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Two for the price of one: Concurrent learning of words and phonotactic regularities from continuous speech
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In: PLoS One (2021)
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Statistical language learning in infancy
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In: Child Dev Perspect (2020)
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Tuning in to non-adjacencies: Exposure to learnable patterns supports discovering otherwise difficult structures
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In: Cognition (2020)
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Sampling to learn words: Adults and children sample words that reduce referential ambiguity
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In: Dev Sci (2020)
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Non-Linguistic Grammar Learning by 12-Month-Old Infants: Evidence for Constraints on Learning
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Statistical learning of multiple speech streams: A challenge for monolingual infants
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In: Dev Sci (2019)
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Assessing Fine-Grained Speech Discrimination in Young Children With Bilateral Cochlear Implants
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Spectral tilt as a cue to word segmentation in infancy and adulthood. ...
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Spectral tilt as a cue to word segmentation in infancy and adulthood. ...
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Roses Are Red, Socks Are Blue: Switching Dimensions Disrupts Young Children’s Language Comprehension
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Early Lexical Comprehension in Young Children with ASD: Comparing Eye-Gaze Methodology and Parent Report
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Infants with Williams Syndrome Detect Statistical Regularities in Continuous Speech
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Second language experience facilitates statistical learning of novel linguistic materials
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Toddlers encode similarities among novel words from meaningful sentences
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Anticipatory coarticulation facilitates word recognition in toddlers
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From flexibility to constraint: The contrastive use of lexical tone in early word learning
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Statistical learning of a tonal language: the influence of bilingualism and previous linguistic experience
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Distributional structure in language: Contributions to noun–verb difficulty differences in infant word recognition
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Abstract:
What makes some words easy for infants to recognize, and other words difficult? We addressed this issue in the context of prior results suggesting that infants have difficulty recognizing verbs relative to nouns. In this work, we highlight the role played by the distributional contexts in which nouns and verbs occur. Distributional statistics predict that English nouns should generally be easier to recognize than verbs in fluent speech. However, there are situations in which distributional statistics provide similar support for verbs. The statistics for verbs that occur with the English morpheme –ing, for example, should facilitate verb recognition. In two experiments with 7.5- and 9.5-month-old infants, we tested the importance of distributional statistics for word recognition by varying the frequency of the contextual frames in which verbs occur. The results support the conclusion that distributional statistics are utilized by infant language learners and contribute to noun–verb differences in word recognition.
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Keyword:
Article
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URL: http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4107307 http://www.ncbi.nlm.nih.gov/pubmed/24908342 https://doi.org/10.1016/j.cognition.2014.05.004
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