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Statistical Word Learning in Children with Autism Spectrum Disorder and Specific Language Impairment
Haebig, Eileen; Saffran, Jenny R.; Ellis Weismer, Susan – Journal of Child Psychology and Psychiatry, 2017
Background: Word learning is an important component of language development that influences child outcomes across multiple domains. Despite the importance of word knowledge, word-learning mechanisms are poorly understood in children with specific language impairment (SLI) and children with autism spectrum disorder (ASD). This study examined…
Descriptors: Autism, Pervasive Developmental Disorders, Language Impairments, Cognitive Processes
Romberg, Alexa R.; Saffran, Jenny R. – Cognitive Science, 2013
Natural languages contain many layers of sequential structure, from the distribution of phonemes within words to the distribution of phrases within utterances. However, most research modeling language acquisition using artificial languages has focused on only one type of distributional structure at a time. In two experiments, we investigated adult…
Descriptors: Artificial Languages, Second Language Learning, Adults, Adult Learning
Hay, Jessica F.; Saffran, Jenny R. – Infancy, 2012
Linguistic stress and sequential statistical cues to word boundaries interact during speech segmentation in infancy. However, little is known about how the different acoustic components of stress constrain statistical learning. The current studies were designed to investigate whether intensity and duration each function independently as cues to…
Descriptors: Infants, Bias, Acoustics, Cues
Lany, Jill; Saffran, Jenny R. – Developmental Science, 2011
Infants can use statistical regularities to form rudimentary word categories (e.g. noun, verb), and to learn the meanings common to words from those categories. Using an artificial language methodology, we probed the mechanisms by which two types of statistical cues (distributional and phonological regularities) affect word learning. Because…
Descriptors: Infants, Language Acquisition, Statistics, Semantics