output supports positive interactions within early intervention classrooms.

Purpose: This study compares the home language environments of children with (a suspicion of) developmental language disorder (DLD) with that of children with typical development (TD). It does so by adopting new technology that automatically provides metrics about children’s language environment (Language ENvironment Analysis [LENA]). In addition, relationships between LENA metrics and standardized language tests are explored in the DLD group.

Language is a universal human ability, acquired readily by young children, who otherwise struggle with many basics of survival. And yet, language ability is variable across individuals. Naturalistic and experimental observations suggest that children’s linguistic skills vary with factors like socioeconomic status and children’s gender. But which factors really influence children’s day-to-day language use? Here, we leverage speech technology in a big-data approach to report on a unique cross-cultural and diverse data set: >2, 500 d-long, child-centered audio-recordings of 1, 001 2- to 48-mo-olds from 12 countries spanning six continents across urban, farmer-forager, and subsistence-farming contexts. As expected, age and language-relevant clinical risks and diagnoses predicted how much speech (and speech-like vocalization) children produced. Critically, so too did adult talk in children’s environments: Children who heard more talk from adults produced more speech. In contrast to previous conclusions based on more limited sampling methods and a different set of language proxies, socioeconomic status (operationalized as maternal education) was not significantly associated with children’s productions over the first 4 y of life, and neither were gender or multilingualism. These findings from large-scale naturalistic data advance our understanding of which factors are robust predictors of variability in the speech behaviors of young learners in a wide range of everyday contexts.

Purpose: We sought to examine second grade teachers’ word use throughout the school day to identify the amount and type of teacher vocabulary use across content areas as well as to examine relationships between this teacher talk and student language and literacy achievement.

Purpose: Measuring language input, especially for infants growing up in bilingual environments, is challenging. Although the ways to measure input have expanded rapidly in recent years, there are many unresolved issues. In this study, we compared different measurement units and sampling methods used to estimate bilingual input in naturalistic daylong recordings.

Objective: To test whether a neonatal intensive care unit-based language curriculum for families with preterm infants enhances the language environment and postdischarge Bayley Scales of Infant and Toddler Development (BSID)-III language and cognitive scores.