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The sequence encoder was shown to learn wordform representations for large-scale English lexicons. Its ability to scale is due, in part, to overcoming the ...
A connectionist architecture termed the sequence encoder is used to learn nearly 75,000 wordform representations through exposure to strings of stress-marked ...
Feb 10, 2010 · Abstract The forms of words as they appear in text and speech are central to theories and models of lexical processing.
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A connectionist architecture termed the sequence encoder is used to learn nearly 75,000 wordform representations through exposure to strings of stress-marked ...
2008, Sibley DE, Kello CT, Plaut DC, Elman JL. Large-Scale Modeling of Wordform Learning and Representation. Cognitive Science. 32: 741-754. PMID 20107621 DOI: ...
In this chapter, we demonstrate how one might scale up models of visual word recognition using a system that learns orthographic representations, ...
This paper aims to find a mathematical and statistical way to express natural words' semantic information by mapping words onto a high-dimension continuous ...
Nonetheless, current methods for simulating their learning and representation fail to approach the scale and heterogeneity of real wordform lexicons. A ...
In this review, I provide an overview of computational models of reading, focussing on models of visual word recognition–how we recognise individual words.
Jun 7, 2024 · We simulated word learning in infants up to 12 months of age in a realistic setting, using a model that solely learns from statistical ...