Cited by 352Language Development and DisordersPhonetics and Phonology ResearchReading and Literacy Development

The DOI matches its Crossref record; 51 of the 51 references it cites were found in a registry or an index.

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

Saffran, Jenny R·2001·Cognition

Abstract

One of the first problems confronting infant language learners is word segmentation: discovering the boundaries between words. Prior research suggests that 8-month-old infants can detect the statistical patterns that serve as a cue to word boundaries. However, the representational structure of the output of this learning process is unknown. This research assessed the extent to which statistical learning generates novel word-like units, rather than probabilistically-related strings of sounds. Eight-month-old infants were familiarized with a continuous stream of nonsense words with no acoustic cues to word boundaries. A post-familiarization test compared the infants' responses to words versus part-words (sequences spanning a word boundary) embedded either in simple English contexts familiar to the infants (e.g. "I like my tibudo"), or in matched nonsense frames (e.g. "zy fike ny tibudo"). Listening preferences were affected by the context (English versus nonsense) in which the items from the familiarization phase were embedded during testing. A second experiment confirmed that infants can discriminate the simple English contexts and the matched nonsense frames used in Experiment 1. The third experiment replicated the results of Experiment 1 by contrasting the English test frames with non-linguistic frames generated from tone sequences. The results support the hypothesis that statistical learning mechanisms generate word-like units with some status relative to the native languag…

Overview

Integrity signals

Registry

Crossref · 10.1016/s0010-0277(01)00132-9

Cites

51 of 51 references verified0 citation errors · 0 not checkable

Statistics

Recomputing p-values needs the paper’s full text.

Verification

Claims the paper makes

This paper’s full text isn’t openly available, so its claims and self-check weren’t run. The registry and citation checks still apply.

Claims other papers make about this one

Each is checked against this paper’s own text: does it say what the citing paper says it does?

Citations

Cites

Show all 50 references

Research works printed but not linked: 1

  1. Aslin, R. N. (2000). Interpretation of infant listening times using the headturn preference technique. Talk presented at the International Conference on Infancy Studies, Brighton, UK.

Cited by

Sorted by citations

See all 352

Metadata

Authors
Saffran, J. R.
Affiliations
University of Wisconsin–Madison (US)
Corresponding author
Saffran, Jenny R
Venue
Cognition
Publisher
Elsevier BV
Published
2001-09
Volume
81
Issue
2
Pages
149-169
ISSN
0010-0277 (ISSN-L)
OpenAlex
W2159265825
Cited by
352
References
50
Citations by year
2026: 2 · 2025: 8 · 2024: 6 · 2023: 11 · 2022: 7 · 2021: 8 · 2020: 12 · 2019: 72 · 2018: 9 · 2017: 12 · 2016: 10 · 2015: 15 · 2014: 9 · 2013: 12 · 2012: 11
FWCI
11.48
Type
journal article
Language
en
Open access
closed
Locations
  • Cognition (publishedVersion)
  • PubMed (publishedVersion)
Funders
  • University of Wisconsin-Madison
  • Eunice Kennedy Shriver National Institute of Child Health and Human Development (HD 03352, HD37466, P30HD003352)
Topics
  • Social Sciences › Psychology › Developmental and Educational Psychology › Language Development and Disorders
  • Social Sciences › Psychology › Experimental and Cognitive Psychology › Phonetics and Phonology Research
  • Social Sciences › Psychology › Developmental and Educational Psychology › Reading and Literacy Development
Keywords
word segmentation, word boundaries, context effects, listening preferences, tone sequences, language acquisition, infant language acquisition
MeSH terms
Auditory Perception, Child Development, Female, Humans, Infant, Language Development, Male, Noise, Semantics

About these checks

Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.

Statistics and arithmetic are recomputed, not judged.

Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.

What counts as a claim ›How we measure confidence ›How we check this ›

Are you an author, or do you see a problem with this page? Request a review