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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.
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.
It occurs in normal speech but becomes more common in more rapid speech. In some cases, assimilation causes the sound spoken to differ from the normal pronunciation in isolation, such as the prefix in-of English input pronounced with phonetic [m] rather than [n]. In this case, [n] becomes [m] since [m] is more phonetically similar to [p].
Supervised learning involves learning from a training set of data. Every point in the training is an input–output pair, where the input maps to an output. The learning problem consists of inferring the function that maps between the input and the output, such that the learned function can be used to predict the output from future input.
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.
Dogs are great communicators. No, our pups can’t use language in the same way as humans, but we can read a lot from their body language and the sounds they make.. And over the last few years ...
For example, if English-learning infants are exposed to a prevoiced /d/ to voiceless unaspirated /t/ continuum (similar to the /d/ - /t/ distinction in Spanish) with the majority of the tokens occurring near the endpoints of the continuum, i.e., showing extreme prevoicing versus long voice onset times (bimodal distribution) they are better at ...