Children’s early word learning is to a large extent driven by the prevalence of words in their language environment, with words that are spoken more often to children being learned earlier. However, children receive language from a variety of sources, including books, television, and movies meant for children, as well as speech and media that is meant for adults, but over- heard by children. Despite considerable similarity of word frequency distributions from these different input sources, there is also significant and predictable variability between them. For example, function words are far more frequent in books than in everyday speech, while early-learned nouns (e.g., ‘ball’ and ‘mommy’) are more frequent in child-directed speech than in other sources. Children receive a mixture of these different frequency distributions. The goal of this paper is to better understand the shared and unique variance in these input sources – in both English and French – and to evaluate how predictive these distributions are of children’s early word learning.

Infants learn language by exposure to streams of speech pro-duced by their caregivers. Early on, they manage to segmentword forms out of this continuous input, which is either di-rectly addressed to them, or directed to other adults, thus over-heard. It has been suggested that infant-directed speech is sim-plified and could facilitate language learning. This study aimedto investigate whether features such as utterance length, seg-mentation entropy and lexical diversity could account for anadvantage in segmentability of infant-directed speech. A largeset of word segmentation algorithms was used on an ecolog-ically valid corpus, consisting of 18 sets of recordings gath-ered from French-learning infants aged 3-48 months. A se-ries of textual analyses confirmed several simplicity featuresof infant-, compared to adult-directed speech. A small seg-mentation advantage was also documented, which could notbe attributed to any of those corpus features. Some particular-ities of the data invite further research on more corpora.

What factors contribute to the growth of children's early vocabulary? One method for exploring this question is investigating predictors (e.g., frequency) that differentiate words learnt earlier from those learnt later. A more comprehensive account requires the examination of multiple language families and multiple levels of linguistic representation (e.g., phonological, morphosyntactic, semantic). Here, we studied 10 predictors of word ages of acquisition across 27 languages and dialects. We found that words that were more frequent, concrete, and associated with babies were learnt earlier, whereas words that had greater length in phonemes and mean length of utterance were learnt later. There was no reliable effect of other morphosyntactic predictors, or of phonological neighbourhood. We found evidence of a tradeoff between a language's morphological complexity and the effect of syntactic complexity for predicates, supporting the competition model. Predictor coefficients revealed broad consistency across all languages, along with variability that reflected language family classifications.