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All fields Title Creator / Publisher Keyword Year AND OR AND NOT All fields Title Creator / Publisher Keyword Year AND OR AND NOT All fields Title Creator / Publisher Keyword Year AND OR AND NOT All fields Title Creator / Publisher Keyword Year AND OR AND NOT All fields Title Creator / Publisher Keyword Year Sort by creator [A → Z]' creator [Z → A]' publishing year ↑ (asc)' publishing year ↓ (desc)' title [A → Z]' title [Z → A]' Simple Search Hits 1 – 2 of 2 1 Phonology impacts segmentation and generalization in speech processing Onnis, L; Monaghan, P; Chater, N... In: Journal of Memory and Language , 53 pp. 225-237. (2005) (2005) BASE Show details 2 Phonology impacts segmentation in online speech processing Onnis, L; Monaghan, P; Richmond, K; Chater, N In: J MEM LANG , 53 (2) 225 - 237. (2005) (2005) Abstract: Pena, Bonatti, Nespor, and Mehler (2002) investigated an artificial language where the structure of words was determined by nonadjacent dependencies between syllables. They found that segmentation of continuous speech could proceed on the basis of these dependencies. However, Pena et al.'s artificial language contained a confound in terms of phonology, in that the dependent syllables began with plosives and the intervening syllables began with continuants. We consider three hypotheses concerning the role of phonology in speech segmentation in this task: (1) participants may recruit probabilistic phonotactic information from their native language to the artificial language learning task; (2) phonetic properties of the stimuli, such as the gaps that precede unvoiced plosives, can influences segmentation; and (3) grouping by phonological similarity, between dependent syllables contributes to learning the dependency. In a series of experiments controlling the phonological and statistical structure of the language, we found that segmentation performance is influenced by the three factors in different degrees. Learning of nonadjacent dependencies did not occur when (3) is eliminated. We suggest that phonological processing provides a fundamental contribution to distributional analysis. (c) 2005 Elsevier Inc. All rights reserved. Keyword: 8-MONTH-OLD INFANTS; artificial language learning; CUES; GRAMMAR; phonology; segmentation; statistical learning; STATISTICS; WORD SEGMENTATION URL: http://discovery.ucl.ac.uk/146898/ BASE Hide details

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