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The role of statistical learning in language acquisition has been particularly well documented in the area of lexical acquisition. [1] One important contribution to infants' understanding of segmenting words from a continuous stream of speech is their ability to recognize statistical regularities of the speech heard in their environments. [1]
Statistical language acquisition, a branch of developmental psycholinguistics, studies the process by which humans develop the ability to perceive, produce, comprehend, and communicate with natural language in all of its aspects (phonological, syntactic, lexical, morphological, semantic) through the use of general learning mechanisms operating on statistical patterns in the linguistic input.
Statistical learning (and more broadly, distributional learning) can be accepted as a component of language acquisition by researchers on either side of the "nature and nurture" debate. From the perspective of that debate, an important question is whether statistical learning can, by itself, serve as an alternative to nativist explanations for ...
Quantitative linguistics deals with language learning, language change, and application as well as structure of natural languages. QL investigates languages using statistical methods; its most demanding objective is the formulation of language laws and, ultimately, of a general theory of language in the sense of a set of interrelated languages ...
Proponents of statistical learning believe that it is the basis for higher level learning, and that humans use the statistical information to create a database which allows them to learn higher-order generalizations and concepts. For a child acquiring language, the challenge is to parse out discrete segments from a continuous speech stream.
Neurolinguistics research investigates several topics, including where language information is processed, how language processing unfolds over time, how brain structures are related to language acquisition and learning, and how neurophysiology can contribute to speech and language pathology.
The Competition Model is a psycholinguistic theory of language acquisition and sentence processing, developed by Elizabeth Bates and Brian MacWhinney (1982). [1] The claim in MacWhinney, Bates, and Kliegl (1984) [2] is that "the forms of natural languages are created, governed, constrained, acquired, and used in the service of communicative functions."
A language model is a probabilistic model of a natural language. [1] In 1980, the first significant statistical language model was proposed, and during the decade IBM performed ‘Shannon-style’ experiments, in which potential sources for language modeling improvement were identified by observing and analyzing the performance of human subjects in predicting or correcting text.