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Children who receive cochlear implants develop spoken language on a protracted timescale. The home environment facilitates speech-language development, yet it is relatively unknown how the environment differs between children with cochlear implants and typical hearing. We matched eighteen preschoolers with implants (31-65 months) to two groups of children with typical hearing: by chronological age and hearing age. Each child completed a long-form, naturalistic audio recording of their home environment (appx. 16 hours/child; >730 hours of observation) to measure adult speech input, child vocal productivity, and caregiver-child interaction. Results showed that children with cochlear implants and typical hearing were exposed to and engaged in similar amounts of spoken language with caregivers. However, the home environment did not reflect developmental stages as closely for children with implants, or predict their speech outcomes as strongly. Home-based speech-language interventions should focus on the unique input-outcome relationships for this group of children with hearing loss.

Purpose: Many studies have found a correlation between overall usage rates of nonmainstream forms and reading scores, but less is known about which dialect differences are most predictive. Here, we consider different methods of characterizing African American English use from existing assessments and examine which methods best predict literacy achievement. Method: Kindergarten and first-grade students who speak African American English received two assessments of dialect use and two assessments of decoding at the beginning and end of the school year. Item-level analyses of the dialect-use assessments were used to compute measures of dialect usage: (a) an overall feature rate measure based on the Diagnostic Evaluation of Language Variation-Screening Test, (b) a subscore analysis of the Diagnostic Evaluation of Language Variation-Screening Test based on items that pattern together, (c) an alternative assessment where children repeat and translate sentences, and (d) "repertoire" measures based on a categorical distinction of whether a child used a particular feature of mainstream American English. Results: Models using feature rate measures provided better data--model fit than those with repertoire measures, and baseline performance on a sentence repetition task was a positive predictor of reading score at the end of the school year. For phonological subscores, change from the beginning to end of the school year predicted reading at the end of the school year, whereas baseline scores were most predictive for grammatical subscores. Conclusions: The addition of a sentence imitation task is useful for understanding a child's dialect and anticipating potential areas for support in early literacy. We observed some support for the idea that morphological dialect differences (i.e., irregular verb morphology) have a particularly close tie to later literacy, but future work will be necessary to confirm this finding.

To learn language, children must map variable input to categories such as phones and words. How do children process variation and distinguish between variable pronunciations ("shoup" for "soup") versus new words? The unique sensory experience of children with cochlear implants, who learn speech through their device's degraded signal, lends new insight into this question. In a mispronunciation sensitivity eyetracking task, children with implants (N = 33), and typical hearing (N = 24; 36-66 months; 36F, 19M; all non-Hispanic white), with larger vocabularies processed known words faster. But children with implants were less sensitive to mispronunciations than typical hearing controls. Thus, children of all hearing experiences use lexical knowledge to process familiar words but require detailed speech representations to process variable speech in real time.

Speech produced by children is characterized by a high fundamental frequency which complicates measurement of vocal tract resonances, and hence coarticulation. Here two whole-spectrum measures of coarticulation are validated, one temporal and one spectral, that are less sensitive to these challenges. Using these measures, consonant-vowel coarticulation is calculated in the speech of a large sample of 4-year-old children. The measurements replicate known lingual coarticulatory findings from the literature, demonstrating the utility of these acoustic measures of coarticulation in speakers of all ages.

Children learn language by listening to speech from caregivers around them. However, the type and quantity of speech input that children are exposed to change throughout early childhood in ways that are poorly understood due to the small samples (few participants, limited hours of observation) typically available in developmental psychology. Here we used child‐centered audio recorders to unobtrusively measure speech input in the home to 292 children (aged 2–7 years), acquiring English in the United States, over 555 distinct days (approximately 8600 total hours of observation, or 29.62 h/child). These large timescales allowed us to compare how different dimensions of child‐directed speech input (quantity, burstiness) varied throughout early childhood. We then evaluated the relationship between each dimension of input and children's concurrent receptive vocabulary size. We found that the burstiness of speech input (spikes of words) was a stronger correlate with age than the quantity of speech input. Input burstiness was also a stronger predictor than input quantity for children's vocabulary size: children who heard spiky, more intense bouts of input had larger vocabularies. Overall, these results reaffirm the importance of speech input in the home for children's language development and support exposure–consolidation models of early language development. [ABSTRACT FROM AUTHOR]

Much research in child speech development suggests that young children coarticulate more than adults. There are multiple, not mutually-exclusive, explanations for this pattern. For example, children may coarticulate more because they are limited by immature motor control. Or they may coarticulate more if they initially represent phonological segments in larger, more holistic units such as syllables or feet. We tested the importance of several different explanations for coarticulation in child speech by evaluating how four-year-olds' language experience, speech practice, and speech planning predicted their coarticulation between adjacent segments in real words and paired nonwords. Children with larger vocabularies coarticulated less, especially in real words, though there were no reliable coarticulatory differences between real words and nonwords after controlling for word duration. Children who vocalized more throughout a daylong audio recording also coarticulated less. Quantity of child vocalizations was more predictive of the degree of children's coarticulation than a measure of receptive language experience, adult word count. Overall, these results suggest strong roles for children's phonological representations and speech practice, as well as their immature fine motor control, for coarticulatory development.

Purpose: The purpose of this study was to evaluate the efficacy of a curriculum supplement designed to enhance awareness of Mainstream American English (MAE) in African American English- (AAE-) speaking prekindergarten children. Method: Children in 2 Head Start classrooms participated in the study. The experimental classroom received the Talking and Learning for Kindergarten program (Edwards, Rosin, Gross, & Chen, 2013), which used contrastive analysis to highlight morphological, phonological, and pragmatic differences between MAE and AAE. The control classroom received the Kindness Curriculum (Flook, Goldberg, Pinger, & Davidson, 2014), which was designed to promote mindfulness and emotional self-regulation. The amount of instruction was the same across the 2 programs. Both classrooms participated in pre- and posttest assessments. Results: Children in the experimental classroom, but not the control classroom, showed significant improvement in 3 norm-referenced measures of phonological awareness and in an experimental measure that evaluated comprehension of words that are ambiguous in AAE, but unambiguous in MAE, because of morphological and phonological differences between the 2 dialects. Conclusion: Although more research needs to be done on the efficacy of the Talking and Learning for Kindergarten program, these results suggest that it is possible to enhance AAE-speaking children's awareness of MAE prior to kindergarten entry.

This study was designed to investigate the relationship between vocabulary size and the speed and accuracy of lexical processing in preschoolers between the ages of 30 and 46 months using an automatic eye tracking task based on the looking-while-listening paradigm (Fernald, Zangl, Portillo, & Marchman, 2008) and mispronunciation paradigm (White & Morgan, 2008). Children's eye gaze patterns were tracked while they looked at two pictures (one familiar object, one unfamiliar object) on a computer screen and simultaneously heard one of three kinds of auditory stimuli: correct pronunciations of the familiar object's name, one-feature mispronunciations of the familiar object's name, or a nonword. The results showed that children with larger expressive vocabularies, relative to children with smaller expressive vocabularies, were more likely to look to a familiar object upon hearing a correct pronunciation and to an unfamiliar object upon hearing a novel word. Results also showed that children with larger expressive vocabularies were more sensitive to mispronunciations; they were more likely to look toward the unfamiliar object rather than the familiar object upon hearing a one-feature mispronunciation of a familiar object-name. These results suggest that children with smaller vocabularies, relative to their larger-vocabulary age peers, are at a disadvantage for learning new words, as well as for processing familiar words.