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1
Learning to assign lexical stress during reading aloud: corpus, behavioral, and computational investigations
In: Journal of memory and language. - Amsterdam [u.a.] : Elsevier 63 (2010) 2, 180-196
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2
Auditory discrimination of voice-onset time and its relationship with reading ability
In: Laterality. - Abingdon : Routledge, Taylor & Francis Group 15 (2010) 3, 343-360
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3
Learning to assign lexical stress during reading aloud: Corpus, behavioral, and computational investigations
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4
Auditory discrimination of voice-onset time and its relationship with reading ability
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5
Stressing what is important: Orthographic cues and lexical stress assignment
In: Journal of neurolinguistics. - Orlando, Fla. : Elsevier 22 (2009) 3, 237-249
OLC Linguistik
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6
Stressing what is important: orthographic cues and lexical stress assignment
In: Journal of neurolinguistics. - Orlando, Fla. : Elsevier 22 (2009) 3, 237-249
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7
Probabilistic Cues to Grammatical Category in English Orthography and Their Influence During Reading
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8
Stressing what is important: Orthographic cues and lexical stress assignment
Abstract: Computational models of reading have typically focused on monosyllabic words. However extending those models to polysyllabic word reading can uncover critical points of distinction between competing models. We present a connectionist model of stress assignment that learned to map orthography onto stress position for English disyllabic words. We compared the performance of the connectionist model to Rastle and Coltheart's [(2000).] rule-based model of stress assignment for words and nonwords. The connectionist model performed well on predicting human performance in reading nonwords that both contained and did not contain affixes, whereas the Rastle and Coltheart model performed well only oil nonwords with affixes. The connectionist model provides an important first step to simulating all aspects of polysyllabic word reading, and indicates that a probabilistic approach to stress assignment can reflect human performance on stress assignment for both words and nonwords. (C) 2008 Elsevier Ltd. All rights reserved.
URL: https://doi.org/10.1016/j.jneuroling.2008.09.002
https://eprints.lancs.ac.uk/id/eprint/52750/
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9
Constraints for Computational Models of Reading: Evidence from learning lexical stress
In: Monaghan, Padraic; Arciuli, Joanne; & Seva, Nada. (2008). Constraints for Computational Models of Reading: Evidence from learning lexical stress. Proceedings of the Cognitive Science Society, 30(30). Retrieved from: http://www.escholarship.org/uc/item/4kp333sg (2008)
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