Jove
Visualize
Contact Us
JoVE
x logofacebook logolinkedin logoyoutube logo
ABOUT JoVE
OverviewLeadershipBlogJoVE Help Center
AUTHORS
Publishing ProcessEditorial BoardScope & PoliciesPeer ReviewFAQSubmit
LIBRARIANS
TestimonialsSubscriptionsAccessResourcesLibrary Advisory BoardFAQ
RESEARCH
JoVE JournalMethods CollectionsJoVE Encyclopedia of ExperimentsArchive
EDUCATION
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab ManualFaculty Resource CenterFaculty Site
Terms & Conditions of Use
Privacy Policy
Policies

Related Experiment Videos

Statistical learning by 8-month-old infants

J R Saffran1, R N Aslin, E L Newport

  • 1Department of Brain and Cognitive Sciences, University of Rochester, Rochester, NY 14627, USA.

Science (New York, N.Y.)
|December 13, 1996
PubMed
Summary
This summary is machine-generated.

Related Concept Videos

You might also read

Related Articles

Articles linked to this work by shared authors, journal, and citation graph.

Sort by
Same author

Statistical learning in a serial reaction time task: access to separable statistical cues by individual learners.

Journal of experimental psychology. General·2002
Same author

Unsupervised statistical learning of higher-order spatial structures from visual scenes.

Psychological science·2002
Same author

The acquisition of language by children.

Proceedings of the National Academy of Sciences of the United States of America·2001
Same author

Infant long-term memory for music.

Annals of the New York Academy of Sciences·2001
Same author

Words in a sea of sounds: the output of infant statistical learning.

Cognition·2001
Same author

Absolute pitch in infant auditory learning: evidence for developmental reorganization.

Developmental psychology·2001
Same journal

Erratum for the Research Article "Detecting supramolecular organic nanoparticles during heat wave".

Science (New York, N.Y.)·2026
Same journal

Local signals, systemic decline.

Science (New York, N.Y.)·2026
Same journal

The mechanics of liver regeneration.

Science (New York, N.Y.)·2026
Same journal

Computing in a memory with physics.

Science (New York, N.Y.)·2026
Same journal

Retraction.

Science (New York, N.Y.)·2026
Same journal

Making time.

Science (New York, N.Y.)·2026
See all related articles

Infants can segment words from fluent speech using only statistical learning of sound patterns. This demonstrates a powerful innate mechanism for early language acquisition, even with minimal exposure.

Area of Science:

  • Cognitive Science
  • Developmental Psychology
  • Linguistics

Background:

  • Learners utilize both experience-independent and experience-dependent mechanisms for environmental information processing.
  • Language acquisition theories predominantly highlight the role of innate, experience-independent mechanisms.
  • The segmentation of words from continuous speech is a critical early language development task.

Purpose of the Study:

  • To investigate if infants can segment words from fluent speech using solely statistical learning.
  • To determine the minimal exposure required for infants to perform word segmentation via statistical learning.
  • To assess the capability of infants' statistical learning mechanisms in processing linguistic input.

Main Methods:

  • Exposing 8-month-old infants to 2 minutes of fluent speech.

Related Experiment Videos

  • Analyzing infants' ability to distinguish word boundaries based on statistical regularities between speech sounds.
  • Utilizing a statistical learning paradigm to evaluate auditory processing.

    • Main Results:

    • Infants successfully segmented words from fluent speech.
    • Segmentation was achieved based solely on statistical relationships between adjacent speech sounds.
    • This word segmentation occurred after only 2 minutes of exposure to the speech input.

    Conclusions:

    • Infants possess a powerful, experience-independent mechanism for statistical learning in language acquisition.
    • Statistical learning from auditory input is a fundamental component of early word segmentation.
    • The findings challenge the overemphasis on innate knowledge, highlighting the power of statistical computation in language development.