The findings suggest that the neuronal processing of semantic information at sentence level is atypical in preschoolers with SLI compared with TD children.
Language is a universal human ability, acquired readily by young children who otherwise struggle with many basics of survival1,2. And yet, language is variable across individuals. Behavioral and experimental observations suggest that children’s linguistic skills vary with factors like socioeconomic status3, children’s gender4, and multilingualism5. 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 day-long, child-centered audio-recordings of 1,001 2- to 48-month-olds from 12 countries spanning 6 continents across urban, farmer-forager, and subsistence-farming contexts. As expected, age and language-relevant clinical risks and diagnoses6 strongly correlated with how much speech (and speech-like vocalization) children produced. Critically, so too did adult talk in children’s environments: Children who heard less talk from adults produced less speech. In contrast to previous conclusions based on more limited sampling methods and a different set of language proxies, socioeconomic status, child gender, and multilingualism were not associated with children’s productions over the first four years of life. These findings from large-scale naturalistic data advance our understanding of what factors are robust predictors of variability in language behaviors of young learners in a wide range of everyday contexts.
Purpose This study compares online word recognition and prediction in preschoolers with (a suspicion of) a developmental language disorder (DLD) and typically developing (TD) controls. Furthermore, it investigates correlations between these measures and the link between online and off-line language scores in the DLD group. Method Using the visual world paradigm, Dutch children ages 3;6 (years;months) with (a suspicion of) DLD ( n = 51) and TD peers ( n = 31) listened to utterances such as, “Kijk, een hoed!” ( Look, a hat! ) in a word recognition task, and sentences such as, “Hé, hij leest gewoon een boek” (literal translation: Hey, he reads just a book ) in a word prediction task, while watching a target and distractor picture. Results Both groups demonstrated a significant word recognition effect that looked similar directly after target onset. However, the DLD group looked longer at the target than the TD group and shifted slower from the distractor to target pictures. Within the DLD group, word recognition was linked to off-line expressive language scores. For word prediction, the DLD group showed a smaller effect and slower shifts from verb onset compared to the TD group. Interestingly, within the DLD group, prediction behavior varied considerably, and was linked to receptive and expressive language scores. Finally, slower shifts in word recognition were related to smaller prediction effects. Conclusions While the groups' word recognition abilities looked similar, and only differed in processing speed and dwell time, the DLD group showed atypical verb-based prediction behavior. This may be due to limitations in their processing capacity and/or their linguistic knowledge, in particular of verb argument structure.
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. Method: Ninety-nine 2- to 4-year-old toddlers participated: 59 with (a suspicion of) DLD and 40 with TD. LENA metrics on adult word count, conversational turn count, and child vocalization count were obtained. For all children, data on parental education and multilingualism were available. In the DLD group, data were collected on receptive and expressive vocabulary and grammar, and on nonverbal intelligence, using standardized tests. Results: We found lower adult word count, conversational turn count, and child vocalization count in the DLD group, independent of multilingualism but not of parental education. In the DLD group, receptive vocabulary was related to conversational turn count and child vocalization count, but not to adult word count. Expressive vocabulary, receptive grammar, and expressive grammar were not related to LENA metrics. Conclusions: Toddlers with (a suspicion of) DLD vocalize less at home than children with TD. They also hear fewer adult words and experience fewer conversational turns. Children with DLD's language outcomes are to a limited extent related to language environment at home. Conversational turns and child vocalizations are in this respect more important than adult words, in line with findings for TD populations.
A cross-modal identity priming experiment examined whether subphonemic variation (length of prevoicing in syllable-initial stops in Dutch) influences lexical access. Word and nonword targets began with voiced plosives. They were chosen so that half of them became words when the initial voiced plosive was replaced by its voiceless counterpart, while the other half changed into nonwords. The visual targets were preceded by auditory word or nonword primes which were either phonologically unrelated or identical to the target. The initial plosives of the identity primes had 0, 6, or 12 periods of prevoicing, but all were identified as voiced. This VOT manipulation had no effect for word targets: lexical decisions were faster after all three identity primes than after the unrelated primes. However, reaction times to nonword targets with word competitors (e.g., BRINS, with the competitor PRINS ‘‘prince’’) were slower when preceded by identity primes without prevoicing than when preceded by primes starting with 6 or 12 periods of prevoicing. This suggests that voiceless competitors are activated by words starting with voiced plosives without prevoicing. Subphonemic variation appears to influence the degree of lexical activation, but this effect depends on the lexical competitor environment.
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