2019
DOI: 10.1016/j.jml.2019.05.003
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A computational model of reading across development: Effects of literacy onset on language processing

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Cited by 50 publications
(72 citation statements)
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References 95 publications
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“…A fully implemented triangle model of learning to read was developed Chang, Monaghan, & Welbourne , 2019;Harm & Seidenberg, 2004;Monaghan et al, 2017). The model learned to map between representations of orthography, phonology, and semantics of words.…”
Section: Simulation 1: Learning To Read An Artificial Orthographymentioning
confidence: 99%
See 1 more Smart Citation
“…A fully implemented triangle model of learning to read was developed Chang, Monaghan, & Welbourne , 2019;Harm & Seidenberg, 2004;Monaghan et al, 2017). The model learned to map between representations of orthography, phonology, and semantics of words.…”
Section: Simulation 1: Learning To Read An Artificial Orthographymentioning
confidence: 99%
“…Following previous simulation work (Chang, Welbourne & Monaghan, 2019;Harm & Seidenberg, 2004), the nearest neighbour measure was used to assess the phonological and semantic representations that the model developed. For testing the model's phonological output, we determined the number of words for which all phonemes were correctly produced.…”
Section: Testing Proceduresmentioning
confidence: 99%
“…In a theoretical position piece Frost (2012) This is not an issue for the broad theoretical framework, however it does place limitations on the validity of our results for consonantal systems, as the increased importance of pre-activated semantic information in consonantal systems from contextual information during reading is likely to have significant implications for the processing dynamics within the reading system. Exploring such an influence of pre-activated semantic information on the dynamics of processing in a consonantal system is a potential line of future investigation that could be explored using the modelling framework presented in this paper (see Chang, Monaghan & Welbourne, 2019).…”
Section: Discussionmentioning
confidence: 99%
“…Networks were trained on a total of 150,000 pre-literacy trials before the onset of literacy training. This ensured that networks were able to perform all tasks to a high degree of accuracy before the onset of literacy training: for the phonological retention and semantic retention tasks, accuracy was 100%; for the speech comprehension task (phonology to semantics mappings), accuracy was 95% (this was the maximum possible because 5% of the training patterns were indistinguishable without additional implementation of contextual information for meaning, e.g., Chang, Monaghan, and Welbourne, 2019, because of the inclusion of homophones in the training set); and for speech production (semantics to phonology mappings) accuracy was 100%. In each case, an accurate response was when the output at the final, 12 th step was closest to the target than to any other pattern in the training set, using cosine distance.…”
Section: Trainingmentioning
confidence: 99%
“…One in eight of the strategies that can be done to build early literacy is by providing activities that increase children's awareness [4], [6], [8], [9]. From the sound of language or that words consist of the smallest unit of sound, namely the alphabet [7], [8], [10]. These activities include playing games and listening to stories, reciting poems, and songs that involve poetry, identifying words that end with the same sound [5], [16], [17].…”
Section: Jampé-jampé Harupat Jampé-jampé Harupat Geura Gedé Geura Lumpatmentioning
confidence: 99%