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Early language acquisition: cracking the speech code

Early language acquisition: cracking the speech code Infants learn their native language quickly and effortlessly, and follow the same developmental path regardless of culture. However, it has proved difficult to understand how they do this, or to build computers that can reproduce this feat. An early and essential task for infants is to make sense of the speech that they hear. Each language uses a unique set of about 40 phonemes, and infants must learn to partition varied speech sounds into these phonemic categories. Young infants are sensitive to subtle differences between all phonetic units, whereas older children lose their sensitivity to distinctions that are not used in their native language. The loss of discrimination for foreign-language distinctions is paralleled by an increase in sensitivity to native-language phonetic units. There is evidence that infants analyse the statistical distributions of sounds that they hear in ambient language, and use this information to form phonemic categories. They also learn phonotactic rules — language-specific rules that govern the sequences of phonemes that can be used to compose words. To identify word boundaries, infants can use both transitional probabilities between syllables, and prosodic cues, which relate to linguistic stress. Most languages are dominated by either trochaic words (with the stress on the first syllable) or iambic ones (with the stress on later syllables). Infants seem to use a combination of statistical and prosodic cues to segment words in speech. Social influences are important in speech learning. Infants learn more easily from interactions with human beings speaking another language than they do from audiovisual exposure to the same language material, and their speech is strongly influenced by the response of others around them, such as their mothers. The importance of social input in language learning has some similarities to social influences on song learning in birds. Language experience causes neural changes. One hypothesis, native language neural commitment (NLNC), proposes that language learning produces dedicated neural networks that code the patterns of native-language speech. As these networks develop, they make it easier for new speech elements and patterns to be learned if they are consistent with the existing patterns, but place constraints on the learning of foreign-language patterns. NLNC might explain the closing of the 'sensitive period' for language learning; once a certain amount of learning has occurred, neural commitment interferes with the learning of new languages so they cannot be learned as easily. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Nature Reviews Neuroscience Springer Journals

Early language acquisition: cracking the speech code

Nature Reviews Neuroscience , Volume 5 (11) – Nov 1, 2004

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References (180)

Publisher
Springer Journals
Copyright
Copyright © 2004 by Nature Publishing Group
Subject
Biomedicine; Biomedicine, general; Neurosciences; Behavioral Sciences; Biological Techniques; Neurobiology; Animal Genetics and Genomics
ISSN
1471-003X
eISSN
1471-0048
DOI
10.1038/nrn1533
Publisher site
See Article on Publisher Site

Abstract

Infants learn their native language quickly and effortlessly, and follow the same developmental path regardless of culture. However, it has proved difficult to understand how they do this, or to build computers that can reproduce this feat. An early and essential task for infants is to make sense of the speech that they hear. Each language uses a unique set of about 40 phonemes, and infants must learn to partition varied speech sounds into these phonemic categories. Young infants are sensitive to subtle differences between all phonetic units, whereas older children lose their sensitivity to distinctions that are not used in their native language. The loss of discrimination for foreign-language distinctions is paralleled by an increase in sensitivity to native-language phonetic units. There is evidence that infants analyse the statistical distributions of sounds that they hear in ambient language, and use this information to form phonemic categories. They also learn phonotactic rules — language-specific rules that govern the sequences of phonemes that can be used to compose words. To identify word boundaries, infants can use both transitional probabilities between syllables, and prosodic cues, which relate to linguistic stress. Most languages are dominated by either trochaic words (with the stress on the first syllable) or iambic ones (with the stress on later syllables). Infants seem to use a combination of statistical and prosodic cues to segment words in speech. Social influences are important in speech learning. Infants learn more easily from interactions with human beings speaking another language than they do from audiovisual exposure to the same language material, and their speech is strongly influenced by the response of others around them, such as their mothers. The importance of social input in language learning has some similarities to social influences on song learning in birds. Language experience causes neural changes. One hypothesis, native language neural commitment (NLNC), proposes that language learning produces dedicated neural networks that code the patterns of native-language speech. As these networks develop, they make it easier for new speech elements and patterns to be learned if they are consistent with the existing patterns, but place constraints on the learning of foreign-language patterns. NLNC might explain the closing of the 'sensitive period' for language learning; once a certain amount of learning has occurred, neural commitment interferes with the learning of new languages so they cannot be learned as easily.

Journal

Nature Reviews NeuroscienceSpringer Journals

Published: Nov 1, 2004

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