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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.
Elissa Lee Newport is a professor of neurology and director of the Center for Brain Plasticity and Recovery at Georgetown University.She specializes in language acquisition and developmental psycholinguistics, focusing on the relationship between language development and language structure, and most recently on the effects of pediatric stroke on the organization and recovery of language.
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]
It is also published in association with a biennial monograph, the Language Learning-Max Planck Institute Cognitive Neurosciences Series. According to the Journal Citation Reports , the journal has a 2011 impact factor of 1.218, ranking it 26th out of 161 journals in the category "Linguistics" [ 2 ] and 42nd out of 203 journals in the category ...
The Piotrowski law is a case of the so-called logistic model (cf. logistic equation). It was shown that it covers also language acquisition processes (cf. language acquisition law). Text block law: Linguistic units (e.g. words, letters, syntactic functions and constructions) show a specific frequency distribution in equally large text blocks.
The fact that during language acquisition, children are largely only exposed to positive evidence, [8] meaning that the only evidence for what is a correct form is provided, and no evidence for what is not correct, [9] was a limitation for the models at the time because the now available deep learning models were not available in late 1980s.
The Child Language Data Exchange System (CHILDES) is a corpus established in 1984 [1] by Brian MacWhinney and Catherine Snow to serve as a central repository for data of first language acquisition. [ 2 ] [ 1 ] Its earliest transcripts date from the 1960s, and as of 2015 has contents (transcripts, audio, and video) in 26 languages from 230 ...
Statistical natural language processing uses stochastic, probabilistic and statistical methods, especially to resolve difficulties that arise because longer sentences are highly ambiguous when processed with realistic grammars, yielding thousands or millions of possible analyses.