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Concept
Statistical language acquisition
Summary
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 acquisition claims that infants' language-learning is based on pattern perception rather than an innate biological grammar. Several statistical elements such as frequency of words, frequent frames, phonotactic patterns and other regularities provide information on language structure and meaning for facilitation of language acquisition.
Fundamental to the study of statistical language acquisition is the centuries-old debate between rationalism (or its modern manifestation in the psycholinguistic community, nativism) and empiricism, with researchers in this field falling strongly in support of the latter category. Nativism is the position that humans are born with innate domain-specific knowledge, especially inborn capacities for language learning. Ranging from seventeenth century rationalist philosophers such as Descartes, Spinoza, and Leibniz to contemporary philosophers such as Richard Montague and linguists such as Noam Chomsky, nativists posit an innate learning mechanism with the specific function of language acquisition.
In modern times, this debate has largely surrounded Chomsky's support of a universal grammar, properties that all natural languages must have, through the controversial postulation of a language acquisition device (LAD), an instinctive mental 'organ' responsible for language learning which searches all possible language alternatives and chooses the parameters that best match the learner's environmental linguistic input. Much of Chomsky's theory is founded on the poverty of the stimulus (POTS) argument, the assertion that a child's linguistic data is so limited and corrupted that learning language from this data alone is impossible.
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