Research project Studying building blocks of statistical learning: Automatic computation of auditory predictability
In the CAPSL project, we examine whether the language-related ability of statistical learning can be explained by a more general mechanism whereby the brain automatically detects when sounds follow different patterns or statistical distributions.
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Infants are sensitive to regularities in the auditory input, and pick up on them from brief and passive exposure. Statistical learning of regularities in the input is an important ability for language development.
There are no pauses between words in the speech signal. For someone who does not already know the words, it is therefore difficult to determine where word boundaries lie.
Infants can identify words in a continuous speech signal without pauses solely based on how frequently different syllables follow one another. This is called statistical learning.
When one can recognize patterns in the auditory signal, it becomes easier to determine which sounds belong together in complex sound environments. This occurs by identifying which sounds share the same or different sound sources.
By explicitly investigating the connection between the language-related ability of statistical learning and this more general mechanism, the CAPSL project can contribute to knowledge about infants’ language development, as well as to our understanding of language ability more broadly.