Statistical Language Learning

@article{Saffran2003StatisticalLL,
  title={Statistical Language Learning},
  author={Jenny R. Saffran},
  journal={Current Directions in Psychological Science},
  year={2003},
  volume={12},
  pages={110 - 114}
}
  • J. Saffran
  • Published 1 August 2003
  • Linguistics
  • Current Directions in Psychological Science
What types of mechanisms underlie the acquisition of human language? Recent evidence suggests that learners, including infants, can use statistical properties of linguistic input to discover structure, including sound patterns, words, and the beginnings of grammar. These abilities appear to be both powerful and constrained, such that some statistical patterns are more readily detected and used than others. Implications for the structure of human languages are discussed. 

Figures from this paper

Domain general constraints on statistical learning.

TLDR
Infant's learning of visual patterns shows the same constraints as infants' learning of phonotactic patterns, consistent with theories suggesting that constraints arise from domain-general sources and, as such, should operate over many kinds of stimuli in addition to linguistic stimuli.

A Role for Chunk Formation in Statistical Learning of Second Language Syntax.

TLDR
The present study compared adult learning of syntax and the ability of two models of statistical learning to simulate human performance: Simple Recurrent Networks and PARSER, which learns chunks as a byproduct of general principles of associative learning and memory.

Statistical learning and developmental language impairments

TLDR
Important studies of statistical learning are reviewed and how these perspectives may be used to improve the study of developmental language impairments and their remedial treatment and a particular focus is on the prospects of designing training tasks in a non-linguistic domain of behavior.

Learning and Long-Term Retention of Large-Scale Artificial Languages

TLDR
A large-scale learning experiment is reported that demonstrates that adults can learn words from unsegmented input in much larger languages than previously documented and that they retain the words they learn for years, suggesting that statistical word segmentation could be scalable to the challenges of lexical acquisition in natural language learning.

Exclusion Constraints Facilitate Statistical Word Learning

TLDR
In environments in which performance could benefit from exclusion, a learning advantage for speech over nonspeech is found, revealing an interaction between statistical and exclusion processes in associative word learning.

Two Distinct Sequence Learning Mechanisms for Syntax Acquisition and Word Learning

TLDR
It is demonstrated that the learning of repeating sequences is related to vocabulary development in these children, suggesting that there may be at least two relatively distinct domain-general sequential processing skills, with each supporting a different aspect of language acquisition.

Ecological theory of language acquisition

An ecological approach to early language acquisition is presented in this article. The general view is that the ability of language communication must have arisen as an evolutionary adaptation to the

Neural substrates of language acquisition.

TLDR
Developmental neuroscience studies using language are beginning to answer questions about the origins of humans' language faculty, and individual continuity in linguistic development from infants' earliest responses to phonemes is reflected in infants' language abilities in the second and third year of life.
...

References

SHOWING 1-10 OF 25 REFERENCES

The Use of Predictive Dependencies in Language Learning

To what extent is linguistic structure learnable from statistical information in the input? This research investigated the role played by statistical learning in the acquisition of rudimentary phrase

Constraints on Statistical Language Learning

Abstract How do learners discover the structure in linguistic input? One set of cues which learners might use to acquire phrase structure are the dependencies, or predictive relationships, which link

Pattern induction by infant language learners.

TLDR
9-month-old infants were given the opportunity to induce specific phonological patterns in 3 experiments in which syllable structure, consonant voicing position, and segmental position were manipulated and revealed that infants rapidly extracted new phonological regularities.

Statistical Learning by 8-Month-Old Infants

TLDR
The present study shows that a fundamental task of language acquisition, segmentation of words from fluent speech, can be accomplished by 8-month-old infants based solely on the statistical relationships between neighboring speech sounds.

Does Grammar Start Where Statistics Stop?

How do we acquire language? Do we identify words in a stream of speech by identifying statistical regularities or by seeking grammatical structure? A new study of adults ([PeA±a][1] et al .) suggests

From Syllables to Syntax: Multilevel Statistical Learning by 12-Month-Old Infants

To successfully acquire language, infants must be able to track multiple levels of regularities in the input. In many cases, regularities only emerge after some learning has already occurred. For

Signal-Driven Computations in Speech Processing

TLDR
It is shown that both statistical computations to identify words in speech and algebraic-like computation to discover higher level (grammatical) structure can be influenced by subtle cues in the speech signal.