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Daniel Swingley; Robin Algayres – Cognitive Science, 2024
Computational models of infant word-finding typically operate over transcriptions of infant-directed speech corpora. It is now possible to test models of word segmentation on speech materials, rather than transcriptions of speech. We propose that such modeling efforts be conducted over the speech of the experimental stimuli used in studies…
Descriptors: Sentences, Word Recognition, Psycholinguistics, Infants
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Ota, Mitsuhiko; Skarabela, Barbora – Language Learning and Development, 2016
Infants' disposition to learn repetitions in the input structure has been demonstrated in pattern generalization (e.g., learning the pattern ABB from the token "ledidi"). This study tested whether a repetition advantage can also be found in lexical learning (i.e., learning the word "lele" vs. "ledi"). Twenty-four…
Descriptors: Infants, English, Language Acquisition, Repetition
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Hay, Jessica F.; Pelucchi, Bruna; Estes, Katharine Graf; Saffran, Jenny R. – Cognitive Psychology, 2011
The processes of infant word segmentation and infant word learning have largely been studied separately. However, the ease with which potential word forms are segmented from fluent speech seems likely to influence subsequent mappings between words and their referents. To explore this process, we tested the link between the statistical coherence of…
Descriptors: Novelty (Stimulus Dimension), Infants, Word Recognition, Probability
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Johnson, Elizabeth K.; Tyler, Michael D. – Developmental Science, 2010
Past research has demonstrated that infants can rapidly extract syllable distribution information from an artificial language and use this knowledge to infer likely word boundaries in speech. However, artificial languages are extremely simplified with respect to natural language. In this study, we ask whether infants' ability to track transitional…
Descriptors: Cues, Artificial Languages, Testing, Infants
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Pelucchi, Bruna; Hay, Jessica F.; Saffran, Jenny R. – Cognition, 2009
Numerous recent studies suggest that human learners, including both infants and adults, readily track sequential statistics computed between adjacent elements. One such statistic, transitional probability, is typically calculated as the likelihood that one element predicts another. However, little is known about whether listeners are sensitive to…
Descriptors: Infants, Test Items, Prediction, Probability
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Gerken, LouAnn – Cognition, 2004
Infants' ability to rapidly extract properties of language-like systems during brief laboratory exposures has been taken as evidence about the innate linguistic state of humans. However, previous studies have focused on structural properties that are not central to descriptions of natural language. In the current study, infants were exposed to 3-…
Descriptors: Infants, Natural Language Processing, Structural Linguistics, Syllables
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Gomez, Rebecca; Maye, Jessica – Infancy, 2005
We investigated the developmental trajectory of nonadjacent dependency learning in an artificial language. Infants were exposed to 1 of 2 artificial languages with utterances of the form [aXc or bXd] (Grammar 1) or [aXd or bXc] (Grammar 2). In both languages, the grammaticality of an utterance depended on the relation between the 1st and 3rd…
Descriptors: Age, Artificial Languages, Infants, Natural Language Processing