The DOI matches its Crossref record; 35 of the 50 references it cites were found in a registry or an index.
Distributional regularity and phonotactic constraints are useful for segmentation
Open accessAbstract
In order to acquire a lexicon, young children must segment speech into words, even though most words are unfamiliar to them. This is a non-trivial task because speech lacks any acoustic analog of the blank spaces between printed words. Two sources of information that might be useful for this task are distributional regularity and phonotactic constraints. Informally, distributional regularity refers to the intuition that sound sequences that occur frequently and in a variety of contexts are better candidates for the lexicon than those that occur rarely or in few contexts. We express that intuition formally by a class of functions called DR functions. We then put forth three hypotheses: First, that children segment using DR functions. Second, that they exploit phonotactic constraints on the possible pronunciations of words in their language. Specifically, they exploit both the requirement that every word must have a vowel and the constraints that languages impose on word-initial and word-final consonant clusters. Third, that children learn which word-boundary clusters are permitted in their language by assuming that all permissible word-boundary clusters will eventually occur at utterance boundaries. Using computational simulation, we investigate the effectiveness of these strategies for segmenting broad phonetic transcripts of child-directed English. The results show that DR functions and phonotactic constraints can be used to significantly improve segmentation. Further, the contributions of DR functions and phonotactic constraints are largely independent, so using both yields better segmentation than using either one alone. Finally, learning the permissible word-boundary clusters from utterance boundaries does not degrade segmentation performance.
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“Across a language sample, sounds that co-occur within words tend to be more highly correlated with one another than sound pairs spanning word boundaries.”
From Incidental Language Learning: Listening (and Learning) Out of the Corner of Your Ear (1997) · cites this paper as Brent & Cartwright, 1996
Experimental — accuracy not yet measuredThe cited source says what the claim attributes to it.
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“infants may be able to exploit statistical cues to word boundaries”
From Incidental Language Learning: Listening (and Learning) Out of the Corner of Your Ear (1997) · cites this paper as Brent & Cartwright, 1996
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“recent computational models of language acquisition suggest that at least some pertinent language-learning mechanisms may induce structure from the input using statistical methods similar to those suggested by incidental-learning research”
From Incidental Language Learning: Listening (and Learning) Out of the Corner of Your Ear (1997) · cites this paper as Brent & Cartwright, 1996
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Citations
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Statistical learning by 8-month-old infants
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Metadata
- Authors
- Brent, M. R., & Cartwright, T. A.
- Affiliations
- Johns Hopkins University (US)
- Corresponding author
- Brent, Michael R.
- ORCID
- Brent, Michael R.
- Venue
- Cognition
- Publisher
- Elsevier BV
- Published
- 1996-10
- Volume
- 61
- Issue
- 1-2
- Pages
- 93-125
- ISSN
- 0010-0277 (ISSN-L)
- OpenAlex
- W2029948425
- Cited by
- 514
- References
- 50
- Citations by year
- 2026: 5 · 2025: 4 · 2024: 4 · 2023: 7 · 2022: 44 · 2021: 12 · 2020: 9 · 2019: 13 · 2018: 10 · 2017: 13 · 2016: 35 · 2015: 24 · 2014: 14 · 2013: 15 · 2012: 15
- FWCI
- 31.09
- Type
- journal article
- Language
- en
- Open access
- hybrid
- doi.org
- Licence
- Locations
- Cognition (publishedVersion, cc-by-nc-nd)
- PubMed (publishedVersion)
- 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
- speech segmentation, phonotactic constraints, word learning, child language acquisition, word boundaries, consonant clusters, utterance boundaries, computer simulation
- MeSH terms
- Adult, Algorithms, Attention, Child, Child, Preschool, Female, Humans, Infant, Language Development, Male, Phonetics, Mental Recall, Verbal Learning, Vocabulary
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